Patent Application
20220405192
The present disclosure relates to the field of software quality assurance systems; in particular, systems and methods for scientific evaluation and data-driven analysis of program code outputs for digital health interventions and software as a medical device products.
Before a new medical treatment (e.g., pharmaceuticals) or device (e.g., surgical instruments or implants) may be dispensed to the public, the relevant regulatory agency for the jurisdiction in which market approval for the treatment or device is being sought, e.g. United States Food and Drug Administration (FDA) in the United States, requires that the manufacturers of the pharmaceuticals, devices, instruments, or implants conduct extensive clinical trial research in order to demonstrate the clinical effectiveness, safety, and medical advantage of their products. Extensive and often complex clinical trial protocols are developed that define, for example, targeted demographics, proposed medications, patient regimens, forms for collection, types of statistically relevant data, the timing or order of events within the study, often even the layout of the reporting data, or other suitable data.
An expanding area of medical devices and technologies is in the area of digital health interventions (i.e. interventions delivered via digital technologies such as smartphones, website, text messaging) to provide effective, cost-effective, safe, and scalable interventions to improve health and healthcare. Digital health interventions (DHI) of software as a medical device (SaMD) can be used to promote healthy behaviors, improve outcomes in people with long term conditions such as cardiovascular disease, diabetes and mental health conditions and provide remote access to effective treatments; for example, computerized cognitive behavioral therapy for mental health and somatic problems. Software as a Medical Device (SaMD) is defined by the International Medical Device Regulators Forum (IMDRF) as “software intended to be used for one or more medical purposes that perform these purposes without being part of a hardware medical device.” DHIs are often complex interventions with multiple components, and many have multiple aims including enabling users to be better informed about their health, share experiences with others in similar positions, change perceptions and cognitions around health, assess and monitor specified health states or health behaviors, titrate medication, clarify health priorities and reach treatment decisions congruent with these, and improve communication between patients and health care professionals (HCP). Active components may include information, psychoeducation, personal stories, formal decision aids, behavior change support, interactions with HCP and other patients, self-assessment or monitoring tools (questionnaires, wearables, monitors, and effective theory-based psychological interventions developed for face-to-face delivery such as cognitive behavioral therapy or mindfulness training).
Regulatory review and approval of DHIs and SaMD products incorporates unique regulatory evaluation considerations that are not relevant to “traditional” medical treatments and devices. Clinical evaluation of SaMD and DHIs may require manufacturers to continuously generate, collect, analyze, and assess the clinical data pertaining to a SaMD/DHI in order to generate clinical evidence to verify the clinical association and the performance metrics of the product when used as intended by the manufacturer. SaMD and DHIs may be further subject to on-going lifecycle scrutiny to thoroughly evaluate the product's performance. Once the product is on the market (post-market), as part of normal lifecycle management processes, the manufacturer may be required to continuously collect real-world performance data (e.g., complaints, safety data), to further understand the user's needs to ensure the product is meeting those needs, and to monitor the product's continued safety, effectiveness and performance in real-world use.
The unique nature of SaMD and DHI products as compared to “traditional” medical treatments and devices pose specific challenges with respect to clinical evaluation and clinical trials for such products. There exists a need for a systems and methods to support scientific evaluation and clinical trials of SaMD and DHI products. Through applied effort, ingenuity, and innovation, Applicant has identified deficiencies of prior art solutions and has developed a solution that is embodied by the present disclosure, which is described in detail below.
In order to provide a basic understanding of the invention, the following is a simplified summary of certain embodiments thereof. This summary is not an extensive and is not intended to identify key/critical elements of the invention or to delineate the scope of the invention. Its sole purpose is to present embodiments of the invention in a simplified form as a prelude to the more detailed description that is further below.
An object of the present disclosure includes systems, methods, devices and computer-readable media configured to collect, process, and manage data from one or more endpoints, across one or more platforms or systems, associated with a DHI/SaMD program, product or platform. Further objects provide for methods for quality control, quality analysis, and quality assurance of program code as well as feature set validation of DHI/SaMD products.
An object of the present disclosure includes systems, methods, devices and computer-readable media configured to process and analyze data being generated through one or more user interactions with a DHI and/or a SaMD program, product or platform for the purpose of providing a statistical analysis of a clinical association between the output of a DHI/SaMD and a targeted clinical condition (to include a pathological process or state); and that the DHI and/or SaMD provides the expected technical and clinical data as defined by manufacturer specifications.
An object of the present disclosure includes a data management system to assess safety, efficacy, performance, and/or patient outcomes associated with a DHI and/or SaMD program, product or platform; and to provide for a distributed platform to generate an accumulating knowledge base associated with a DHI/SaMD that can be used to guide decision-making for manufacturers of DHIs/SaMDs.
An object of the present disclosure includes a data management system and distributed platform for research and evaluation of a DHI/SaMD. Certain embodiments of the data management system and distributed platform may be configured to assess patient outcomes and overall impact of a DHI/SaMD across a patient population and provide data-driven analysis to improve human-centered design methods.
An object of the present disclosure includes a data processing and data management system for development, analysis and/or validation of causal models related to one or more components of a DHI/SaMD. In accordance with some embodiments, a data processing and management system is configured to identify one or more essential or active components of a DHI/SaMD (and its delivery package). Certain embodiments may be configured to process and analyze data according to certain predefined business logic or rules-based framework(s); such as, for example, a Multiphase Optimization Strategy (MOST). Certain embodiments may be configured to process and analyze data according to one or more predictive model and/or machine learning framework(s), including but not limited to linear/logistic regression, principal component analysis, a generalized linear mixed model, a random decision forest, a support vector machine, and an artificial neural network.
An object of the present disclosure is to provide for systems and methods for conducting randomized controlled trials (RCTs) for DHIs/SaMDs. Certain embodiments provide for systems and methods for manufacturers of DHIs/SaMDs to generate more useful data through: improving methods of early formative product design and development; better understanding of when and how short-term proxy outcomes should be used and when definitive outcomes are needed; better methods for improving internal validity of trials and/or feature analysis without jeopardizing external validity; improved methods for enhancing DHI/SaMD uptake and minimizing missing data; and better methods for considering whether and how DHI/SaMD can become scalable and sustainable across a targeted patient population.
An object of the present disclosure is to provide for a distributed research and evaluation platform configured to enable more useful synthesis and comparison of data generated by different studies of DHIs and SaMDs through: improved specification and classification of context, target populations, digital health interventions and their components, using more appropriate comparators for the stage of the research process, and improved reporting of trials and studies of DHIs and SaMDs.
Certain aspects of the present disclosure provide for a computer-implemented system comprising at least one server being communicably engaged with a communications network to receive a plurality of input data from one or more endpoints, the one or more endpoints comprising one or more electronic devices being associated with at least one user in a user population, the plurality of input data comprising a plurality of user-generated inputs in response to one or more computerized stimuli or interactions, the one or more computerized stimuli or interactions being associated with a targeted medical or personal wellness output; wherein the at least one server comprises a processor, a database and a non-transitory computer-readable medium having one or more instructions stored thereon that, when executed, cause the processor to perform one or more operations, the one or more instructions comprising instructions for analyzing, for the at least one user in the user population, a stimulus-response pattern between the one or more computerized stimuli or interactions and the plurality of user-generated inputs at two or more time points to determine one or more performance metrics for the at least one user in the user population; analyzing the plurality of input data and the one or more performance metrics to determine one or more user outcome metrics for the at least one user in the user population; analyzing, according to a validation model, the one or more computerized stimuli or interactions and the one or more user outcome metrics to determine one or more efficacy metrics associated with the targeted medical or personal wellness output; and outputting the one or more user outcome metrics and the one or more efficacy metrics to one or more administrator devices.
In accordance with certain embodiments, the one or more instructions may further comprise instructions for segmenting the user population into two or more user groups according to one or more scientific evaluation parameters and/or protocols. The one or more computerized stimuli or interactions may comprise an instance of a mobile software application executing on a mobile electronic device, wherein the mobile software application may comprise a computer-implemented therapy or intervention associated with a targeted physiological or cognitive condition or state.
In accordance with certain embodiments, the one or more instructions may further comprise instructions for modifying or configuring the one or more computerized stimuli or interactions according to one or more scientific evaluation parameters and/or protocols. The one or more instructions may further comprise instructions for continuously receiving the plurality of input data from the one or more electronic devices and segmenting the plurality of input data according to one or more scientific evaluation parameters and/or protocols. In accordance with certain embodiments, the one or more instructions may further comprise instructions for modifying one or more user permission or revoking user access to the mobile software application according to one or more scientific evaluation parameters and/or protocols.
In accordance with further embodiments, the one or more endpoints may further comprise an electronic medical records server or third-party application server. The one or more instructions may further comprise instructions for analyzing the plurality of input data according to one or more scientific evaluation parameters to determine a measure of protocol compliance or deviation for the at least one user in the user population. Further still, the one or more instructions may comprise instructions for dynamically modifying or configuring the one or more computerized stimuli or interactions for a first user group in the two or more user groups according to the one or more scientific evaluation parameters.
Further aspects of the present disclosure provide for a computer-implemented system comprising at least one server comprising at least one processor, the at least one server implementing a plurality of functional modules configured to provide a plurality of scientific evaluation functions; an application server communicably engaged with the at least one server via a communications network, the application server hosting a software product configured to process a plurality of user inputs in response to one or more computerized stimuli or interactions to generate a targeted output for treatment, diagnosis or management of a medical or personal wellness condition; and a non-transitory computer readable storage medium operably engaged with the at least one processor and encoded with computer-executable instructions that, when executed by the at least one processor, perform a method for scientific evaluation of the software product, the method comprising establishing a communication interface and data transfer protocol between the application server and the at least one server, the data transfer protocol being configured to enable secure transmission of mobile endpoint data to the at least one server, wherein the mobile endpoint data comprises user-generated data from a user device executing an instance of the software product; configuring one or more scientific evaluation parameters for the software product comprising one or more usage or session parameters for one or more users of the software product, wherein the one or more users comprise a user population; providing one or more instance of the software product to the user device for the one or more users in the user population in accordance with the one or more scientific evaluation parameters; receiving mobile endpoint data and user-generated data for the one or more users in the user population; processing the mobile endpoint data and user-generated data according to an analytical framework to determine one or more user statistics and one or more stimulus-input patterns for the one or more users in the user population, the one or more user statistics and the one or more stimulus-input patterns comprising user outcome data; and analyzing the user outcome data for the user population according to at least one statistical framework to determine one or more scientific validation metrics for the targeted output of the software product.
In accordance with said aspects of the present disclosure, the method for scientific evaluation of the software product encoded on the non-transitory computer readable medium may further comprise monitoring user adherence (e.g. protocol compliance or deviation) to the one or more scientific evaluation parameters. The method may further comprise segmenting the user population into two or more user groups according to the one or more scientific evaluation parameters, wherein the one or more scientific evaluation parameters comprise a first set of parameters for a first user group and a second set of parameters for a second user group in the two or more user groups. Certain embodiments of the computer-implemented system of the present disclosure may further comprise at least one third-party application server being communicably engaged with the at least one server via a communications network, the at least one third-party application server being configured to execute at least one scientific evaluation function.
In accordance with certain aspects of the present disclosure, the method for scientific evaluation of the software product encoded in the non-transitory computer readable medium may further comprise modifying the one or more computerized stimuli or interactions or revoking access to the software product according to one or more scientific evaluation parameters. The method may further comprise providing one or more notifications to the user device according to the one or more scientific evaluation parameters, the one or more notifications comprising user instructions or user prompts for executing an instance of the software product. In accordance with certain embodiments, the one or more notifications are provided to the user device according to one or more user adherence rules.
Still further aspects of the present disclosure provide for a computer-implemented system comprising at least one server comprising at least one processor, the at least one server implementing a plurality of functional modules configured to provide a plurality of scientific evaluation functions; an application server communicably engaged with the at least one server via a communications network, the application server hosting a software product configured to process a plurality of user inputs in response to one or more computerized stimuli or interaction to generate a targeted output for treatment, diagnosis or management of a medical or personal wellness condition; and a non-transitory computer readable storage medium operably engaged with the at least one processor and encoded with computer-executable instructions that, when executed by the at least one processor, perform a method for scientific evaluation of the software product, the method comprising establishing a communication interface and data transfer protocol between the application server and the server, the data transfer protocol being configured to enable secure transmission of mobile endpoint data to the server, wherein the mobile endpoint data comprises user-generated data from a user device executing an instance of the software product; configuring one or more clinical evaluation parameters for the software product comprising one or more safety, efficacy or performance parameters for the software product; providing one or more instance of the software product to the one or more user devices at two or more time points; receiving the user-generated data and the mobile endpoint data from the one or more user devices; processing the user-generated data and the mobile endpoint data according to an analytical framework to determine one or more user statistics and one or more stimulus-input patterns for each user in the user population, the one or more user statistics and the one or more stimulus-input patterns comprising user outcome data; and analyzing the user outcome data according to at least one statistical framework to determine one or more safety, efficacy or performance metrics for the software product.
In accordance with said aspects of the present disclosure, the method for scientific evaluation of the software product encoded on the non-transitory computer readable medium may further comprise modifying or configuring the one or more computerized stimuli or interactions in response to the one or more safety, efficacy or performance metrics. The method may further comprise processing the user-generated data and the mobile endpoint data in response to modifying or configuring the one or more computerized stimuli or interactions, and analyzing the user outcome data according to the at least one statistical framework to determine a measure of change in the one or more safety, efficacy or performance metrics. The method may further comprise further modifying or configuring the one or more computerized stimuli or interactions in response to the measure of change in the one or more safety, efficacy or performance metrics.
The foregoing has outlined rather broadly the more pertinent and important features of the present invention so that the detailed description of the invention that follows may be better understood and so that the present contribution to the art can be more fully appreciated. Additional features of the invention will be described hereinafter which form the subject of the claims of the invention. It should be appreciated by those skilled in the art that the conception and the disclosed specific methods and structures may be readily utilized as a basis for modifying or designing other structures for carrying out the same purposes of the present invention. It should be recognized by those skilled in the art that such equivalent structures do not depart from the spirit and scope of the invention.
The above and other objects, features and advantages of the present disclosure will be more apparent from the following detailed description of, and in conjunction with, the accompanying drawings, which are briefly described below.
Exemplary embodiments are described herein so as to provide a more detailed description of the invention. Variations of the various embodiments will be apparent to those of skill in the art. Therefore, before specific exemplary embodiments of the invention are described, it is to be understood that this invention is not limited to the exemplified embodiments described herein. It is also to be understood that the terminology used herein is for the purpose of describing certain specific embodiments and is not intended to limit the scope of the invention which is defined only by the appended claims.
Moreover, certain terminology is used in the following description for convenience only and is not limiting. For example, the words “right,” “left,” “top,” “bottom,” “upper,” “lower,” “inner” and “outer” designate directions in the drawings to which reference is made. The word “a” is defined to mean “at least one.” The terminology includes the words above specifically mentioned, derivatives thereof, and words of similar import.
Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limit of that range and any other stated or intervening value in that stated range is encompassed within the invention. The upper and lower limits of these smaller ranges may independently be included in the smaller ranges is also encompassed within the invention, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either both of those included limits are also included in the invention.
The indefinite articles “a” and “an,” as used herein in the specification and in the claims, unless clearly indicated to the contrary, should be understood to mean “at least one.” 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, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with “and/or” should be construed in the same fashion, i.e., “one or more” of the elements so conjoined. 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. Thus, as a non-limiting example, a reference to “A and/or B”, when used in conjunction with open-ended language such as “comprising” can refer, in one embodiment, to A only (optionally including elements other than B); in another embodiment, to B only (optionally including elements other than A); in yet another embodiment, to both A and B (optionally including other elements); etc.
As used herein in the specification and in the claims, “or” should be understood to have the same meaning as “and/or” as defined above. For example, when separating items in a list, “or” or “and/or” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as “only one of’ or “exactly one of,” or, when used in the claims, “consisting of,” will refer to the inclusion of exactly one element of a number or list of elements. In general, the term “or” as used herein shall only be interpreted as indicating exclusive alternatives (i.e. “one or the other but not both”) when preceded by terms of exclusivity, such as “either,” “one of,” “only one of,” or “exactly one of.” “Consisting essentially of,” when used in the claims, shall have its ordinary meaning as used in the field of patent law.
As used herein in the specification and in the claims, the phrase “at least one,” in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase “at least one” refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, “at least one of A and B” (or, equivalently, “at least one of A or B,” or, equivalently “at least one of A and/or B”) can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc.
In the claims, as well as in the specification above, all transitional phrases such as “comprising,” “including,” “carrying,” “having,” “containing,” “involving,” “holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to.
The terms “program” or “software” are used herein in a generic sense to refer to any type of computer code or set of computer-executable instructions that can be employed to program a computer or other processor to implement various aspects of the present technology as discussed above. Additionally, it should be appreciated that according to one aspect of this embodiment, one or more computer programs that when executed perform methods of the present technology need not reside on a single computer or processor, but may be distributed in a modular fashion amongst a number of different computers or processors to implement various aspects of the present technology. Computer-executable instructions may be in many forms, such as program modules, executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Typically, the functionality of the program modules may be combined or distributed as desired in various embodiments.
As used in certain examples herein, the term “healthcare provider” encompasses one or more of a physician (including a pediatrician and/or a behavioral specialist), a nurse, a physician's assistant, a psychologist, a psychiatrist, and the supporting clinical and administrative office staff of a healthcare or medical facility.
As used in certain examples herein, the term “user” encompasses one or more of an end user of a software program, product or platform and may further include: a patient being engaged with a software program, product or platform for a targeted medical or personal wellness purpose; a participant in a clinical trial, study or evaluation of a software program, product or platform; a user being engaged with a software program, product or platform for the purpose of evaluating or developing one or more technical, clinical, and/or functional aspects of a digital health intervention and/or a software as a medical device program, product or platform.
As used herein the terms “software program,” “software product,” and “software platform” may be used interchangeably and may be used to described one or more software program, product or platform, including any product(s), program(s) and/or platform(s) that incorporate any combination of hardware and software, being designed and/or utilized for any targeted medical or personal wellness purpose, including but not limited to the treatment, diagnosis, management, prevention, cure, or generation/provision of clinical/health/wellness insights or recommendations to one or more users for one or more medial, health or personal wellness purpose; including one or more digital health intervention (DHI) and/or software as a medical device (SaMD); and may further include software that is itself directly therapeutically active in treating and/or targeting one or more neurological circuits related to one or more neurological, psychological and/or somatic conditions, diseases, and/or disorders, rather than just being a component of overall treatment.
As used herein the term “digital health intervention (DHI)” may be used interchangeably with software as a medical device (SaMD) and encompasses any software program, product, or platform, including any software/hardware combination, being designed and/or utilized for any targeted medical or personal wellness purpose, including but not limited to the treatment, diagnosis, management, prevention, cure, or generation/provision of clinical/health/wellness insights or recommendations to one or more users for one or more medial, health or personal wellness purpose; including any software program, product, or platform, including any software/hardware combination, being designed and/or utilized to promote healthy behaviors, improve outcomes in people with long term conditions such as cardiovascular disease, diabetes and mental health conditions and provide remote access to effective treatments; for example, computerized cognitive behavioral therapy for mental health and somatic problems; and may further encompass one or more software program, product or platform, including any product(s), program(s) and/or platform(s) that incorporate any combination of hardware and software, that is/are directly therapeutically active in treating and/or targeting one or more neurological circuits related to one or more neurological, psychological and/or somatic conditions, diseases, and/or disorders, rather than just being a component of overall treatment.
As used herein the term “software as a medical device (SaMD)” may be used interchangeably with the term digital health intervention (DHI) and encompasses any software program, product, or platform, including any software/hardware combination, being designed and/or utilized for any targeted medical or personal wellness purpose, including but not limited to the treatment, diagnosis, management, prevention, cure, or generation/provision of clinical/health/wellness insights or recommendations to one or more users for one or more medial, health or personal wellness purpose; and may further encompass any software program, product, or platform, including any software/hardware combination, intended to be used for one or more medical purposes that perform these purposes without being part of a hardware medical device; and may further encompass one or more software program, product or platform, including any product(s), program(s) and/or platform(s) that incorporate any combination of hardware and software, that is/are directly therapeutically active in treating and/or targeting one or more neurological circuits related to one or more neurological, psychological and/or somatic conditions, diseases, and/or disorders, rather than just being a component of overall treatment.
As used in certain examples herein, the term “patient” encompasses a user being engaged with a software program, product or platform for a targeted medical or personal wellness purpose, indication, and/or intended use.
As used in certain examples herein, the term “stakeholder” encompasses a manufacturer of software program, product or platform; an administrative user of a software program, product or platform; and may further include one or more of a healthcare provider, researcher, investigator, reviewer, administrator, parent, custodian, guardian or other caregiver of a patient.
As used in certain examples herein, the terms “investigator,” “administrator,” or “researcher,” encompass a user or stakeholder being engaged with a software program, product or platform for the purpose of evaluating or developing one or more technical, clinical, and/or functional aspects of the software program, product or platform; and may further include a user or stakeholder being engaged with a software program, product or platform for the purpose of conducting a scientific evaluation, such as a clinical trial.
As will be appreciated by one of skill in the art, embodiments of the present disclosure may be embodied as a method (including, for example, a computer-implemented process, a business process, and/or any other process), apparatus (including, for example, a system, machine, device, computer program product, and/or the like), or a combination of the foregoing. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.), or an embodiment combining software and hardware aspects that may generally be referred to herein as a “system.” Furthermore, embodiments of the present invention may take the form of a computer program product on a computer-readable medium having computer-executable program code embodied in the medium.
All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present invention, exemplary methods and materials are now described. All publications mentioned herein are incorporated herein by reference to disclose and describe the methods and/or materials in connection with which the publications are cited.
Following below are more detailed descriptions of various concepts related to, and embodiments of, inventive methods, devices and systems for collecting, processing and analyzing a plurality of endpoint data to assess one or more functional, scientific, and/or clinical aspects of a DHI/SaMD program, platform or product. Certain embodiments provide for a platform to analyze user-generated data from a DHI/SaMD program, platform or product to determine one or more safety, efficacy, performance, and/or patient outcome metrics associated with one or more program code output and/or functional aspects of the DHI/SaMD. Certain embodiments further provide for a platform to design and facilitate the administration of a research study, clinical evaluation, and/or clinical trial for a DHI/SaMD program, platform or product. Certain embodiments further provide for a platform to continuously monitor and analyze a plurality of endpoint data to verify and improve safety, efficacy, and/or performance of a DHI/SaMD.
Certain embodiments provide for a system for configuring and administering a clinical trial for a DHI/SaMD program, platform or product. Such embodiments may comprise system and methods for the secured collection and analysis of data, and the secured sharing of content between disparate systems and platforms for the purpose of configuring and administering the clinical trial. The content can be, but is not limited to, the collected data and/or the results of the data analysis.
Certain embodiments of the present disclosure can be coupled with one or more types of measurement components, for receiving and analyzing data collected from at least one measurement of the one or more measurement components. As non-limiting examples, the measurement component can be a physiological component.
Certain embodiments of the present disclosure can be coupled with one or more types of cognitive platforms, for analyzing data collected from user interaction with the cognitive platform. As non-limiting examples, the cognitive platform and/or platform product can be configured for cognitive monitoring, cognitive assessment, cognitive screening, and/or cognitive treatment, including for clinical purposes. The data from the cognitive platform can be used by the exemplary systems, methods, and apparatus disclosed herein as symptom measurement data.
Certain embodiments of the present disclosure can be implemented to facilitate testing, monitoring and/or improved treatment of a variety of different conditions, such as but not limited to neuropsychological conditions, including dementia, Parkinson's disease, cerebral amyloid angiopathy, familial amyloid neuropathy, Huntington's disease, or other neurodegenerative condition, autism spectrum disorder (ASD), presence of the 16p11.2 duplication, and/or executive function disorders, including attention deficit hyperactivity disorder (ADHD), sensory-processing disorder (SPD), mild cognitive impairment (MCI), Alzheimer's disease, multiple-sclerosis, schizophrenia, major depressive disorder (MOD), or anxiety.
In a non-limiting example, certain embodiments of the present disclosure can be configured to facilitate testing, monitoring and/or improved treatment of ADHD. Symptoms of ADHD include inattentiveness, impulsivity and hyperactivity. Both children and adults can have ADHD, however, the symptoms can be exhibited beginning in childhood. ADHD can be considered a chronic disease in certain aspects. Once diagnosed, it is typically treated with medications and managed through behavioral therapies.
In an example, certain embodiments of the present disclosure can be configured to collect and analyze content that assist with monitoring progress and/or modifying the individual's treatment plan. In another example, certain embodiments of the present disclosure can be configured to assist in improving the results of a treatment using visualizations.
In another example, certain embodiments of the present disclosure can be configured as an application (“App”) for use by a user or stakeholder. The scientific evaluation platform in this example can be configured to provide secured, authenticated access for the collection of data. The clinical trials platform gives parent, custodian, guardian or other caregiver of the child the capability to control the level and type of access that another user can have to the platform, thereby facilitating the collection of data through a secured access (such as but not limited to a secured login).
In this non-limiting exemplary implementation, the scientific evaluation platform may be configured such that an individual (including a parent, custodian, or other caregiver of an individual) may download an aspect of it as an App and use the App to collect data about the individual (including the child) on a regular basis. The App provides reminders and encouragement to ensure consistent, long-term engagement by the individual (including a parent, custodian, or other caregiver of an individual). The App is configured to provide the primary user the capability to request behavior data from another designated user (such as but not limited to a teacher or other caregiver of the individual). The request may be sent through a secured invitation delivered via email or other means. As an example, when the other, secondary user receives the invitation, they access the secure link provided, provide the information requested to set up an account (such as but not limited to login credentials) to be accessed at intervals to enter data and other information in the measurement fields provided (such as but not limited to information on how the child is behaving in school or to quantify measures of the individual's symptoms).
In non-limiting examples of a scientific evaluation platform for use in ADHD, the type of behavior metrics that are quantified can be behavior metrics related frequency and quality of homework assignment completion, frequency and quality of performing chores, and the quality of getting along with the parents, custodians, guardians, or other individual acting on behalf of a child. The exemplary symptom metrics can be set using scores from other symptom trackers.
The scientific evaluation platform is configured to allow a primary user to work with a healthcare provider to determine the type of test, system, or device to be presented in the measurement fields of the clinical trials platform and quantified using the platform.
The exemplary scientific evaluation platform allows users (such as but not limited to parent, teacher, physicians, behavioral therapists, etc.), to provide quantifiable measures of a variety of symptoms, also captures data from actual treatments (such as but not limited to scores from a cognitive treatment and other treatment), analyzes the collected data, an generates an enhanced analysis report that presents the data and analysis results in a form of interpretable, meaningful metrics, which can be used to determine if treatment is progressing adequately or satisfactorily.
An enhanced analysis report can be used in consultation with a healthcare provider to evaluate the individual's response to the treatment, determine any modifications to be made to the treatment, the overall time period for implementation of the modifications to the treatment, etc., in order to derive a stable outcome or an improved outcome of the treatment for the individual. This can result in a better condition management (including disease management) outcome for the individual.
In any example herein, the scientific evaluation platform provides control settings such that the access level and permissions for a secondary user set by a primary user may be revoked or overruled. While the examples are described relative to behavior measures or symptom measures, other types of measures are also applicable to the scientific evaluation platform.
Turning now to the drawings,
In use, the processing system 100 is adapted to allow data or information to be stored in and/or retrieved from, via wired or wireless communication means, at least one database 116. The interface 112 may allow wired and/or wireless communication between the processing unit 102 and peripheral components that may serve a specialized purpose. In general, the processor 102 can receive instructions as input data 118 via input device 106 and can display processed results or other output to a user by utilizing output device 108. More than one input device 106 and/or output device 108 can be provided. It should be appreciated that the processing system 100 may be any form of terminal, server, specialized hardware, or the like.
It is to be appreciated that the processing system 100 may be a part of a networked communications system. Processing system 100 could connect to a network, for example the Internet or a WAN. Input data 118 and output data 120 could be communicated to other devices via the network. The transfer of information and/or data over the network can be achieved using wired communications means or wireless communications means. A server can facilitate the transfer of data between the network and one or more databases. A server and one or more databases provide an example of an information source.
Thus, the processing computing system environment 100 illustrated in
In the description that follows, certain embodiments may be described with reference to acts and symbolic representations of operations that are performed by one or more computing devices, such as the computing system 100 of
Embodiments of the present invention can be implemented with numerous other general-purpose or special-purpose computing devices, systems or configurations. Examples of well-known computing systems, environments, and configurations suitable for use in embodiment of the invention include, personal computers, handheld or laptop devices, personal digital assistants, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network, minicomputers, server computers, game server computers, web server computers, mainframe computers, and distributed computing environments that include any of the above systems or devices.
Various embodiments of the invention will be described herein in a general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types. In certain embodiments, distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network may also be employed. In distributed computing environments, program modules may be located in both local and remote computer storage media including memory storage devices.
With the general computing system environment 100 of
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In accordance with certain embodiments, manufacturer server 202 is operably engaged with a manufacturer database 204 to host and execute a server-side instance of a software product 228 comprising one or more digital health intervention (DHI) and/or software as a medical device (SaMD) product. Manufacturer server 202 may be operably engaged with manufacturer client 222 to control and/or configure one or more aspects of software product 228. Manufacturer client 222 may be communicably engaged with platform server 206 via communications network 212 to execute an instance of scientific evaluation application 216, which may optionally be configured to render a manufacturer user interface 242. In accordance with certain embodiments, a computing device 226 may be communicably engaged with manufacturer server 202 via communications network 212 to execute an instance 228′ of software product 228. In some embodiments, computing device 226 may comprise a smartphone or tablet computer having one or more sensors and a touchscreen interface. Instance 228′ may comprise a series of computerized stimuli or interactions (CSIs) comprising one or more user prompts being associated with a DHI/SaMD output. Software product 228 may be configured to receive and process/aggregate data from endpoints 244. Endpoints 244 may comprise one or more of biological/physiological measurement device 230 (e.g., an EEG machine, heartrate monitor, blood pressure cuff, continuous glucose monitoring (CGM) system, etc.), a mobile/wearable electronic device configured to measure one or more activity inputs and/or physiological measurements of a user (e.g., a smart watch or wearable activity monitor comprising one or more heart rate sensor, inertial or motion sensor, acoustic transducer, touch interface, and the like), and one or more external data sources 234 including, but not limited to, a laboratory information management system (LIMS) 236 and/or electronic medical record (EMR) system 238.
In accordance with certain aspects of the disclosure, system 200 is configured to enable scientific evaluation of software product 228. In certain embodiments, scientific evaluation engine 208 and scientific evaluation platform product 240 are operably configured with platform server 206 and platform database 210 to analyze one or more safety, efficacy, performance, and/or quality assurance aspects of the program code for software product 228. In further embodiments, scientific evaluation engine 208 and scientific evaluation platform product 240 are operably configured with platform server 206 and platform database 210 to enable configuration and administration of a distributed clinical trial for software product 228. In further embodiments, scientific evaluation engine 208 and scientific evaluation platform product 240 are operably configured with platform server 206 and platform database 210 to enable scientific evaluation of one or more outputs of software product 228 for one or more medical or clinical intended use.
In accordance with certain embodiments, scientific evaluation engine 208 is configured to process and analyze data from endpoints 244 according to one or more analytical frameworks. In certain embodiments, scientific evaluation engine 208 may process and analyze data from endpoints 244 according to one or more supervised or unsupervised, linear or non-linear, dimension reduction and/or data aggregation framework. Suitable dimension reduction and data aggregation frameworks include, without limitation: Principal Component Analysis (PCA), Multi-Dimension Scaling (MDS), Locally Linear Embedding (LLE), Independent Component Analysis, and Linear Discriminant Analysis. In certain embodiments, reducing dimensionality of input data comprises applying a PCA algorithm, resulting in output data that is orthogonal in the vector space. In certain embodiments, reducing dimensionality of input data comprises applying a Manifold Learning method to identify one or more non-linear structure(s) in the data. Manifold Learning methods are particularly useful for identifying high dimensional structures of raw input data from the data itself, without use of predetermined classifications.
In further embodiments, MDS is employed for projecting high dimensionality data into a lower dimensional surface. In such embodiments, observations include a similarity distance delta for input into the algorithm. Outcomes are provided as vectors of coordinates for each data point in a x-dimensional with the objective being to find representatives of K for a given input data set. The representatives of K are called “cluster centers” or “centroids,” and are selected so as to have a minimum distance from each data point to a centroid in the same.
In still further embodiments, a lower dimension projection of a selected data set is identified or located using LEE, which preserves distances (location) within local neighborhoods. Furthermore, dimensionality of labeled data can be achieved using supervised methods, such as Linear Discriminant Analysis and/or Neighborhood Component Analysis.
In accordance with certain embodiments, scientific evaluation engine 208 is further configured to clean some or all input data before processing the input data for analysis. Exemplary data cleaning techniques employed by scientific evaluation engine 208 may include, without limitation, imputation, capping, and flooring of the data. In accordance with certain embodiments, data cleaning by imputation may comprise the use of a decision tree. In one embodiment, one or more leaf node may comprise a class label with a majority of training examples reaching the leaf. In certain embodiments, each internal node represents a question on at least one feature of software product 228 that will be branching out according to each answer. Each answer generates a set of questions that aid to determine the data and decision-making based on it. The final result of decision tree indicates the possibility of all decision and outcome scenarios. In an alternative exemplary embodiment, K-nearest neighbor (KNN) may be employed for imputation of missing data. KNN defines a set of nearest neighbors of a sample and substitutes the missing data by calculating the average of non-missing values to its neighbors. Nearest neighbor is measured as the closest values based on the Euclidean distance.
In certain embodiments, a “Bayesian network” may be employed for data input in the compiling of a dataset. Specifically, compiling a dataset according to embodiments of the invention comprises employing one or more Bayesian network to apply additional independent constraints on variables so as to identify, in a concise manner, one or more probable relationship(s) between the variables. Using Bayesian networks for imputation offers several advantages, including the ability to handle missing data models encodes dependencies among all variables and the preservation of the joint probability distribution of the variables. A key element of the Bayesian approach is that missing data is incorporated as an added unknown quantity in estimating a posterior distribution, with the posterior distribution being defined as the total knowledge of integration between prior distribution and likelihood function to a parameter after its been observed. In certain embodiments, particularly in models sensitive to high data input values, data cleaning may comprise calculating the mean (variance) by a method of capping and flooring of the input dataset or observations at one or more specific percentiles (e.g., 1% or 99%).
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In accordance with certain embodiments, protocol design and review module 528 may comprise operations for configuring and executing one or more protocol design and review functions, including one or more functions for: trial/evaluation design; trial/evaluation methodology; selection and/or training of data model(s); user permissions and access/usage parameters; data segmentation and assessment of functional areas (e.g. safety, efficacy, performance, etc.); protocols for adverse event handling; quality control and assurance parameters; and data management and reporting parameters. Trial/application startup module 530 may comprise one or more operations for configuring and executing one or more trial/application startup functions, including one or more functions for: user onboarding (e.g. secure account creation, first time user experience, user instructions and messaging, and user consent(s)) and user demographic/information prompts; user reimbursement setup, including electronic linking of user bank account (for trials or evaluations in which a user is reimbursed for time and/or expenses); user authentication parameters and protocols; and data transfer interface and protocols, including endpoint selection and interface. User recruitment module 532 may comprise one or more operations for configuring and executing user recruitment functions, including one or more functions for: study support and study selection parameters; study signup workflow and parameters; study-specific consent terms and requirements. Operational data management module 536 may comprise operations for configuring and executing one or more operational data management functions, including one or more functions for: user assignment and segmentation; user notifications and communications; operational data processing and reporting; data security protocols and parameters; user activity and software usage parameters and notifications; administrative controls and access rights, including parameters for lack of use, revoking access, or removal/bricking of software or specific features; adverse event tracking and handling; and data transfer interface with third-party systems. Supply logistics module 538 may comprise one or more operations for configuring and executing one or more supply logistics functions, including one or more functions for: software product acquisition; parallel authentication/login framework; and additional application acquisition. User outcome data management module 540 may comprise one or more operations for configuring and executing user recruitment functions, including one or more functions for: data rendering and reporting; data collection parameters and data transfer protocols; selection and/or training of data model(s); data segmentation and cleaning; and data access and data query parameters.
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Routine 1000 may proceed by processing the operational data 1006 according to one or more data processing models, framework, and/or rules engine. Routine 1000 may proceed by executing one or more operational workflows 1008 in response to processing the operational data. In accordance with certain embodiments, the one or more operational workflows may comprise one or more user notification(s) 1016; adverse event tracking/handling 1018; operational data interface(s) 1020; and administrative controls and support 1022. Upon execution of one or more operational workflows in accordance to the data processing output, routine 1000 may continue by updating and storing the operational data in the platform database.
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It will be evident to persons skilled in the art that the above-described embodiments of the invention can be implemented in any of numerous ways. For example, some embodiments may be implemented using hardware, software or a combination thereof. When any aspect of an embodiment is implemented at least in part in software, the software code can be executed on any suitable processor or collection of processors, whether provided in a single computer or distributed among multiple computers.
Additionally, various aspects of the invention may be embodied at least in part as a computer readable storage medium (or multiple computer readable storage media) (e.g., a computer memory, compact disks, optical disks, magnetic tapes, flash memories, circuit configurations in Field Programmable Gate Arrays or other semiconductor devices, or other tangible computer storage medium or non-transitory medium) encoded with one or more programs that, when executed on one or more computers or other processors, perform methods that implement the various embodiments of the technology discussed above. The computer readable medium or media can be transportable, such that the program or programs stored thereon can be loaded onto one or more different computers or other processors to implement various aspects of the present technology as discussed above.
Although embodiments of the invention have been described with a certain degree of particularity, it is understood that the present disclosure is provided by way of example and that various changes to details of construction or arrangement of parts and even steps may be made without departing from the spirit or scope of the invention. The terms and expressions used herein have been employed as terms of description rather than terms of limitation, and their use is not intended as excluding equivalents of the features or steps described thereby.
The present application is a continuation of U.S. application Ser. No. 16/748,688 filed Jan. 21, 2020, the contents of which are hereby incorporated herein at least by virtue of this reference.
| Number | Date | Country | |
|---|---|---|---|
| Parent | 16748688 | Jan 2020 | US |
| Child | 17893099 | US |
