Patent Application
20240416137
The application generally relates to methods, devices and systems for providing personalized intelligent self-adaptive bioelectromagnetic therapy.
Bioelectromagnetic therapy has been used as a non-invasive physical therapy to address injury and disease, including cancer, bone non-union fractures and pain. For example, in the case of a bone fracture, studies have shown that the rate of non-union of a fracture may be reduced in people who have used electromagnetic stimulation in their treatment. Contradictory studies, however, show minimal or no benefit of using bioelectromagnetic therapy for bone healing.
One reason for inconsistent clinical efficacy of bioelectromagnetic therapy is due to the subjective nature of determining dosages and regimens of electrical stimulation by the medical practitioner. A clinician may select protocols based on animal studies or based on protocols used for other patients. As there is no rigorous way to determine the ideal physical parameters for the applied bioelectromagnetic therapy, clinicians have generally adopted a therapeutic approach based on a limited sense of historical equivalencies. However, the lack of optimized conditions inevitably leads to variability in clinical outcomes, including treatment failure. This variability has precluded bioelectromagnetic therapy becoming a standard of care for applicable diseases and injuries. In addition to variability, many protocols and systems used for applying bioelectromagnetic therapy are inconvenient and impractical to use leading to poor patient compliance and other undesirable complications.
Knowledge processing has been incorporated into treatment methods in order to try to customize a treatment profile more closely to that of the patient. Generally, these methods require the generation of a profile of the patient that includes demographics, physiological data and characteristics of the condition for which treatment is sought. The patient profile is compared to a patient analytics database that comprises data compiled on a plurality of individuals to determine a recommended therapy, based on matching the patient profile to an individual with the most similar characteristics. While treatment outcome may be improved, this approach is not truly unique to the patient, but rather, most similar to the matched historical individual.
Identifying a less subjective and more personalized treatment approach for patient bioelectromagnetic therapy is projected to lead to more optimal therapeutic outcomes.
The above discussion is not intended as an admission that any of the foregoing is pertinent prior art.
In view of the foregoing limitations and shortcomings of presently used bioelectromagnetic treatment methods, as well as other disadvantages not specifically mentioned above, a more precise and effective bioelectromagnetic therapy approach is desired.
There are several variables involved with presently used approaches and regimens for administering therapeutic electrical fields to a target area for treatment. Electrical fields can be applied using direct current via implanted electrodes at the treatment target site, by the generation of transient alternating currents at the treatment target site using capacitively-coupled electrodes, or inductive stimulation using coils to generate an electromagnetic field (EMF) at the treatment target site. With respect to capacitively-coupled or inductively-coupled EMF treatments, a variety of electrode or coil arrangements and designs are possible. Electrodes/coils are positioned in close proximity to the target site of treatment. Problems may arise due to self-inductance and background electrical interference. Depending on the size of the target treatment area, a wider spacing of the active components may be required causing a decrease in the EMF strength. Further, electrodes/coils contoured to a curvature of the treatment area may distort the induced field leading to variable treatment results.
There is also considerable variability with respect to the biology of a patient that may influence the outcome of EMF treatment. For example, variability exists due to the patient's biometrics, genetics, medical history, comorbidities and high-risk lifestyle factors. Variability also exists with respect to the type of injury, trauma, disorder or disease. Injuries may be superficial or within a deeper structure. The tissue and cellular milieu of an injury is unique with the cells having an influence on electrical activation and activation selectivity.
There is also variability in the starting point for adoption of bioelectromagnetic therapy within the progression of the disease or injury repair along with inherent changes in the required biological cascade throughout the treatment process.
Living tissues comprise complex cellular architectures. Cells of the body have built in electromagnetic attributes such that they are exquisitely responsive to electromagnetic stimulation of exactly the right frequency and amplitude. The endogenous bioelectric field and current transmission in a tissue in turn affects: cell membrane capacitance, permeability of the cell membrane, signaling mechanisms of the cell membrane, intracellular mineral concentrations, nutrient flow into the cell and waste disposal. The composition and degree of injury of a tissue will affect the bioelectric field and the flow of current therein. Bioelectromagnetic therapy can trigger or enhance inherent bioelectric events underway within the cells and tissues in response to injury or disease and thus assist in healing and repair.
The cellular architecture of an injury/disease varies upon the length of time since the occurrence of the injury/disease and/or concurrent biological events such as inflammation, and potential re-injury of the same tissue in a subject. This is more pronounced between different subjects for a variety of reasons such as differences in age, gender and presence of any underlying health factors. It is therefore not clinically sound to provide the same treatment regime for different people even with the same type of injury/disease and expect the same therapeutic outcome. Providing the correct and required stimulating signal to promote proper growth and differentiation is an inherently unique feature of the type and location of cells and stage of healing of the patient at that particular time of treatment.
The interplay of the aforementioned variabilities have provided a basis for development of the personalized bioelectrotherapeutic approach disclosed herein.
Personalized bioelectrotherapeutic therapy for treating biological tissues should generate bioelectric stimulation with sufficient intensity, format, duration and temporal sequence to be capable of activating a cascade of cellular signaling processes and extracellular signals, initiate enzyme reactions, membrane transport, cell proliferation and differentiation and other biological processes involved in healing and repair without being so strong that the generated currents create undesirable physiological reactions. The electromagnetic field (EMF) should satisfy the frequency, amplitude, and temporal pattern that native and repair cells innately possess, require and expect for proper growth and differentiation during the process of healing.
It has not previously been realized that parameters external to the injury or disease microenvironment related to the generation and transmission of a therapeutic electromagnetic field are tied to, and thus intimately related to, the ability of providing therapeutic bioelectromagnetic stimulation to satisfy requirements of the injury or disease microenvironment targeted for treatment in a given patient. Nor was it previously realized that even subtle differences in one or more of the variabilities involved can render a bioelectromagnetic therapy ineffective between different patients even for the same type of anatomical injury/disease.
Accordingly, the invention provides bioelectromagnetic therapy methods, devices and systems that comprise multiple points of personalization throughout a bioelectromagnetic treatment protocol thus compensating for variabilities associated with the biological challenge, the patient profile, the EMF transmission pathway, and device deployment specifics in order to stimulate a desired outcome.
The complex relationship between the variable biological parameters of the patient and the microenvironment of the treatment area and the variable parameters of the electromagnetic treatment modality prescribed for the patient are computationally defined in order to provide an effective personalized electromagnetic treatment protocol specific for the patient.
Described herein are bioelectromagnetic therapy methods, devices and systems that advantageously incorporate specialized and intelligent physics-based computational engines to provide a more robust, comprehensive, and effective approach to deliver personalized bioelectromagnetic therapy. The proprietary computational engines are configured to employ artificial intelligence, machine learning, computational and mathematical analysis—to organized collections of data representing multidimensional parameters relating to: (a) biology of the patient, and the biology of the patient's microenvironment targeted for treatment, inclusive of clinical metadata pertaining to the biology of similar patient and target microenvironment; and (b) the electromagnetic treatment modality prescribed for the patient that emit electromagnetic fields to influence the target microenvironment, this includes parameters affecting electromagnetic field deployment and electromagnetic field transmission efficiency, in order to generate a personalized treatment for a patient.
The proprietary computational engines are configured to enable determination of an ideal electromagnetic field requirement directed at the microenvironment targeted for treatment of a subject and further determine a personalized electromagnetic field treatment protocol for the subject inclusive of a precise means to deliver the determined ideal electromagnetic field requirement during the personalized treatment protocol.
The personalization of a treatment for a patient as herein described is not based on a historical database comparison and not a general patient-matching treatment model. To the contrary, the personalized treatment protocol as herein described is to be an exact match for the requirements of the patient microenvironment being treated with a prescribed electromagnetic treatment modality in order to more exactly influence healing at cellular and molecular levels and/or act on mediators of inflammation, and/or act on biological factors to provide faster healing of injury, increased quality of healing, reduction in disease progression and/or pain management.
The limits of the bioelectromagnetic field stimulation applied during a personalized treatment protocol is not predetermined, but instead established specifically to match the microenvironment of a target in a patient and thereafter self-adaptively adjusts responsive to changes occurring at the cellular level of the target as a result of the applied electric signal over the course of the treatment protocol.
Embodiments of the invention disclosed herein include in aspects, a Microenvironment Computational Engine (MiCE) configured to use organized indexed collections of data representing multidimensional parameters of the patient and the biology of the patient's microenvironment targeted for treatment (patient-centric data), and clinical metadata pertaining to the biology of similar patients and target microenvironments for calculating a patient-specific and theoretically ideal Personalized Microenvironment Stimulation Target (PMST). The PMST is the calculated ideal electromagnetic field stimulation required for the microenvironment targeted for treatment.
Embodiments of the invention disclosed herein include in aspects a Macrotranslation Computational Engine (MaCE) configured to use organized indexed collections of data representing multidimensional parameters of the prescribed electromagnetic field modality (EMF modality-centric data) to calculate the precise means to deliver the ideal electromagnetic field requirement (i.e., the PMST). The MaCE outputs the initial settings characterizing the EMF source, referred to as the Personalized Treatment Protocol (PTP). EMF modality-centric data represents: (a) transmission pathway data representing the signal pathway separating the microenvironment and EMF source that is influenced by material properties and physical dimensions and movement of tissues and materials along the signal pathway; and (b) deployment specifics data representing the modality of electromagnetic field generation and physical construction of EMF signal generator device as configured to the patient and the injury or disease.
Embodiments of the invention disclosed herein may further comprise optimization extension.
In aspects the optimization extension comprises a Feedback Computational Engine (FCE) configured for dynamic sensing, calculation and adaptive correction of the MaCE.
In aspects the optimization extension comprises a Learning Computational Engine (LCE) configured for dynamic clinical sensing, calculation and adaptive correction of the MiCE.
In aspects the optimization extension comprises both an FCE and an LCE.
Herein described are computer implemented methods, devices and systems comprising MiCE and MaCE and optionally one or both of FCE and LCE that overcome at least one shortcoming of previously described electromagnetic methods and for generation and application of personalized bioelectrical signals optimized to provide an exact stimulus required and unique to the injury or disease microenvironment of the patient resulting in the desired biological response.
A desired biological response for injury or disease may comprise alterations in biological processes at the microenvironment involved in for example but not limited to: stabilizing, reversing and/or improving state of injury or disease; improving/restoring function of injury or tissue/organ affected by disease; decrease spread/growth of disease; stabilize injury or disease; manage/decrease pain associated with injury or disease.
In aspects, the personalized electromagnetic field signals as described herein more efficiently match frequency components to a relevant cellular/molecular process of the injury or disease microenvironment of the patient for which it was calculated.
In aspects, the personalized electromagnetic field signals as described herein correspond more directly to signals of the injury or disease microenvironment of the patient for which it was calculated resulting in accelerated healing.
In aspects the personalized electromagnetic field signals as described herein more precisely target biochemical and biophysical pathways of cells and associated structures in the injury or disease microenvironment encouraging cellular growth, tissue growth, repair, and maintenance.
In aspects, the application of the personalized electromagnetic field signals as described herein may stimulate action of growth factors and other cytokines of the targeted microenvironment.
In aspects, the application of personalized electromagnetic field signals as described herein may modify the genetic regulation of cells within the targeted microenvironment.
In aspects, the personalized electromagnetic field signals as described herein may have decreased effects on off target cells/tissues.
In aspects the personalized electromagnetic field is for application for a time effective for the injury to substantially heal.
In aspects the personalized electromagnetic field is applied for a time effective to reverse, stabilize and/or cure the disease.
In aspects, the personalized electromagnetic field is a pulsed electromagnetic field (PEMF).
In aspects, the personalized electromagnetic field is a capacitively-coupled electric field.
According to an aspect of the invention is device for providing an electromagnetic field (EMF) to an injury or disease in a patient, the device comprising:
In aspects, the device is configured to deliver a personalized electrical stimulation field to preferentially stimulate (up-regulate, down-regulate, or a combination of both) the biochemical cellular and sub-cellular molecular responses to trigger the activation of known mammalian genes responsible for the regeneration, restoration, repair, maintenance, or any combination of cartilage, bone, or both.
In aspects, the device is configured to deliver a personalized electrical stimulation field to preferentially stimulate (up-regulate, down-regulate, or a combination of both) the biochemical cellular and sub-cellular molecular responses unique to the patient microenvironment to trigger the activation of known mammalian genes responsible for pain regulation, pain relief, and/or pain reduction.
In aspects, the device is configured to deliver a personalized electrical stimulation field to preferentially stimulate (up-regulate, down-regulate, or a combination of both) the biochemical cellular and sub-cellular molecular responses unique to the patient microenvironment to trigger the activation of known mammalian genes responsible for slowing down or reversing cancer growth.
In aspects, the device is configured to deliver a personalized electrical stimulation field to preferentially stimulate (up-regulate, down-regulate, or a combination of both) the biochemical cellular and sub-cellular molecular responses to trigger the activation of known mammalian genes unique to the patient microenvironment responsible for general feeling of well being, or reduction in one or more symptoms of anxiety, or reduction in one or more symptoms of stress.
In aspects, the device is configured to deliver a personalized electrical stimulation field to preferentially stimulate (up-regulate, down-regulate, or a combination of both) the biochemical cellular and sub-cellular molecular responses unique to the patient microenvironment to trigger the activation of known mammalian genes responsible for slowing down or reversing or managing a neurological disorder.
In aspects, the EMF signal applicator is configured for inductive coupling with the EMF source(s), e.g. a coil(s), or capacitive coupling using electrode(s) for electrochemical contact with surface of the treatment target.
In aspects the electromagnetic (EMF) signal generator comprises the engine means, processor(s) and memory for generating and delivering the personalized programmed treatment protocol to satisfy the requirements of the personalized microenvironment stimulation target at the injury or disease site of a patient.
In aspects the EMF signal generator may further comprise a display and touch pad or input keys allowing for patient interaction or navigation within the display. In aspects, the EMF may form a kit or part of a kit with instructions. In aspects, the EMF signal generator may be in operable communication with one or more remote operational networks.
In aspects, the device is configured as a wearable device comprising an anatomical wrap, anatomical support (e.g. brace), apparel (e.g. t-shirt, sweat shirt), chest support (e.g. bra), hat/cap/helmet, foot ware (e.g. insoles for sneakers, boots), fashion accessory (e.g. bracelet), dressing, bandage, compression bandage and compression dressing.
In aspects, the device and/or components thereof is configured to be re-useable.
In aspects, the device is configured to be re-programmable.
In aspects, the device and/or components thereof are configured to be disposable, recyclable and/or replaceable.
In aspects, the device and/or components thereof are configured to be implantable in a patient.
In aspects the device and/or components thereof is configured to be integrated into a mattress, mattress pad, linen (sheets, pillowcases), furniture (e.g. bed, chair, sofa), exercise equipment, or support device (e.g. wheelchair) onto which the subject may sit, recline, etc.
According to an aspect of the invention is a method personalized for treatment of an injury or disease in a patient, the method comprising:
In aspects, the personalized electromagnetic field is generated incorporating biological data parameters of the injury or disease of the patient.
In aspects, the personalized electromagnetic field is generated incorporating biological data parameters of the patient relevant to the injury or disease.
In aspects, the personalized electromagnetic field is generated incorporating clinical metadata relevant to the injury or disease.
In aspects, the personalized electromagnetic field is generated incorporating clinical metadata relevant to the injury or disease.
According to an aspect of the invention is an electromagnetic field (EMF) treatment system personalized for a patient comprising:
In aspects, the Microenvironment Computational Engine (MiCE) comprises protocols to integrate and process parameter data based on the patient, the biology of the patient's microenvironment, and clinical metadata pertaining to the biology of similar target microenvironment.
In aspects, the Macrotranslation Computational Engine (MaCE) comprises protocols to integrate and process parameter data based on the EMF treatment modality and patient factors external to the microenvironment to deliver the ideal personalized electromagnetic field to the microenvironment of the patient.
According to an aspect of the invention is a wearable electromagnetic field (EMF) therapy system for treating an injury or disease in a patient, the system comprising:
According to an aspect of the invention is a computer implemented electromagnetic field (EMF) treatment system comprising:
According to a further aspect is a bioelectromagnetic therapy system comprising:
The system, device and methods described herein are suitable for personalization of treatments for any variety of clinical indications including but not limited to treatment of injury, disease, pain management, physical effects of stress and/or anxiety and for whole body systemic benefit. The system, device and method of the invention may also in aspects be suitable as a preventative strategy for a recurring condition.
The personalized, intelligent self-adaptive bioelectromagnetic therapy of the invention is well tolerated by a patient, need not be invasive or unpleasant, does not cause pain and thus is beneficial for increasing patient treatment compliance. The method does not require manual adjustment of power, pulse rate duration, pulse width duration, or treatment time by the treatment provider. A bioelectromagnetic therapy device programmed and configured to deliver the personalized, intelligent self-adaptive bioelectromagnetic therapy as herein described benefits from convenience of use, versatility and ability for treatment of single or multiple treatment targets on the same patient or alternatively for full body treatment of a patient.
This comprehensive personalized approach improves the efficacy of the bioelectromagnetic treatment resulting in desired and more enduring therapeutic outcomes. The method is also advantageous as it calculates the EMF treatment protocol specific to a treatment target area of a patient and thus substantially avoids possible compromising effects to tissues in close proximity.
From the foregoing, it will be appreciated by those skilled in the art that the present invention provides a particularly effective method, device and system for overcoming many of the limitations associated with the treatment of patients using conventional electromagnetic energy. It will also be readily appreciated by one with ordinary skill in the art that the invention is suitable for treatment of humans and also has veterinary applications.
These and other features, embodiments, and advantages of the present disclosure are mentioned not to limit or define the disclosure, but to provide examples to aid in the understanding thereof when read with the following Description and with reference to the accompanying drawings.
For a more complete understanding of the present disclosure, reference is made to the following description taken in conjunction with the accompanying drawings.
Reference will now be made in detail to embodiments, examples of which are illustrated in the accompanying drawings. In the following detailed description, numerous specific details are set forth in order to provide a sufficient understanding of the subject matter presented herein. But it will be apparent to one of ordinary skill in the art that the subject matter may be practiced without these specific details. Moreover, the particular embodiments described herein are provided by way of example and should not be used to limit the scope of the invention to these particular embodiments. In other instances, well-known data structures, timing protocols, software operations, procedures, and components have not been described in detail so as not to unnecessarily obscure aspects of the embodiments of the invention.
As used herein, the terms “invention” or “present invention” are non-limiting terms and not intended to refer to any single aspect of the particular invention but encompass all possible aspects as described in the specification and the claims.
All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. The publications and applications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present invention is not entitled to antedate such publication by virtue of prior invention. In addition, the materials, methods, and examples are illustrative only and are not intended to be limiting.
In the case of conflict, the present specification, including definitions, will control. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as is commonly understood by one of skill in the art to which the subject matter herein belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and the present disclosure, and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
Reference to “one embodiment,” “an embodiment,” “a preferred embodiment” or any other phrase mentioning the word “embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the-disclosure and also means that any particular feature, structure, or characteristic described in connection with one embodiment can be included in any embodiment or can be omitted or excluded from any embodiment. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Moreover, various features are described which may be exhibited by some embodiments and not by others and may be omitted from any embodiment. Furthermore, any particular feature, structure, or characteristic described herein may be optional. Similarly, various requirements are described which may be requirements for some embodiments but not other embodiments. Where appropriate any of the features discussed herein in relation to one aspect or embodiment of the invention may be applied to another aspect or embodiment of the invention. Similarly, where appropriate any of the features discussed herein in relation to one aspect or embodiment of the invention may be optional with respect to and/or omitted from that aspect or embodiment of the invention or any other aspect or embodiment of the invention discussed or disclosed herein.
It will be understood that any component defined herein as being included in any described embodiment may be explicitly excluded from the claimed invention by way of proviso or negative limitation.
As used herein, the articles “a” and “an” preceding an element or component are intended to be non-restrictive regarding the number of instances (i.e. occurrences) of the element or component. Therefore, “a” or “an” should be read to include one or at least one, and the singular word form of the element or component also includes the plural unless the number is obviously meant to be singular.
It will be further understood that the terms “comprises” and/or “comprising,” or “includes”, “including” and/or “having” and their inflections and conjugates denote when used in this specification, specify the presence of stated features, regions, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, regions, integers, steps, operations, elements, components, and/or groups thereof. Words using the singular or plural number also include the plural or singular number respectively. Additionally, the words “herein,” “hereunder,” “above,” “below,” and words of similar import refer to this application as a whole and not to any particular portions of this application.
As used herein, the term “about” refers to variation in the numerical quantity. In one aspect, the term “about” means within 10% of the reported numerical value. In another aspect, the term “about” means within 5% of the reported numerical value. Yet, in another aspect, the term “about” means within 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1% of the reported numerical value.
“About,” is equivalent to “approximately,” or “substantially” as used herein and inclusive of the stated value and means within an acceptable range of deviation for the particular value as determined by one of ordinary skill in the art, considering the measurement in question and the error associated with measurement of the particular quantity (i.e., the limitations of the measurement system). For example, “about,” “approximately,” or “substantially” can mean within one or more standard deviations, or within +30%, 20%, 10%, 5% of the stated value.
Should a range of values be recited, it is merely for convenience or brevity and includes all the possible sub-ranges as well as individual numerical values within and about the boundary of that range. Any numeric value, unless otherwise specified, includes also practical close values and integral values do not exclude fractional values. Ranges given herein also include the end of the ranges.
As will also be understood by one skilled in the art, all language such as “up to”, “at least”, “greater than”, “less than”, “more than”, “or more”, and the like, include the number recited and such terms refer to ranges that can be subsequently broken down into sub-ranges as discussed above. Accordingly, specific values recited for radicals, substituents, and ranges, are for illustration only; they do not exclude other defined values or other values within defined ranges for radicals and substituents.
As used herein the term ‘may’ denotes an option or an effect which is either or not included and/or used and/or implemented and/or occurs, yet the option constitutes at least a part of some embodiments of the invention or consequence thereof, without limiting the scope of the invention.
The phrase “and/or,” as used herein in the specification and in the claims, should be understood to mean “either or both” of the elements so conjoined, e.g., elements that are conjunctively present in some cases and disjunctively present in other cases. Other elements may optionally be present other than the elements specifically identified by the “and/or” clause, whether related or unrelated to those elements specifically identified unless clearly indicated to the contrary. When the word “or” is used in reference to a list of two or more s, that word covers all of the following interpretations of the word: any of the s in the list, all of the s in the list and any combination of the s in the list.
As used herein, expressions such as “at least one of,” when preceding a list of elements, modify the entire list of elements and do not modify the individual elements of the list.
“Combination or combining” for the purposes of this invention means any method of putting two or more materials together. Such methods include, but are not limited to, mixing, blending, commingling, concocting, homogenizing, incorporating, intermingling, fusing, joining, shuffling, stirring, coalescing, integrating, confounding, joining, uniting, or the like.
The terms “patient,” “subject,” “individual,” and the like are used interchangeably herein.
In certain non-limiting aspects, the patient, subject or individual is a mammal and includes humans.
As used herein “disease” refers to any abnormal condition that negatively affects the structure or function of all or part of a subject, and that is not due to injury. Diseases are medical conditions associated with specific signs and symptoms such as for example pain and dysfunction and includes for example disorders, syndromes, conditions and mental abnormal behaviors.
As used herein “injury” is damage to the body of a human. Injury can include “trauma” as any injury to human tissues and organs caused by an external force from minor (e.g. cuts and bruises) to critical (e.g. major brain or spinal injuries) and may be categorised as blunt or penetrating.
As used herein “bioelectrical signals” are electrical signals that can be measured from biological beings, for example, humans and include endogenous bioelectrical signals that are produced in cells by the cumulative action of ion channels, pumps, and transporters and transduced into second-messenger responses, and alter aspects of cell behavior. In aspects, low amplitude and low frequency electrical signals.
As used herein “bioelectricity” refers to endogenous electrical potentials and currents occurring within or produced by living cells and tissues.
As used herein “electromagnetic field” (EMF) is a form of waves with both electric and magnetic components, the waves characterised by energy, frequency and wavelength. The EMF is the stimulating signal for providing therapy.
As used herein “pulsed electromagnetic field (PEMF)” refers to a time varying (pulsed) electromagnetic field with frequency and intensity.
“Bioelectromagnetic Therapy” refers to treatment of a subject using electromagnetic fields.
“Electromagnetic Field (EMF) Source” refers to the device/apparatus comprising components that generate an electromagnetic field.
“Stimulate” refers to generating a desired response at the cellular level of the biological microenvironment of the treatment target with the application of the personalized EMF treatment protocol. The desired response may change during the course of treatment, for example, an initial increase in cellular growth and differentiation at the biological microenvironment may at first occur followed by either a maintenance period or a period of decrease in the rate of cellular growth and differentiation and/or activation of further cellular events. This is specific to the particular healing process of the biological microenvironment of the particular injury, trauma, disease or condition of the patient.
As used herein “Personalized” refers to treatment specifically generated and customized for an individual patient, and more specifically to the biological microenvironment of the treatment target of the patient.
“Treatment target” refers to the general anatomical area or tissue receiving bioelectromagnetic therapy and is not limited. Any part of the body can be injured or afflicted with disease. The treatment target can also include the “whole body”.
“Microenvironment” refers to the intricate three-dimensional, dynamic network of tissue architecture of the ‘treatment target’ in terms of its composition of cells, extracellular matrix (ECM) components, soluble factors, and physical forces (e.g., fluid flow and mechanical stress). As a result of a particular type of injury or disease the biological microenvironment faces several physiological and/or biochemical challenges in order to begin the complex process of healing and/or complex tissue growth, such as for example but not limited to management of exudate, bacterial control, maceration of cells/tissues, and dead cells/tissues.
As used herein “Personalized Intelligent Self-Adaptive Bioelectromagnetic Therapy” refers to a novel patient-specific and optimized treatment designed specifically for a single patient using computational engines configured to receive specific structured data that generally relates to (a) the microenvironment, this being data regarding the patient and the microenvironment of the treatment target, (b) macrotranslation factors this being data regarding the EMF treatment deployment and logistics of its use relating to the microenvironment (a) Taken together, this allows calculation of a patient-specific and theoretically ideal calculated electromagnetic stimulation requirement for the desired cellular response within the microenvironment for the specific patient.
The structured data relating to the patient and the microenvironment of the treatment target is defined as:
Table 1 lists non-exhaustive, non-limiting examples of data that is collected for a patient to undergo personalized bioelectromagnetic therapy,
Age, Gender, Ethnicity, Height, Weight, BMI
ness/markers.
indicates data missing or illegible when filed
“Personalized Microenvironment Stimulation Target” (PMST) refers to a patient-specific and theoretically ideal calculated electromagnetic stimulation requirement for the desired cellular response within the microenvironment for the specific patient. It may define a specific induced current or magnetic field density, as a non-limiting example, within the biological microenvironment.
“Microenvironment Computational Engine” (MiCE) refers to a physics-based engine for calculating (e.g. generates, determines) the Personalized Microenvironment Stimulation Target (PMST) for the patient based on the biological challenge data, the patient profile data and the clinical metadata which is inclusive of proprietary experimental data.
The structured data relating to the macrotranslational factors, data regarding the EMF treatment deployment and logistics of its use relating to the microenvironment (a) is defined as:
“Macrotranslation Computational Engine” (MaCE) refers to a physics-based engine configured use the PMST and the macrotranslational parameters to calculate/determine the initial output required from the EMF source, i.e., the initial EMF settings that, subject to translational effects along the transmission pathway, meets the required specifications to generate the ‘personalized microenvironment stimulation target’. The output of this engine is the ‘Personalized Treatment Protocol’ (PTP).
“Personalized Treatment Protocol” (PTP) refers to the combination of EMF signal parameters (frequency, intensity, waveform, driving voltage, current delivered to coils/electrodes) that are required to meet the ideal PMST. Additionally, this protocol describes the treatment length, daily exposure times and any temporal variations to the personalized EMF target signal over the course of treatment.
“Feedback Computational Engine” refers to a feedback engine configured for correcting differences, at the biological microenvironment, between the ideal PMST and the actual signal, based on input as measured by one or more EMF sensors at or near the microenvironment during treatment, as a result of inaccuracies in the MaCE or distortion and/or attenuation of the PMST due to changes/perturbations that may occur during the treatment protocol. Corrections are sent as feedback data to modify the MaCE input parameters that are used to calculate the personalized treatment protocol.
“Learning Computational Engine” refers to an optimization engine configured as a self-contained feedback loop, using clinical follow-up data and clinical sensor data (sensing in vivo biological parameters), for optimizing the ‘personalized treatment protocol’ and adaptively correcting any inaccuracies in the ‘microenvironment computational engine’. The learning computational engine can incrementally adjust parameters (including frequency, intensity, waveform, etc.) of the ‘personalized treatment protocol’, monitor and map out their effects, and then select the optimal settings to continue treatment. To improve resolution, the interim and final results of treatment and associated patient information are incorporated into the input parameters of the physics-based computational engines.
Conventional pre-defined or manufacturer-suggested non-specific EMF treatment regimes and frequencies, at any scale, completely lack any form of true clinical personalization that would have the potential to account for not only the application (e.g., disease or injury) but also the patient profile, and hardware specifics for precise EMF deployment and optimization of the treatment protocol over time.
The diverse cellular responses to electromagnetic fields between different patients highlight the therapeutic limitations of predetermined electromagnetic fields proposed as universal patient treatments. The basis of the invention disclosed herein is that the ideal EMF exposure for a specific patient can and should be determined specific to (a) microenvironmental factors included in the biological challenge and patient profile; and (b) macrotranslational factors that describe the transmission pathway and deployment specifics of device implementation. Further, during treatment, the therapy can “learn” by deliberately making small changes to the initial ideal EMF exposure to find a true, optimized solution. Real-time and intermittent sensing is inherently required for “learning” and consistent application of the treatment and will dynamically account for sensed distortion or attenuation of the ideal EMF.
The present invention provides a bioelectromagnetic treatment method for delivering personalized, effective bioelectromagnetic therapy to a microenvironment injury/disease site of a patient undergoing the therapy. The bioelectromagnetic treatment method is self-adaptive and bio-responsive to the microenvironment undergoing treatment and to the device administering therapy. No single electromagnetic field specification will work effectively for everyone. Novel computer-implemented computational engines process parameters defining a patient and injury to compute an ideal personalized electromagnetic field. The microenvironment computational engine calculates a personalized stimulation target using patient-specific factors and the macrotranslation computational engine incorporates external macro parameters related to device deployment to create an effective personalized EMF treatment protocol to achieve the calculated stimulation target.
The methods, device and system described herein minimizes undesired effects of electromagnetic fields on adjacent/non-target cells/tissue as electromagnetic field dispersion to adjacent tissues is minimized. The prescribed treatment modality in conjunction with the personalized treatment protocol maintains electromagnetic field concentration at the center of the microenvironment being treated.
In embodiments disclosed herein are methods, devices and systems for providing treatment of injury or disease in a patient by the application of personalized bioelectromagnetic therapy, including:
The computer implemented platform in conjunction with an EMF device provides personalized, intelligent, optimized and self-adaptive bioelectromagnetic therapy developed for the treatment of any injury and/or disease in a patient resulting in a better outcome for the patient.
Patient-based biophysical/biological ‘microenvironment parameters’ and EMF source deployment and transmission ‘macrotranslation parameters’ need to be accommodated on a personalized basis in the effective and successful operation of the bioelectromagnetic therapy. These patient-specific factors ultimately affect how an EMF elicits the required biological response at the microenvironment of the injury or disease of the patient.
Mathematical computation using the microenvironment computational engine described herein provides a means to calculate a patient-specific and theoretically ideal electromagnetic stimulation, i.e. PMST, for the microenvironment in need of treatment. The MaCE described herein computes the PTP that configures the initial settings of the EMF source to generate the PMST for the patient's microenvironment.
MaCE is configured to create a PTP based on the device deployment specifics and the transmission pathway. Following the PTP, the EMF source delivers an appropriate signal to generate the unique PMST. When calculating the personalized treatment protocol, accounting for and adapting to microenvironment and macrotranslation parameters unique to the individual enhances bio-effective processes involved in repair of injury and/or lessens and/or reverses progression of disease in a patient.
The personalized bioelectromagnetic therapy may additionally comprise an optional optimization extension that adaptively corrects/adjusts the treatment protocol in substantively real time to further optimize the personalized treatment protocol. The optimization extension includes two stages that follow after the calculation and delivery of the personalized treatment protocol and are designed to correct inaccuracies in the MiCE and MaCE configuration of outputs using a series of sensors. Optimization extension can be continuous or intermittent.
Optimization extension comprises two stages: (a) a feedback computational engine configured to acquire input data from EMF sensors at or near the microenvironment undergoing treatment and to determine and correct for differences between the target EMF defined by the MaCE and actual measured EMF, as a result of any inaccuracies in the MaCE and/or as a result of rotational movement and/or impact forces on the EMF modality; and (b) a learning computational engine configured to use the following inputs to operate a self-contained optimization loop: clinical sensor data obtained via one or more clinical sensors at or near the microenvironment, clinical follow-up input data and the adjusted treatment protocol.
The learning computational engine is configured for adjustment in small incremental changes to EMF source initial settings (e.g., increase or decrease the frequency by 10%) and for monitoring their effects using sensors. After mapping out the causal relationships, an optimized personalized treatment protocol is determined for continued treatment. The interim and final results of treatment and associated patient data and microenvironment data based on the personalized treatment protocol are relayed back into the MiCE. More specifically, real-time interim result data are fed back and integrated into one of the databases accessed by the microenvironment computational engine to improve the personalized microenvironment stimulation target for the current patient. The real-time inerim result data is cumulative during the treatment protocol such that there is successive addition to the patient data database.
The final result data are used to update the organized collection of clinical metadata to improve the determination of an effective microenvironment stimulation target for future patients.
The ability to logically and mathematically determine a personalized microenvironment stimulation target customized specifically to a target microenvironment of a patient is unique. Further, the ability to logically and mathematically integrate the personalized microenvironment stimulation target into the macrotranslation computational engine calculations to create a personalized treatment protocol is unique. The generation of an external EMF whose parameters, including waveform, frequency, amplitude, etc., are determined based on causal relationships between the EMF-derived stimulation and cellular responses, the specific attributes of the patient's injury, the specific attributes of the local microenvironment that are dependent on intrinsic patient characteristics, such as metabolic activity and limitations thereof, the transmission pathway between the EMF source and the microenvironment, and the specific configuration and operation of the EMF source induces the theoretically perfect electromagnetic field encompassing the cellular architecture of the microenvironment. This represents true customization of a bioelectromagnetic therapy for a specific patient with a specific biological challenge leading to an improved treatment outcome that is clinically effective and enduring.
In general, the EMF signal generator (20) is powered to output an electrical current with a defined waveform that flows into the coils or electrodes, creating the EMF. The device may transmit the personalized EMF signals as described herein via inductive coupling with a coil applicator or via capacitive coupling where the EMF applicators are electrodes in electrochemical contact with the conductive surface of the target for treatment.
A coil applicator comprises wire coils as loops of flexible wire. As part of a wearable bioelectromagnetic treatment device, in aspects, the coils are flexible/pliable and lightweight. As understood by one of skill in the art, the EMF source(s) may comprise a plurality or multiple coils/electrodes to deliver the personalized electromagnetic field to the target microenvironment. A multi-coil applicator may be made from a metal containing material such as a metal wire (e.g., copper) and coils of the applicator may be interconnected. One of skill in the art would understand that any desired number of coils or electrodes of various sizes and shapes can be incorporated depending on the mode of prescribed EMF treatment.
Sensors may be incorporated externally and/or implanted at the tissue level. It is understood by one skilled in the art that the number and type of sensor (EMF and/or) clinical may vary as can the positioning of these sensors with respect to the microenvironment targeted for treatment.
EMF sensors provide dynamic sensing of parameters at the microenvironment that may cause a deviation from the PMST. EMF sensors can comprise one or more of gaussmeters, magnetometer, spatial location sensors, force sensors, pressure sensors, shape sensing sensors, reversible and irreversible strain sensors and impedance sensors.
Clinical sensors provide dynamic sensing of biochemical parameters at the microenvironment and can comprise one or more of pH sensor, ion concentration sensor, glucose sensor, oxygen sensor, and temperature sensor, etc.
Safety sensors may be provided to alert the patient and the medical practitioner of any malfunction. These safety sensors operate to immediately shut down the device.
In embodiments, the system may be configured to limit the degree of adjustment to the treatment protocol by a patient in order not to manually expand the treatment protocol unless authorized by a clinical caretaker. In embodiments a patient may be able to self-direct changes to the therapy, but only for example between sessions or within an on-going session within predetermined limits programmed by the physician and/or device manufacturer. This prevents patient selection of a harmful treatment protocol operation.
Such limits or treatment governor functions may advantageously protect the patient from radically altering the therapy in an uncontrolled way that is very different from recent, familiar operating points. This may advantageously protect the patient from receiving an erratic course of therapies that may reduce the therapeutic value of the feedback on patient outcomes.
In embodiments the system is configured to govern the maximum increment of any parameter changes at the microenvironment.
In some embodiments, the system may send an electronic message or alert (for example email, text, call to a physician upon an attempt by a patient to expand the treatment protocol beyond that initialized in the system.
The device may comprise a housing with LCD or LED display to display information to the patient and may be a touch screen display. The housing may comprise a keypad for controls, and jack(s)/socket(s) for receiving the wire(s) (lead/harness) for connection to the EMF applicator or electrodes.
In some embodiments, the device and/or components thereof can be miniaturized for different configurations required in different treatment modalities.
The device may include one or more controllers/processors each including a central processing unit for processing data and computer-readable instructions and memory. The device may be configured to apply the personalized programmed treatment protocol. The steps of a method or a treatment protocol described in connection with the embodiments disclosed herein may be embodied directly in hardware, or in a software module executed by a processor. The memory may include volatile random-access memory (RAM), non-volatile read only memory (ROM), non-volatile magneto-resistive (MRAM) and/or other types of memory. The device may also include a data storage component for storing data and controller/processor-executable instructions. The data storage component may include one or more non-volatile storage types such as magnetic storage, optical storage, solid-state storage, etc. The device may also be connected to removable or external non-volatile memory and/or storage (such as a removable memory card, memory key drive, networked storage, etc.) through input/output device interface.
The device may be connected over any type of communication network implemented using wired infrastructure (e.g., cable, CATS, fiber optic cable, etc.), a wireless infrastructure (e.g., WiFi, RF, cellular, microwave, satellite, Bluetooth, etc.), and/or other connection technology. The device may connect to the network of the healthcare practitioner through either wired or wireless connections and further may include a local or private network and/or the internet. For example, the device may be connected to a network through a wireless service provider, over a WiFi connection or a cellular network connection. Network-connected support devices, such as a laptop computer, desktop computer, and a server may connect to the network through a wired or wireless connection.
Aspects of the system and disclosed herein may be implemented as a computer implemented method or as a device or a non-transitory computer readable storage medium (e.g. diskette, CD-ROM, ROM, or fixed disk) or interface device (via a medium to a network). The computer readable storage medium may be readable by a computer and may comprise computer executable instructions for causing a computer or other device to perform methods described in the present disclosure.
Some of the instructions that are executed during the execution of the method of the invention are described with reference to the operational flowcharts. Those skilled in the art will appreciate that the function, operation, determination, etc. of all or part of each step or combination of steps in the flowchart or block diagram may be implemented as computer program instructions, software, hardware, firmware, or combinations thereof. In addition, although the present invention may be embodied in software such as program code, the functions necessary to carry out the present invention are, optionally or alternatively, partially or wholly combined with combinational logic, firmware and or hardware components, such as application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other hardware, or some combination of hardware, software and/or firmware components.
Implementation of embodiments of the disclosed embodiments based on the flow charts and associated text description sufficiently sets forth the invention thus particular sets of program code instructions is not considered necessary for an adequate understanding of how to make and use embodiments.
The methods and systems described herein provide several computer advantages. The method efficiently and rapidly produces/transmits/retains personalized patient-based microenvironment target signals. The personalized treatment protocol and optional optimization extension can be accomplished in near real time.
A signal generator (20) of a device is shown operationally connected to EMF applicators (24) configured and positioned surrounding the target microenvironment (M). EMF sensors(S) installed externally or implanted at the tissue level can monitor the EMF induced at or near the microenvironment. The sensor data is fed into a feedback computational engine to continually compensate for any inaccuracies of the Macrotranslation Computational Engine, which defines EMF source output. Sensing of biological and functional progress may be done continuously or periodically and includes: biosensor dynamic sensing of biochemical parameters at the microenvironment, patient self-assessment (e.g. pain levels) and compliance, and one or more steps of clinical follow-up. The biological sensing data is used to determine if the biological response is achieved, as dictated by the Personalized Microenvironment Stimulation Target and is further incorporated to the proprietary clinical metadata.
Under control of the signal generator (20), the EMF applicators (24) are positioned to induce a focused field (F) that encompasses the microenvironment (M) to stimulate a biological response on at the cellular level (C). Such arrangement is to ensure the entire microenvironment is exposed to the electromagnetic field and cells within may experience the same magnetic forces and/or induced electric currents. With respect to a bone injury such as a fracture, exposure may enhance osteoblastic differentiation and promote bone healing. Additionally, EMF stimulation of a cancerous tumor can selectively accelerate apoptosis in cancer cells. At the cellular level an applied electromagnetic field disturbs the cellular membrane, for example forming lipidic nanopores for passage of ions, and may activate many intracellular pathways and physiological pathways. The mechanical action on both the intracellular and plasma_membrane levels, includes ion channels, receptors, cytokines, enzymes, and peripheral inflammatory pain modulators (Ross C L, et al., Altern Ther Health Med. 2016; 22:52-64). Cell behaviour in response to an induced EMF may be affected by a multitude of patient-specific factors (x, y, z).
The signal used to generate the field (F) is a function of: the microenvironment (M), both its physical location and the cellular (C) behaviour; the surrounding tissue (T); and external media (Ex) it may have to interact with. The tissue (T) level includes the electrical properties of the various tissues around the injury site, such as conductivity. External factors (Ex) encompass everything outside of the body, such as for example the device configuration (e.g., a hard support device such as a cast) and the configuration of the delivery system (e.g., size of coil and number of windings, number of coils), or simply an air gap.
The representation will be unique to the injury or disease of a patient due to the variability of the interconnected factors present at the microenvironment.
A patient presents with an injury or disease [1] is diagnosed and subsequently recommended by a healthcare practitioner for Bioelectromagnetic Therapy (subject to relevant counterindications) [2]. The commercial implementation of Bioelectromagnetic Therapy is divided into components relating to the Microenvironment, which describes the factors influencing the injury/disease microenvironment, and Macrotranslation that includes details pertaining to the macroenvironment surrounding the microenvironment, and the electromagnetic field-producing device itself.
Prior to application of a therapy, the location of the injury or diseased tissue target volume and the relative locations and types of normal tissues are determined by diagnostic imaging and other medical techniques as would be understood by one of skill in the art. Using this information, and, optionally methods similar to those employed in radiation therapy planning, external (fiducial) marks can be placed on the patient surface as an anatomical marker to provide a reference coordinate system for targeting the injury or diseased tissue target volume within the body. Additionally, physical assessments and an analysis of the patient's historical medical circumstance are performed [3] to generate the following organized collection of data, which will be used to inform physics-based computational engines:
All of the patient-specific information data is fed into a series of physics-based computational engines capable of calculating an effective treatment plan and optimizing such plan in relationship to the patient and the specific microenvironment of the patient being treated.
First, the ‘Microenvironment Computational Engine’ utilizes physics-based algorithms in combination with the patient-specific Biological Challenge and Patient Profile to compute a theoretically ideal ‘Personalized Microenvironment Stimulation Target’ [4]. The microenvironment computational engine also incorporates data from a database of clinical metadata and proprietary experimental data that is continually updated as treatments are optimized and concluded [4a]. These additional parameters aid in calculating an initial Personalized Microenvironment Stimulation Target by considering data from similar patients, similar injury and/or similar disease.
The Personalized Microenvironment Stimulation Target is sent to the ‘Macrotranslation Computational Engine’ [5] where macro parameters, such as location and size of the injury/disease and device, and the ‘daisy chain’ of material properties separating the device and the microenvironment [5a], are used to compute a ‘Personalized Treatment Protocol’. The Personalized Treatment Protocol describes the initial settings (i.e., frequency, intensity and waveform of the signal sent to the active EMF-generating elements) required to achieve the Personalized Microenvironment Stimulation Target at the microenvironment. Additionally, the Treatment Protocol includes the daily exposure and expected treatment length.
The patient receives the Personalized Treatment Protocol [6a] based on patient compliance with recommended therapy and thereby the patient microenvironment ideally receives electromagnetic stimulation that is exactly the Personalized Microenvironment Stimulation Target [6b].
Optionally, the treatment comprises an Optimization Extension comprising two further computational engines that obtain information from a series of sensors at the micro and macro levels to provide feedback (dashed connector lines) to optimize the Microenvironment Computational Engine and the Macrotranslation Computational Engine.
The first optional optimization engine is a ‘Feedback Computational Engine’ [7] that takes input from EMF sensors [7a] at or near the microenvironment to determine and correct for differences between the Microenvironment Stimulation Target and the actual measured EMF, as a result of inaccuracies in the Macrotranslation Computational Engine. Any corrections are sent as feedback to the parameters influencing the calculation of the Personalized Treatment Protocol.
Throughout treatment, progress data is collected via clinical follow-up [8a] and clinical sensors [8b], including any updated clinical assessments including for example radiographic or functional assessments, biomarker assays, real-time biosensors, compliance metrics, or input directly from the patient (e.g., pain scores and/or compliance scores on a visual analogue scale).
The ‘Learn Computational Engine’ [9] provides a final round of optimization during the active treatment, via a self-contained feedback loop, using inputs from follow-up and/or sensor data. The Treatment Protocol is optimized to compensate for inaccuracies in the Microenvironment Computational Engine through the following sequence:
Interim and final results of the Bioelectromagnetic Therapy, including all associated patient information, are fed back into the system to improve treatment for both the current patient and future patients, respectively [10]. Interim results [10a] are fed back into the Microenvironment Computational Engine to improve the current Stimulation Target. The final results [10b] are used to update the collection of clinical metadata used to calculate a personalized microenvironment stimulation target for future patients.
These embodiments are provided for purposes of illustration only and are not intended to be limiting unless otherwise specified. Thus, the invention should in no way be construed as being limited by the following studies, but rather, should be construed to encompass any and all variations which become evident as a result of the teaching provided herein.
The prescribed PEMF device configuration is shown in
Example 1 presents experimental data demonstrating variability in the response of cells from a specific donor and between different donors to different EMF stimulation. This supports the need for the described personalized bioelectricity treatment protocol for treatment of bone as shown with non-union fracture healing.
The reference numerals below refer to the numbered sequence elements in
The prescribed capacitive-coupled EMF device configuration is shown in
Experimental data presented in Example 2 demonstrates that EMF therapy inhibit cell growth of breast cancer cells and also enhances chemotherapeutic effects. This confirms the need for the described personalized bioelectricity treatment protocol related to cancer therapy.
The prescribed PEMF device configuration is shown in
Experimental data shown in Example 3 demonstrates inter-donor and intra-donor variability in pain-related gene expression in human astrocytes associated with different EMF stimulation profiles. This confirms the need for the described personalized bioelectricity treatment protocol for to pain management.
The personalized bioelectromagnetic therapy method, device and system described herein are suitable for non-invasive or invasive treatment of injury or disease and advantageously does not possess negative side effects of pharmacological treatments. It can, however, be used in conjunction with pharmacological treatments. Furthermore, it can be used before other treatments, after completing a different treatment approach or in conjunction with other therapeutic and prophylactic procedures and modalities such as heat, cold, ultrasound, wound dressing, orthopedic fixation devices, and surgical interventions.
Treatment of injury or disease may include but not be limited to cancer, cardiovascular disease, inflammatory disease, autoimmune disease, neurological disease, musculoskeletal pain management, wound repair, bone repair, osteoporosis, tissue repair, rehabilitation of traumatic injuries, sports injuries and surgical rehabilitation. The injury or disease is not limiting.
The method of the invention modulates physiologically relevant pathways of the targeted injury/disease microenvironment, such as general transmembrane potential changes, involved in stabilizing, reversing, healing of injury or disease. Some of the physiological induced changes may include variations in cell membrane, enzymatic activity, cell apoptosis, nerve conduction, collagen synthesis, vasodilation, vasoconstriction, viscosity of body fluids/blood, pain signaling, production of endorphins, tissue metabolism, inflammation, supply of oxygen & nutrients, tissue/muscle repair or healing, fibroblast activity, collagen fibril density, protein synthesis, and tissue regeneration.
The method of the invention also provides an improved means to enhance blood flow and biochemical activity by action of exogenous factors (for example growth factors and cytokines) to accelerate repair of cells, organs and tissues, and modulate angiogenesis and neovascularization.
The method of the invention may modulate activity of a variety of biochemical molecules/markers involved to promote healing of an injury or disease. Representative non-limiting examples include cytokines, growth factors, tumor markers, inflammatory markers, endocrine markers and metabolic markers.
Exemplary growth factors may include EGF ligands, EGF, TGFα, EGFR/ErbB receptor family, FGF family, IGF family, IGF-binding protein (IGFBP) family, receptor tyrosine kinases, proteoglycans, TGFβ super family and VEGF/PDGF family.
Exemplary inflammatory markers may include ICAM-1, RANTES, MIP-2, MIP-1β, MIP-1α, MMP-3, adhesion molecules, vitronectin, fibronectin, collagen, laminin, ICAM-1, ICAM-3, BL-CAM, LFA-2, VCAM-1, NCAM, PECAM, cytokines such as the IFN family, chemokines, tumor necrosis factor (TNF), TNF superfamily receptors and modulators, TGFβ, superfamily ligands BMP (bone morphogenetic protein), EGF ligands, fibrinogen, glial markers, (MHC) glycoproteins, microglial markers, α2 macroglobulin receptor, fibroblast growth factor, angiogenic factor-1, MIF, blood vessels Nascent factor-2, CD14, β-defensin 2, MMP-2, nitric oxide, endothelin-1, and VEGF.
Exemplary cytokines may include FGF basic, G-CSF, GCP-2, granulocyte macrophage colony stimulating factor GM-CSF (GM-CSF), growth-related oncogene-keratinocytes (GRO-KC), HGF, ICAM-1, IFN-α, IFN-γ, interleukins, interferon-inducible proteins, MCP-1, macrophage inflammatory proteins, tumor necrosis factor family, VCAM-1, and VEGF.
Exemplary tumor markers may include EGF, TNF-α, PSA, VEGF, TGF-β1, FGFb, TRAIL, and TNF-RI (p55).
Exemplary markers of endocrine function may include 17β-estradiol (E2), DHEA, ACTH, gastrin, and growth hormone (hGH).
Exemplary markers of autoimmune function may include GM-CSF, C-reactive protein, and G-CSF.
Exemplary cardiovascular markers may include cardiac troponin I, cardiac troponin T, brain natriuretic peptide, NT-proBNP, C-reactive protein HS, and β thromboglobulin.
Exemplary metabolic markers may include Bio-intact PTH (1-84) and PTH.
In certain embodiments, personalized bioelectromagnetic target signals may have an effect in vivo on stem cell homing signals (SDF-1 and PDGF), stem cell differentiation signals, blood vessel growth signals, and organ-specific tissue building signals.
In certain embodiments, the bioelectromagnetic target signals may have an effect in vivo on blood vessel growth factors, e.g., VEGF, SDF-1, PDGF, HIF 1 α, eNOS, tropoelastin, HGF, and EGF.
In certain embodiments, personalized bioelectromagnetic target signals may have an effect in vivo on for example SDF-1, IGF-1, HGF, EGF, PDGF, eNOS, VEGF, follistatin, Activin A and B, Relaxin, tropoelastin, GDF-10, GDF-11 and Neurogenin-3.
In certain embodiments, personalized bioelectromagnetic target signals may have an effect in vivo on a protein selected from the group consisting of SDF-1, IGF-1, HGF, EGF, PDGF, VEGF, HIF 1 alpha, eNOS, activin A, activin B, IL-6, follistatin, tropoelastin, GDF-10, GDF-11, neurogenin 3, FGF, TGF, TNF alpha, RANKL, OPG, and combinations thereof.
In certain embodiments, personalized bioelectromagnetic target signals may have an effect in vivo on activity of osteoblasts, osteocytes, osteoclasts, fibroblasts, chondrocytes, keratinocytes, endothelial cells, epithelial cells, mature macrophages and granulocytes.
In certain embodiments, personalized bioelectromagnetic target signals may have an effect in vivo to stimulate multipotent adult stem cells (mesenchymal stem cells or bone marrow stem cells) to promote proliferation and differentiation of the multipotent adult stem cells into specific pathways such as bone, connective tissues, fat etc.
In certain embodiments, the bioelectromagnetic methods according to the present disclosure may be applied for treatment of osteoarthritis and associated pain and/or inflammation in peripheral structures, such as an inflamed knee joint. Neurochemical and metabolic changes in the area of the inflamed knee joint results in chronic pain.
In certain embodiments, the bioelectromagnetic methods according to the present disclosure may be applied for treatment of injured or diseased bone for promoting the growth and repair of bone tissue in vivo. The bone micro-environment is composed of intercellular calcified material, osteoblasts, osteocytes and osteoclasts while the extracellular matrix comprises an organic component of collagens, proteoglycans, hyaluronan and other proteins, phospholipids and growth factors. The mineralized inorganic component is predominantly crystallized calcium and phosphorus in the form of hydroxyapatite. The method described herein has an effect in vivo to release BMP-2, BMP-7, for proliferation and differentiation of osteoblasts to increase the number of osteoblasts for mineralization, to enhance the mineralization step and ossification of new bone tissue, to modulate the activity of calcium/calmodulin-mediated actions as well as G protein coupled receptors and mechanoreceptors, and increase bone density. This enhances the generation of sufficient tissue for proper tissue healing in vivo.
The bioelectromagnetic therapy described herein is suitable for accelerating healing of bone fractures including, but not limited to accidental occurrences or deliberate surgical intervention, to promote fusion of vertebrae after spinal fusion surgery and treat osteopenia and osteonecrosis.
More specifically, bone fractures are categorized as simple and compound fractures and further subdivided as: simple fracture (closed fractures) that occur when a bone suffers breakage but does not pierce through the epidermis; compound fracture, opposite to simple fracture and is also known as an open fracture involving luxation of the bone that pierces through the epidermis and thus susceptible to infection; oblique fracture where the fissure runs diagonal to the axis of the bone; transverse fracture that is perpendicular to the axis of the bone; spiral fracture involving a fracture line that twists around the bone; comminuted fracture where the bone will be broken into several fragments; liner Fracture where the break is parallel to the long axis of the bone; greenstick fracture, partial fracture with one side of the bone unharmed; impacted fracture where the bone splits into two fragments; Complete and Incomplete Fractures; Compression Fracture where at least two bones are forced against one another; Avulsion Fracture, a closed fracture that occurs when the bone breaks due to a forceful contraction of a muscle; Stress Fracture (hairline fracture) due to overuse; Displaced Fracture where the bone breaks into two parts in a way that the bone loses its alignment; Non-Displaced Fracture where the bone snaps into two pieces but stays aligned; Fatigue Fracture where the bone becomes traumatized because of mundane stressors which cause weakness over a period of time; and Pathological Fracture as a result of an underlying health condition, such as osteoporosis or if cancer cells spread to the bones.
In aspects, the method has use to accelerate the healing of damaged or torn cartilage associated with injured bone
In aspects, the method has use for the treatment of bone diseases such as but not limited to osteoporosis, metabolic bone disease, bone cancer, and scoliosis.
In aspects, the method has use for the treatment of joint diseases such as but not limited to osteoarthritis, rheumatoid arthritis, spondyloarthritis, juvenile idiopathic arthritis, lupus, gout, and bursitis.
In certain embodiments, the bioelectromagnetic methods according to the present disclosure may be applied for treatment of cancer in conjunction with surgery, radiation therapy and chemotherapy. Examples of cancer include, but are not limited to, breast cancer, skin cancer, bone cancer, prostate cancer, liver cancer, lung cancer, brain tumor (glioma), head and neck cancers, colon cancer, osteosarcoma, small cell lung tumor, smooth muscle tumor, osteosarcoma and other sarcomas.
In the embodiment of a brain tumor (e.g., glioma) the personalized bioelectromagnetic method herein described may help reduce uncontrolled cell division and, after cancer tumor eradication, help to regenerate tissue/organs to health and function which includes for example stem cell homing, controlled proliferation, differentiation and blood vessel sprouting, growth and maturation expression proteins.
In certain embodiments, the personalized bioelectromagnetic methods according to the present disclosure may be applied for treatment of a pain-related disorder and the therapeutic response includes a reduction or elimination of pain experienced by the patient. Examples of pain-related disorders include, for example, pain response elicited during tissue injury (e.g., inflammation, infection, and ischemia), and pain associated with musculoskeletal disorders (e.g., joint pain such as that associated with arthritis, toothache, and headaches).
In some implementations, the personalized bioelectromagnetic methods according to the present disclosure may be applied for the reduction or elimination of pain associated with an injury or disease and may include but not be limited to adhesive capsulitis, tennis elbow, osteoarthritis, back pain, multiple sclerosis, tendon inflammation, and carpal tunnel syndrome.
In some implementations, the personalized bioelectromagnetic methods according to the present disclosure may be applied for the treatment of a patient with a bone, joint, soft-tissue, or connective tissue disorder and the method reduces or eliminates inflammation in a bone, joint, soft-tissue, or connective tissue of the patient and thus leads to a reduction or elimination of pain associated with the disorder.
In some implementations, the personalized bioelectromagnetic methods according to the present disclosure may be applied for the treatment of a dental condition, and the therapeutic response includes a reduction or elimination of pain associated with the dental condition.
In some implementations, the personalized bioelectromagnetic methods according to the present disclosure may be applied for the treatment of a patient with post-traumatic and post-operative pain and edema in soft tissues, wound healing, burn treatment, and nerve regeneration. In aspects this is by reducing inflammatory responses associated with the painful conditions. The personalized bioelectromagnetic therapy described herein may enhance the production of nitric oxide via modulation of Calcium (“Ca2+”) binding to calmodulin (“CaM”). This in turn can inhibit inflammatory leukotrienes that reduce the inflammatory process.
An electromagnetic field device is used to provide the personalized self-adaptive bioresponsive bioelectromagnetic therapy as herein described and comprises components for generating a personalized microenvironment stimulation target and executing a personalized treatment protocol for a patient. The device can be configured in a variety of manners depending on the injury or disease and as prescribed by a healthcare practitioner for a patient. In any configuration, the device is programmable to execute the personalized microenvironment stimulation target and transmit the personalized treatment protocol for a patient. One or more processor(s)/control module(s), integral and/or external to the device, are configured to receive the operating signals for the device via the healthcare provider's electronic computing device (e.g., smartphone, laptop, tablet, etc.). In one non-limiting example a Bluetooth chip can be provided in the device and in a transceiver unit of the wearable device, and is thus able to transmit treatment and sensor data from the device to the electronic computing device, and/or operating commands from the electronic computing device to the EMF device. Data can be wirelessly transmitted from the computer implemented platform as described herein to a cloud storage, and vice versa. Some or all of the components of a therapeutic electromagnetic field delivery device may be integrated into a control circuit chip to miniaturize the device for various deployment configurations. Timing circuitry can be provided in the device or remote microcontroller, the timing circuitry configured to automatically repeat delivery of the electromagnetic waves and periods of off-time.
In an embodiment, conductive contact of the device with the anatomical area is not required to induce the electrical current in the tissue. As a non-invasive device a patient may be more psychologically prepared to experience and comply with a method incorporating its use resulting in a better outcome. Further, non-invasive methods may avoid possible negative effects to biological tissues, are generally painless and may be performed without any of the risks involved with surgery and without the need for local anesthesia. Less training may be required for use of non-invasive procedures by medical professionals utilizing the device described herein and thus suitable for use by the patient or family members at home or by first responders at home or at a workplace.
In a further embodiment, the device is configured to securably place the conductive coils directly adjacent the area targeted for treatment.
Still in further embodiments, for some applications the device or components thereof can be configured for implantation in the patient.
The device can be stationary (i.e., fixed), portable, disposable, and/or implantable. The device can be configured as a stand-alone device of any size to be used for example at home, at a clinic, hospital, treatment center and/or outdoors. The device may be suitable for prolonged or intermittent use. In some implementations the device may be placed directly over/juxtaposed with/substantially adjacent an anatomical area of a patient to provide bioelectromagnetic therapy to the injury or disease microenvironment located at that area.
A stationary configuration may include for example, but not be limited to, incorporation with furniture (e.g., bed) with respect to a mattress providing full body bioelectromagnetic treatment of a patient during periods of rest and/or sleep. The mattress may include a plurality of interconnected current carrying coils arranged in a desired pattern and operationally connected to the EMF source. Other configurations may include integration with a mattress pad, cushion, sheet, pillow, blanket, wheelchair, chair, body support for a car, exercise device and with other therapeutic and health maintenance devices as understood by one of skill in the art.
Alternatively, the device may be configured as a wearable device providing ergonomic fit to a specific anatomical area of the patient's body (e.g., head, neck, chest, shoulders, knee, foot, ankle, back, wrist, and elbow) that has an injury or disease for application of the personalized treatment protocol to a target microenvironment. A wearable device may be unisex, configured to be of any shape and size to fit any patient, lightweight, hands-free (once positioned on the patient's body) and portable due to incorporating, attaching or embedding a bioelectromagnetic EMF circuit comprising in aspects: a rechargeable and replaceable battery (alternatively, wireless operation configuration); a central processing unit; a wireless transceiver; optional display for input or for monitoring status; a power switch; one or more sensors and one or more coils. As a wearable device, the components may be miniaturized as required.
A wearable device may include but not be limited to an anatomical wrap, anatomical support, apparel, chest support (e.g., bra), hat/cap/helmet, foot ware (e.g., sneakers, boots), fashion accessory (e.g., bracelet), dressing, bandage, compression bandage and compression dressing. In an embodiment of an anatomical wrap device, such a device is shaped for encircling the particular area of the patient's body requiring treatment, such as for example an arm, leg, head, neck or hand.
A wearable wrap device comprises a means for fastening securely to the anatomical site, e.g., treatment target of the patient's body, with for example reversible fasteners such as Velcro™-like straps, hooks, snaps, combinations thereof and the like.
A wearable device may be manufactured to comprise a variety of materials that may be soft, flexible, provide stretch, body-compatible, natural or synthetic, for example, cotton, wool, polyester, rayon, Gore-Tex®, rubber, neoprene, resin or other fibers or materials known to a person skilled in the art as non-irritating and in aspects breathable (i.e., for a garment). The material may be a smart material that can sense the environment and respond to changes in strain, temperature, moisture, and pH. The material may be selected depending on the treatment target area, for example a snug fit may be desired for a wrap placed around the patient treatment target. Configurations of a wearable device may provide some structural support and may also function as an orthopedic support brace. A wearable device can be layered. A flexible plastic that can be molded about a body part is also suitable for use. Alternatively, the device can be configured within a non-flexible material such as a plaster cast. The wrap device may also include other semi-stiff components such as, for example, bendable plastic found in orthopedic applications.
A wearable device as herein described is prescribed for a patient in a personalized configuration such that once in place on the patient juxtaposed at the treatment target, the coils or electrodes are strategically positioned to effectively provide the personalized treatment protocol.
It is understood by one of skill in the art that a wearable device as herein described can be provided as a kit comprising: a bioelectromagnetic EMF circuit comprising in aspects, a rechargeable and replaceable battery (alternatively, wireless operation configuration), a central processing unit, a wireless transceiver, optional display for input or for monitoring status, a power switch, one or more sensors and one or more coils; an anatomical wrap or support, apparel, chest support (e.g., bra), hat/cap/helmet, foot ware (e.g., insoles for a pair of sneakers, boots), fashion accessory (e.g., bracelet), dressing, bandage, compression bandage and compression dressing; and instructions for use.
The inventions described herein may be implemented as a system, it is understood that such systems may include and/or involve a variety of general-purpose computer components such as but not limited to software modules, general-purpose central processing unit (CPU) and main memory (RAM).
The inventions described herein may be implemented with disparate or different software, hardware and/or firmware components, beyond that set forth above, for example, with general purpose or special purpose computing systems or configurations not limited to: software or other components within or embodied on personal computers, servers or server computing devices such as routing/connectivity components, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, consumer electronic devices, network PCs, other existing computer platforms, distributed computing environments that include one or more of the above systems or devices.
The inventions described herein may in some instances be achieved via or performed by for example logic and/or logic instructions including program modules, executed in association with such components or circuitry. In general, program modules may include routines, programs, objects, components, data structures, etc. that performs particular tasks or implement particular instructions herein. The inventions may also be practiced in the context of distributed software, computer, or circuit settings where circuitry is connected via communication buses, circuitry or links. In distributed settings, control/instructions may occur from both local and remote computer storage media including memory storage devices.
Innovative software, circuitry and components herein may also include and/or utilize one or more type of computer readable media resident on, associable with, or can be accessed by such circuits and/or computing components, for example, computer readable media may comprise computer storage media and communication media. Computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and can accessed by computing component. Communication media may comprise computer readable instructions, data structures, program modules and/or other components. Communication media may include wired media but not transitory media.
Aspects of the method, device and system as described herein with respect to the logic, can be functionality programmed into any of a variety of circuitry, including programmable logic devices (“PLDs”), such as field programmable gate arrays (“FPGAs”), programmable array logic (“PAL”) devices, electrically programmable logic and memory devices and standard cell-based devices, as well as application specific integrated circuits. Other aspects of the method, device and system as described herein can implement memory devices, microcontrollers with memory (such as EEPROM), embedded microprocessors, firmware, software and the like. Aspects may be embodied in microprocessors having software-based circuit emulation, discrete logic (sequential and combinatorial), custom devices, fuzzy (neural) logic, quantum devices, and hybrids of any of the above device types.
Logic and/or functions disclosed herein may be enabled using any number of combinations of hardware, firmware, and/or as data embodied in various machine-readable or computer-readable media, in terms of their behavioral, register transfer, logic component, and/or other characteristics.
The need for the present invention will be further illustrated in the following examples. However, it is to be understood that these examples are for illustrative purposes only and should not be used to limit the scope of the present invention in any manner.
These examples are provided for purposes of illustration only and are not intended to be limiting unless otherwise specified. Thus, the invention should in no way be construed as being limited to the following examples, but rather, should be construed to encompass any and all variations which become evident as a result of the teaching provided herein.
To support the assertion that electromagnetic therapy should be personalized to a specific patient and the biology of the injury/disease to be treated, the effects of EMF stimulation on biological effects at the cellular level between different donors was examined (Examples 1-3).
The results demonstrated that the baseline level of biological activity at the cellular level for different donors was fundamentally different, as would be expected. Furthermore, when the same EMF exposure was delivered to cells from different donors (inter-donor variability) the biological effects at the cellular level were different. Also, when cells from the same donor were exposed to different electromagnetic fields (intra-donor variability), the resulting biological effects were different. Inter- and intra-patient differences support the need for personalization and optimization of treatment for a patient.
EMF stimulation profiles demonstrated differential gene expression in donor mesenchymal stem cells (Example 1). An identical EMF exposure was demonstrated to differentially up-regulate or down-regulate genes for each of five donors. As quantified by gene expression, each donor cell group had a different response. In addition, one donor was subjected to different stimulation profiles but only one (1 mT, 75 Hz pulse administered for 10 minutes per day) produced marked increases in osteogenic and chondrogenic gene expression. This same exposure generated different responses in each of the donors.
EMF exposure profiles also demonstrated intra-donor variability in the breast cancer cell line MDA-MB-231 with respect to cell growth and gene expression involving genes belonging to apoptosis, cellular senescence and angiogenesis pathways (Example 2). EMF was demonstrated to enhance the effect of the cisplatin (a chemotherapeutic agent) supporting the use of the personalized bioelectromagnetic therapy described herein as an adjunct to traditional chemotherapy. EMF exposure profiles also demonstrated inter- and intra-donor variability with respect to astrocyte cell donors (Example 3) where gene expression levels along inflammation signalling pathways were altered.
The experimental results also support the use of gene expression as a useful tool to monitor and characterize the effects of EMF treatment on the cells of the injury/disease microenvironment and may further provide guidance for identifying the optimal initial treatment protocol, amending the treatment protocol during treatment, or for the use of an adjunct therapy. A baseline gene expression profile can be obtained from patient cells prior to the start of treatment to determine EMF gene targeting effects
This clinical data would be supplemental data to include in the “Patient Profile” as one of the variable biological parameters fed to MiCE to compute a personalized microenvironment stimulation target for the patient. Any appropriate cell type may be extracted/harvested from a patient from for example a blood draw, a mouth swab, or invasively from the microenvironment. Gene expression and control levels can be assessed at different time points throughout the treatment protocol to allow progressive therapy optimization. The selection of genes may be dependent on the cell/tissue type as well as on the type of injury and disease. Non-limiting examples of genes for expression array assessment are listed in Appendix I-III.
The following examples further illustrate the need for and the implementation of the present invention. However, it is to be understood that these examples are for illustrative purposes only and should not be used to limit the scope of the present invention in any manner.
This in vitro experimental study demonstrates variability in the response of cells from a specific donor to different EMF stimulation (intra-donor differences) and that, for equivalent EMF stimulation, there is donor-to-donor (i.e., inter-donor) differences. The response of different donor cells to various harmless and undetectable extremely-low frequency magnetic fields is compared using a PCR array. Outcomes relevant to osteogenesis and bone repair are quantified and compared using relative gene expression levels.
The data collected from the mesenchymal stem cell-specific PCR array provide evidence for variable gene expression depending on the donor and the EMF stimulation. The same exposure was shown to up-regulate or down-regulate genes differently for each donor and the response of a donor cell group was specific to the EMF field parameters. Donor PC-1 was exposed to six different stimulation profiles and observed marked increases in osteogenic and chondrogenic gene expression when subjected to a 1 mT, 75 Hz pulse for only 10 minutes per day. This same exposure did not generate a similar response from four other donors. While beneficial to PC-1, this exposure has not been optimized but demonstrates, at a cellular level, the need for donor-to-donor personalization and optimization for development of personalized treatment protocols as described herein.
The technology described herein utilizes and may ‘learn’ from the identified baseline gene expression differences inherent in the patient profile, and further influenced by the biological challenge, to compute a personalized microenvironment stimulation target and then actively optimize the treatment during the fracture's exposure to EMF.
Bone marrow-derived mesenchymal stem cells (BM-MSC) were procured for a wide range of donors, each possessing a unique patient profile (Table 2). MSCs from donors with no known pre-existing medical issues (Donor LZ-1) were obtained from Lonza (Lonza Walkersville, Walkersville, MD, USA). Cells sourced from PromoCell (PromoCell GmbH, Heidelberg, Germany) offer an expanded donor profile that includes age, sex, ethnicity, smoking status, body-mass index, and whether they suffer from osteoarthritis (Table 2). MSCs from four different donors, obtained from PromoCell, provide a diverse set of characteristics (Donors PC-1 through PC-4). Comparing baseline gene expression levels between donors (inter-donor) prior to exposure reveals significant differences that logically are likely to affect response to EMF stimulation.
indicates data missing or illegible when filed
Bone Marrow derived Mesenchymal stem cells (BM-MSCs) were sourced from different donors (PromoCell: C-12974/Lonza: PT-2501). Cells were thawed from frozen (−150° C.) and plated into a T75 flask containing DMEM supplemented with 1% GlutaMAX™ and 5% human platelet lysate. Cells were placed in an incubator set to 37° C. and 5.0% CO2. Media was exchanged 1 day after thawing to remove the DMSO. Media was exchanged every 2-3 days thereafter. Cells proliferated until 70-90% confluency. Upon reaching this threshold, cells were washed with DPBS and detached using TrypLE Select. The detached cells were neutralized, centrifuged, and seeded in culture vessels at a concentration of 5000 cells/cm2 for passaging.
For PCR analysis, the dissociated cells (approximately 500,000 cells) were neutralized using an equal volume of complete media and centrifuged for 2 minutes at 4000 RPM. Following centrifugation, the supernatant was aspirated, and the cell pellets were immediately frozen at −80° C. for future RNA extraction.
Stimulation in vitro profiles were designed consisting of biphasic alternating current (AC) magnetic fields whose waveforms were sinusoidal or pulsed. The driving waveforms (signals) varied not only in shape, but also frequency and amplitude. Table 3 lists details of each exposure evaluated, as well as the daily stimulation time and time spent in culture. The pulsed waveforms are driven using a biphasic rectangular wave with a 10% duty cycle and each of Experiment 1-3 has different daily exposure times. Sine wave inputs (Experiments 4-6) oscillate about zero (i.e., zero DC offset) and vary only in frequency. Stimulation profiles were varied for the same donor to demonstrate intra-donor variability (PC-1). Inter-donor comparisons are made by exposing cells from each of the five donors to the same electromagnetic field therapy (Experiments 1 and 5 for pulsed and sinusoidal stimulation, respectively).
Current through the coils was generated by a DG2052 waveform generator (Rigol Technologies, China) and then amplified by a BOP 100-4DL power supply (KEPCO, INC., USA). The waveform generator can generate sine waves up to 50 MHz (square wave at 15 MHz), however, stimulation frequencies were kept to the extremely low frequency range (<300 Hz). Low intensity, AC magnetic fields in this frequency range produce no heat or sound and have been shown to be harmless. The magnetic flux density of the induced field is at any instance directly proportional to the current in the coils (monitored using RP1001C current probe (Rigol Technologies, China)) and was measured using a 5180 gaussmeter and SAD18-1904 axial probe (F.W. Bell, USA). The maximum peak magnetic flux density was 4 mT. At high current, dissipated power in the coils resulted in elevated coil temperatures, however, the heating effect was negligible at the centre of the coils where the cells are situated. Exposure timing was controlled via remote commands sent to the waveform generator via LabVIEW (National Instruments, USA).
Cells were imaged prior to each feed and on the day of termination using a Zeiss Axio Vert A1 Inverted Microscope at 50× magnification.
RNA was extracted from frozen cell pellets using a RNeasy kit (Qiagen: 74004) and subsequent cDNA was reverse transcribed (Qiagen: 330404). Reverse transcribed templates ware analyzed by a Mesenchymal Stem Cell PCR Array (MSC RT2 Profiler Array (Qiagen: 330231; PAHS-082ZD)) on a BioRad CFX96 Real Time PCR Detection System. Each experimental point was performed in triplicate. Gene expression of the 84 genes of interest on each PCR array was normalized to reference genes (ΔCt) and then averaged within an experimental group. ΔΔCt for each gene was then calculated between groups before fold change was calculated according to 2(−ΔΔCt). In the results below, some data is presented in the form of heatmaps, where the fold change is displayed at log base 2.
Control and Exposed donor cell culture groups were imaged before each feed and before termination to monitor morphology. There were no morphological changes observed with or without EMF stimulation of any intensity or duration.
A PCR array designed specifically for mesenchymal stem cells (Qiagen) measures the expression levels of 84 different genes, A1 to G12, listed in Appendix I. Genes targeted in the array include stemness markers, differentiation markers, and other known mesenchymal stem cell specific genes. RNA isolated from Control cells belonging to each donor were analyzed using the PCR array to elucidate unstimulated baseline expression differences between donors (note that Controls are also used to quantify the effect of EMF exposure).
All five donor cell groups were exposed to a pulsed magnetic field following cell seeding. The field parameters were set according to Experiment 1 in Table 2 where the input pulse width was 1.3 ms (duty cycle=10%). Cells were exposed for 10 minutes per day until confluent. Cells were not exposed on the day the cells were terminated.
By selecting specific osteogenic genes from the PCR arrays shown in
Exposing cells from the five donors to an oscillating, sinusoidal magnetic field (Experiment 5 in Table 2) yields markedly different results. The sine wave (apart from being lower intensity and frequency than Experiment 1 has more gradual gradients than a pulse wave and will result in weaker induced electric currents. Figure C(b) shows gene expression heatmaps post-exposure to a sine wave for 6 hours a day. The sine wave produced much less extremes than the pulsed signal and there are fewer distinguishing factors from donor to donor. This result (particularly the lack of a significant response from PC-1) suggests that some EMF treatments influence biological responses at the cellular level in different ways on a patient-by-patient basis.
The field parameters defined in Experiments 1 to 6 (Table 3) were each used to stimulate PC-1 during growth. After normalizing to an unexposed control, the heatmaps in
The different responses to EMF treatments are highlighted by selecting and focusing on ten osteogenic genes (
A breast cancer cell line (MDA-MB-231) was cultured in the presence of various time-varying electromagnetic fields capable of inducing electric currents in the culture media and across the cells themselves. Proliferation cultures with four different exposure profiles yielded a different response from each experiment. Two exposures caused a statistically significant decrease in cell growth (a positive outcome for inhibiting cancer cells). The two exposure profiles were (i) a 432 Hz sine wave administered continuous from seeding to termination and (ii) a series of low frequency triangular waves with increasing separation for 3 hours per day. These two waveforms were investigated further using PCR arrays configured for cancer-related pathways. Despite the two exposures having a very similar effect on cell count, intra-donor variability was observed via the PCR arrays. Genes belonging to apoptosis, cellular senescence and angiogenesis pathways, to name a few, were all up-regulated in favour of inhibited cell growth. However, some indicators of increased proliferation and apoptosis inhibitors were also up-regulated. Additionally, the benefit of bioelectromagnetic therapy as an adjunct to chemotherapy was demonstrated using cisplatin. When the two modalities are combined, the EMF acts to enhance the effect of the cisplatin and cell count are significantly decreased.
These results support personalized treatment optimization using EMF based on the type of cancer for slowing tumour growth demonstrating bioelectromagnetic therapy as an attractive alternative (or adjunct) to traditional chemotherapy and/or radiotherapy.
MDA-MB-231 cells, a human triple-negative breast cancer cell line, were obtained at passage 40 (Sigma: 92020424). The culture media used was high glucose DMEM (Gibco: 31053-028) supplemented with 1% GlutaMAX™ (Gibco: 35050-061) and 10% fetal bovine serum (Gibco).
Cells were thawed from frozen (−150° C.), placed in a tube with warm media and spun down for 5 minutes at 240×g. After pelleting the cells, the media was removed, and the cells resuspended and seeded into a T225 flask with 45 mL of media. Cells were placed in an incubator set to 37° C. and 5.0% CO2. Media was exchanged every 2-3 days. Cells proliferated until they reached 80-90% confluency. Upon reaching this threshold. cells were passaged. Cells were washed with DPBS and detached using TrypLE Express (Gibco). The detached cells were neutralized, centrifuged, and seeded in culture vessels at a density of 10,000 cells/cm2.
For experimental harvests cells were detached as when passaging and neutralized with media. A 100 μL aliquot was taken and used for cell counts. Cells were counted on a NC-200 Nucleocounter (ChemoMetec). The remaining dissociated cells were centrifuged for 2 minutes at 4000 RPM. Following centrifugation, the supernatant was aspirated, and the cell pellets were immediately frozen at −80° C. for future RNA extraction.
Cells were imaged prior to each feed and on the day of termination using a Zeiss Axio Vert A1 Inverted Microscope at 50× magnification.
Cisplatin is a platinum-based chemotherapy drug that inhibits DNA synthesis. Cisplatin is used in the treatment of many cancers, including breast cancer. Cisplatin (Millipore-Sigma: 232120) was dissolved in DPBS with 140 mM NaCl at a concentration of 1 mg/mL and stored at room temperature, protected from light. The solution was further diluted in culture media to obtain the desired concentration for experiments. DPBS with 140 mM NaCl was used as a vehicle control. Cisplatin at 20 μM was used as a positive control as this concentration reduced the cell number by more than 90%. Lower concentrations of 2 μM and 0.667 μM (one tenth and one thirtieth the concentration of the positive control, respectively) were used in combination with PEMF stimulation.
RNA was extracted from frozen cell pellets using a RNeasy kit (Qiagen: 74004) and subsequent cDNA was reverse transcribed (Qiagen: 330404). Reverse transcribed templates ware analyzed by a Human Cancer PathwayFinder™ PCR Array (Human Cancer PathwayFinder™ RT2 Profiler Array (Qiagen: 330231; PAHS-033Z)) on a BioRad CFX96 Real Time PCR Detection System. Each experimental point was performed in triplicate. Gene expression of the 84 genes of interest (Appendix II) on each PCR array was normalized to reference genes (ΔCt) and then averaged within an experimental group. ΔΔCt for each gene was then calculated between groups before fold change was calculated according to 2(−ΔΔCt). In the results below, some data is presented in the form of heatmaps, where the fold change is displayed at log base 2.
Cells were exposed, as previously described for mesenchymal stem cells, to a spatially uniform, time-varying magnetic field using Helmholtz coils. A description of the exposure system (coils, signal generator, incubators, etc.) is described in Example One.
Demonstrated are effects of four low-frequency magnetic fields (are non-invasive and cause no pain) on the growth and gene expression on a breast cancer cell line. Extremely low frequency magnetic fields on cancerous cells have demonstrated inhibition of proliferation (Bergandi L, Lucia U, et al., BBA—Mol Cell Res. 2019; 1866:1389-1397) and/or increased apoptosis (Giladi M, Schneiderman R S, et al., Sci Rep. 2015; 5:18046). Table 3 contains the parameters describing four different fields covering a wide range of shapes, intensities and frequencies. The two sinusoids are simple sine waves with no offset. The pulse waveform has a 10% duty cycle, creating sudden, large changes in the field's magnetic flux density (B). Finally, Experiment 4 consists of pairs of triangular waves with increasing separation equivalent to a decreasing frequency from 36 Hz to 10 Hz. The waveform consists of 15 pairs and has a period of approximately 900 ms. Positive results with Experiments 3 and 4 (described below) ledto repeating the exposures with the addition of a chemotherapy drug cisplatin). Additionally, Experiments 3 and 4 were also performed with “healthy” chondrocytes.
Breast cancer cells were exposed to one of the four experimental stimulation profiles described in Table 4 during the entirety of the culture (4-5 days). The desired outcome is decreased proliferation to inhibit the uncontrolled division of cancer cells.
The effective stimulation profiles (3 and 4) were analyzed further using a cancer pathway finder PCR array designed specifically for cancer cells. The array contains primers for 84 genes related to, for example, one or more of apoptosis, cellular senescence, and angiogenesis. A list of the genes is included in Appendix II. The heatmaps in
The biological mechanism of cancer cell growth inhibition with EMF exposure is poorly understood and on-going research continues to investigate the effects of an incredibly wide range of EMF parameters and delivery methods, within the extremely low frequency range and beyond. The gene expression levels for the two seemingly effective stimulations in Figure I highlight genes involved in affected pathways. The decreased cell counts post exposure can be related to increases in the expression of pro-apoptotic genes APAF1 (heatmap position: A6) and CASP2 (B2), however, apoptosis inhibitors NOL3 (E8) and XIAP (G12) are also up-regulated. Further, cellular senescence is generally promoted causing cell proliferation arrest: IGFBP3 (D7) and IGFBP7 (D9), MAP2K3 (E4) and MAPK14 (E5) all have increased expression. Markers of DNA damage and repair (DDB2 (C1), PPP1R15A (F2) and GADD45G (D3)) changed in favour of apoptosis and tumour suppression. To the contrary, many of the genes related to cell cycle pathways (e.g., MCM2 (E6) and MKI67 (E7)) are typically high in cancer cells and have been further expressed post-exposure, which would be in favour of increased proliferation. Finally, ANGPT1 (A4) and CCL2 (B5), both genes involved in angiogenesis that recruit blood supply for growing tumours, are down-regulated by the EMF. The genes discussed are some of the more strongly regulated genes by either stimulation.
Chemotherapy drugs, including cisplatin, are a commonplace and proven method of treating cancer tumours despite a plethora of side effects. Large doses of these drugs can be a significant monetary and health concern for many patients so any method of reducing the dosage with an adjunct therapy is welcome. To test the combined effect of cisplatin and EMF exposure, two low concentrations (2 μM and 0.667 μM) of cisplatin were added to the culture media of MDA-MB-231 cells subjected to Experiment 3 and 4 exposures. Additionally, cells were cultured with 20 μM of cisplatin and no exposure as a “positive” control.
The effect of EMF stimulation on pain-related gene expression in normal human astrocytes sourced from three different donors was tested. The findings demonstrate inter-donor and intra-donor variability to different EMF stimulation profiles. This supports that patient-to-patient differences will affect their response to EMF treatment at a cellular level and that a personalized parameter set will be required for each patient to achieve a desired outcome.
Astrocytes are an abundant cell type in the central nervous system and are included in many essential processes required to maintain a healthy system. Astrocytes were chosen for this in vitro study because they are involved along pain perception and modulation pathways where they are responsible for producing and regulating pro-inflammatory and anti-inflammatory substances. In the case of chronic pain, reactive astrocytes may accentuate pain perception and inflammatory responses long after the pain-inducing injury occurred. It is presently demonstrated that the expression of inflammatory genes in reactive astrocytes can be down-regulated using EMF stimulation. Stimulation was not universally beneficial and changing the waveform, frequency, or intensity of the field affected gene expression levels. Additionally, different cell donors had variable responses to the same stimulation profile. This finding supports patient-by-patient optimization, whereby a personalized microenvironment stimulation target is generated based on a patient profile and then actively modified and optimized subject to pain level feedback from the patient.
The sensation of pain is a complex biophysical process which involves many neuroanatomic and neurochemical systems. Primarily, the nociceptive pathway is used to transmit and process information to and from the brain upon noxious stimulation of tissue. On a macroscopic level, this involves the transmission of signals from the area of noxious stimuli using the afferent pathway to the dorsal root ganglion which transfers the information to the brain.
Within the nociceptive pathway, there is a known interaction between neuronal cells and neuroglial cells which contribute to the perception of pain. As the most abundant cell type in the CNS, astrocytes have been identified as an active contributor to the sensation of pain through the process of reactive astrogliosis. In the presence of noxious stimuli, astrocytes undergo a phenotypic and functional change to become reactive which involves inflammatory and neurotoxic responses contributing to the sensation of pain. In particular, cortical reactive astrocytes have demonstrated the ability to create a chemical imbalance of glutamate and gamma aminobutyric acid (GABA) which leads to synaptic remodelling and chronic pain. Thus, the induction of astrocytes into a reactive state may be considered a reasonable model of pain by examining the ability of EMF to revert reactive astrocytes into a naïve or non-inflammatory state.
Normal human astrocytes (NHA), isolated from brain tissue (cerebral cortex), from three different donors were purchased. The first donor, NHA1, was procured from Lonza (Lonza Walkersville, Walkersville, MD, USA), while NHA2 and NHA3 were purchased from ScienCell (ScienCell Research Laboratories, Inc., Carlsbad, CA, USA). Information pertaining to the donors themselves was not provided, but baseline gene expression levels (see below) reveal inter-donor differences prior to any EMF treatment.
Astrocytes were sourced from different donors (Lonza: CC-2565/ScienCell: 1800). Cells were thawed from frozen (−150° C.) and plated into a poly-D-lysine coated T75 flask containing astrocyte culture medium (Lonza: CC-3186/ScienCell: 1801-prf). Cells were placed in an incubator set to 37° C. and 5.0% CO2. Media was exchanged 1 day after thawing to remove the DMSO. Media was exchanged every 2-3 days thereafter. Cells proliferated until 70-90% confluency. Upon reaching this threshold, cells were washed with DPBS and detached using 0.05% Trypsin supplemented with neutral proteases. The detached cells were neutralized, centrifuged, and seeded in poly-D-lysine coated culture vessels at a concentration of 5000 cells/cm2 for passaging.
For PCR analysis, the dissociated cells (approximately 500,000 cells) were neutralized using an equal volume of complete media and centrifuged for 2 minutes at 4000 RPM. Following centrifugation, the supernatant was aspirated, and the cell pellets were immediately frozen at −80° C. for future RNA extraction.
To induce astrocytes into an inflammatory reactive state, cytokines TNFα (R&D Systems: 210-TA-005/CF) and IL-1B (201-LB-005/CF) were added to cultures at a concentration of 10 ng/mL following the method described by Hyvärinen et al., 2019 (Hyvärinen T, Hagman S, et al., Sci Rep. 2019; 9:16944). Media was exchanged every 2-3 days.
Cells were exposed, as previously described for mesenchymal stem cells, to a spatially uniform, time-varying magnetic field using Helmholtz coils. The exposure system (coils, signal generator, incubators, etc.) is as described in Example 1 (bone healing).
Previous pain management systems have implemented a diverse set of stimulation profiles using a variety of deployment methods. There is no consensus on the most effective EMF parameters but there is a trend towards low intensity and very low frequency stimulation that results in an imperceptible electromagnetic field. Table 5 contains the exposure parameters used in each of three experiments designed to show the inter-donor and intra-donor variability of astrocytes exposed to electromagnetic stimulation. Experiment 1 tested the response of all three donors to a 15 Hz sinusoid for 10 min/day, while Experiments 2 and 3 only included a single donor (NHA2). Relative to the sinusoid, the ramp (Experiment 2) and pulse (Experiment 3) functions induce stronger electric currents in the media due to sharp changes in the input signal, and do so at significantly higher and lower frequencies, respectively.
Cells were imaged prior to each feed and on the day of termination using a Zeiss Axio Vert A1 Inverted Microscope at 50× magnification.
qPCR
RNA was extracted from frozen cell pellets using a RNeasy kit (Qiagen: 74004) and subsequent cDNA was reverse transcribed (Qiagen: 330404). The expression levels of glial fibrillary acidic protein (GFAP), interleukin 6 (IL6), interleukin 1β (IL-1β), tumor necrosis factor-α (TNFα), complement component 3 (C3), transforming growth factor Beta 1 (TGFβ1), signal transducer and activator of transcription (STAT3), interleukin 8 (IL8), SRY-box transcription factor 9 (SOX9) were determined relative to the reference gene glyceraldehyde 3-phosphate dehydrogenase (GAPDH) by real-time RT-PCR using the SYBR Green detection system. Each sample was diluted 1:10 and analyzed in duplicate using the iTaq Universal SYBR Green Supermix (BioRad: 1725122) with the optimized concentration of forward and reverse primer (0.6 μM) on a CFX96 Touch™ real-time RT-PCR machine (Bio Rad). The program used to run all samples included an enzyme activation step at 95° C. for 30 sec followed by 40 cycles with 95° C. for 3 sec and 60, 61, 62, or 63° C. (depending on target gene) for 30 sec. After the amplification phase, a dissociation curve was established to ensure the presence of a single amplicon. Reaction efficiencies were 100±10% with an R 2>0.990 and calculated by the CFX Manager Software (Bio Rad, Mississauga, ON, Canada). In each assay, a standard curve created with gBlocks (specifically designed for each gene amplicon), a no template control, and a no reverse transcription control (to ensure the absence of genomic DNA in the samples) were run with the samples. The standard curve was generated by serial dilution of the gBlocks. The standard curve was then used to interpolate and calculate the mRNA level of target and reference gene in each sample. The mRNA level of each target gene was calculated relative to the reference gene GAPDH.
RNA was extracted from frozen cell pellets using a RNeasy kit (Qiagen: 74004) and subsequent cDNA was reverse transcribed (Qiagen: 330404). Reverse transcribed templates ware analyzed by a Human Pain: Neuropathic and Inflammatory PCR Array (Human Pain: Neuropathic and Inflammatory RT2 Profiler Array (Qiagen: 330231; PAHS-162Z)) on a BioRad CFX96 Real Time PCR Detection System. Each experimental point was performed in triplicate. Gene expression of the 84 genes of interest on each PCR array was normalized to reference genes (ΔCt) and then averaged within an experimental group. ΔΔCt for each gene was then calculated between groups before fold change was calculated according to 2(−ΔΔCt). In the results below, some data is presented in the form of heatmaps, where the fold change is displayed at log base 2.
Control and Exposed donor cell culture groups were imaged before each feed and before termination to monitor morphology. For groups receiving reactive state cytokines (IL-1β and TNFα), there is an expected morphological change as the astrocytes alter their phenotype.
The normal human astrocytes were placed into their reactive state by culturing with an additional set of growth factors, including IL-1β and TNFα. The state of the astrocytes was verified 72 hours after seeding by terminating the cells, isolating RNA and detecting for specific marker genes using qPCR. Nine genes were quantified as markers of the reactive state, including four that should be down-regulated (GFAP, TGFβ, STAT3 and SOX9) and five that are expected to have increase expression levels (IL6, TNFα, IL8, IL-1β and C3).
The PCR array heatmap in
The pain PCR array was utilized to compare the baseline gene expression levels of each donor cell group to the others while in a reactive state.
The stimulation profile tested in Experiment 1 (Table 4) was applied to each astrocyte donor cell group to demonstrate inter-donor variability due to EMF exposure. The short daily exposure produces quantifiable changes in gene expression levels and notable changes from donor to donor (relative to their own controls).
In
Donor NHA2 was exposed to three different EMF stimulation profiles covering a broad range of frequencies, exposure times, and signal shapes (Table 4). The three experiments each resulted in altered gene expression (relative to reactive state quantities) and demonstrate the varied effects treatment with EMF can elicit. Heatmaps in
The result of Examples 1-3 when taken together, demonstrate inter-donor differences at the cellular level supporting the need for donor-to-donor treatment personalization and optimization.
The results also support the use of gene expression as a useful tool to monitor and characterize the effects of EMF treatment on the cells of the microenvironment and may further provide guidance for either amending the treatment protocol or for the use of an adjunct therapy. A baseline gene expression profile can be obtained from patient cells prior to the start of treatment to determine EMF gene targeting effects. This clinical data would be supplemental data to include in the “Patient Profile” as one of the variable biological parameters fed to MiCE to compute a personalized microenvironment stimulation target for the patient. Any appropriate cell type may be extracted/harvested from a patient from for example a blood draw, a mouth swab, or invasively from the microenvironment. Gene expression and control levels can be assessed at different time points throughout the treatment protocol to allow progressive therapy optimization. The selection of genes may be dependent on the cell/tissue type as well as on the type of injury and disease. Non-limiting examples of genes for expression array assessment are listed in Appendices I-III.
Aspects, including embodiments, of the present subject matter described herein may be beneficial alone or in combination, with one or more other aspects or embodiments. Without limiting the foregoing description, certain non-limiting aspects of the disclosure numbered 1-66 are provided below. As will be apparent to those of skill in the art upon reading this disclosure, each of the individually numbered aspects may be used or combined with any of the preceding or following individually numbered aspects. This is intended to provide support for all such combinations of aspects and is not limited to combinations of aspects explicitly provided below:
The descriptions of the various embodiments and/or examples of the present invention have been presented for purposes of illustration but are not intended to be exhaustive or limited to the embodiments and/or examples disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application, or to enable further understanding of the embodiments disclosed herein.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/CA2022/051490 | 10/7/2022 | WO |
| Number | Date | Country | |
|---|---|---|---|
| 63253850 | Oct 2021 | US |
