Methods, systems, and software program for validation and monitoring of pharmaceutical manufacturing processes

Information

  • Patent Grant
  • RE43527
  • Patent Number
    RE43,527
  • Date Filed
    Tuesday, November 25, 2008
    16 years ago
  • Date Issued
    Tuesday, July 17, 2012
    12 years ago
Abstract
Methods, systems, and software program for validation of pharmaceutical manufacturing processes and quality assurance process are described and disclosed herein. Consequently, the methods provide a means to perform validation on an integrated level whereby the quality control unit can ensure data and product integrity and minimize cost.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS

Not applicable.


STATEMENT OF RIGHTS TO INVENTIONS MADE UNDER FEDERALLY SPONSORED RESEARCH

Not applicable.


FIELD OF THE INVENTION

The invention described herein relates to methods, systems, and software program that are modified for use in software and hardware validation of pharmaceutical manufacturing processes. The invention further relates to the enhancement of quality assurance implementation protocols in current good manufacturing practice in manufacturing, processing, packing, and/or holding of drugs.


BACKGROUND OF THE INVENTION

Over the last two decades, significant changes in the environment of pharmaceutical regulation have occurred and have resulted in incremental adjustments in regulatory approaches to product quality. These changes included an increased number of pharmaceutical products and a greater role of medicines in health care, decreased frequency of manufacturing inspections as a result of fewer resources available for pharmaceutical manufacturing inspections, accumulation of experience with, “and lessons learned from”, various approaches to the regulation of product quality, advances in the pharmaceutical sciences and manufacturing technologies, application of biotechnology in drug discovery and manufacturing, advances in the science and management of quality and, globalization of the pharmaceutical industry. The cumulative impact of these changes has been greater than the sum of the parts and there is an industry wide need to develop integrated approaches to monitor and assess the validation of processes and overall quality of products provided to end users and patients.


Looking ahead the most up-to-date concepts of risk management and quality systems approaches should be incorporated while continuing to ensure product quality. The latest scientific advances in pharmaceutical manufacturing and technology are encouraged. Additionally, the submission review program and the inspection program should operate in a coordinated and synergistic manner and regulation and manufacturing standards should be applied consistently. The management of validation and quality assurance programs should encourage innovation in the pharmaceutical manufacturing sector in order to provide the most effective public health protection. Resource limitations prevent uniformly intensive coverage of all pharmaceutical products and production. Significant advances in the pharmaceutical sciences and in manufacturing technologies have occurred over the last two decades. While this knowledge has been incorporated in an ongoing manner into product quality regulation, the fundamental nature of the changes dictates a thorough evaluation of the science base to ensure that product quality assurance and validation not only incorporates up-to-date science, but also encourages further advances in technology. Integrated quality systems orientation principles from various innovative approaches to manufacturing quality that have been developed in the past decade should be evaluated for applicability and current Good Manufacturing Practices requirements and related pre-approval requirements should be evaluated according to applicable principles. In addition, interaction of the pre-market Chemistry, Manufacturing, and Controls review process and the application of current Good Manufacturing Practices requirements should be evaluated as an integrated system.


With the globalization of pharmaceutical manufacturing requires a global approach to integration keeping in mind the overall objective of strong public health protection. To accomplish these needed goals there is a need to carry out the following actions. The artisan should use emerging science and data analysis to enhance validation and quality assurance programs to target the highest risk areas. From the aforementioned, the evaluation of the feasibility of establishing dedicated and integrated cadres of pharmaceutical validation and quality assurance experts should become readily apparent to one of ordinary skill in the art. Also apparent to one of ordinary skill in the art is the ability to provide a cost-efficient network of validation and quality assurance protocols. By providing an integrated and user friendly approach to validation and quality assurance the overall benefit to the public at-large is pharmaceutical end products available at lower costs. This is turn will allow more persons or animals to benefit from innovations that occur in the treatment of disease. Additionally, there is also a need to use these modalities as research tools to monitor, assess, and further the state of the art in all areas of life science treatment and studies, specifically biotechnology and pharmaceuticals.


SUMMARY OF THE INVENTION

The invention provides for a software program that validates devices used in the manufacture, processing, and storing of drugs. As used herein, the term “drug” is synonymous with “pharmaceutical”. In certain embodiments, the program can be modified to conform to the programming language and operating system requirements of an individual system. In a further embodiment, the program is used to validate hardware use in drug manufacture. In another embodiment, the program is used to validate software used in drug manufacture. In another embodiment, the program is used to monitor quality assurance protocols put in place by the quality control unit.


The invention further provides methods for validating drug manufacture using the application software. In one embodiment, the method comprises installation during the concept phase of manufacturing. In another embodiment, the method comprises installation at which time the manufacture process is on-line. In another embodiment the method comprises installation during the course of quality assurance. In another embodiment, the method comprises monitoring the validation and quality assurance based on a routine maintenance schedule.


The invention further comprises a system which integrates application software and methods disclosed herein to provide a comprehensive validation and quality assurance protocol that is used by a plurality of end users whereby the data compiled from the system is analyzed and used to determine is quality assurance protocols and validation protocols are being achieved.





BRIEF DESCRIPTION OF THE FIGURES


FIG. 1. Schematic of analysis method.



FIG. 2. Flowchart of Standard Hazard Analysis and Mitigation.



FIG. 3. Schematic of failure analysis method.





DETAILED DESCRIPTION OF THE INVENTION

Outline of Sections


I.) Definitions


II.) Software Program


III.) Analysis


IV.) KITS/Articles of Manufacture


I.) Definitions:


Unless otherwise defined, all terms of art, notations and other scientific terms or terminology used herein are intended to have the meanings commonly understood by those of skill in the art to which this invention pertains unless the context clearly indicates otherwise. In some cases, terms with commonly understood meanings are defined herein for clarity and/or for ready reference, and the inclusion of such definitions herein should not necessarily be construed to represent a substantial difference over what is generally understood in the art. Many of the techniques and procedures described or referenced herein are well understood and commonly employed using conventional methodology by those skilled in the art, such as, for example, the widely utilized current Good Manufacturing Practice guidelines.


As used herein the terms “drug” and “pharmaceutical” include veterinary drugs and human drugs, including human biological drug products.


“abstraction” means the separation of the logical properties of data or function from its implementation in a computer program.


“access time” means the time interval between the instant at which a call for data is initiated and the instant at which the delivery of the data is completed.


“accuracy study processor” means a software tool used to perform calculations or determine accuracy of computer manipulated program variables.


“adaptive maintenance” means software maintenance performed to make a computer program usable in a changed environment.


“address” means a number, character, or group of characters which identifies a given device or a storage location which may contain a piece of data or a program step.


“algorithm” means any sequence of operations for performing a specific task.


“algorithm analysis” means a software verification and validation (“V&V”) task to ensure that the algorithms selected are correct, appropriate, and stable, and meet all accuracy, timing, and sizing requirements.


“alphanumeric” means pertaining to a character set that contains letters, digits, and usually other characters such as punctuation marks, etc.


“analog” means pertaining to data [signals] in the form of continuously variable [wave form] physical quantities; e.g., pressure, resistance, rotation, temperature, voltage.


“analog device” means a device that operates with variables represented by continuously measured quantities such as pressures, resistances, rotations, temperatures, and voltages.


“analog-to-digital converter” means input related devices which translate an input device's [sensor] analog signals to the corresponding digital signals needed by the computer.


“analysis” means a course of reasoning showing that a certain result is a consequence of assumed premises.


“application software” means software designed to fill specific needs of a user.


“bar code” means a code representing characters by sets of parallel bars of varying thickness and separation that are read optically by transverse scanning.


“BASIC” means an acronym for Beginners All-purpose Symbolic Instruction Code, a high-level programming language intended to facilitate learning to program in an interactive environment.


“basic input/output system” means firmware that activates peripheral devices in a PC. Includes routines for the keyboard, screen, disk, parallel port and serial port, and for internal services such as time and date. It accepts requests from the device drivers in the operating system as well from application programs. It also contains autostart functions that test the system on startup and prepare the computer for operation. It loads the operating system and passes control to it.


“batch processing” means execution of programs serially with no interactive processing.


“benchmark” means a standard against which measurements or comparisons can be made.


“bias” means a measure of how closely the mean value in a series of replicate measurements approaches the true value.


“block” means a string of records, words, or characters that for technical or logical purposes are treated as a unity.


“block check” means the part of the error control procedure that is used for determining that a block of data is structured according to given rules.


“block diagram” means a diagram of a system, instrument or computer, in which the principal parts are represented by suitably annotated geometrical figures to show both the basic functions of the parts and the functional relationships between them.


“blueprint” means an detailed plan or outline.


“boot” means to initialize a computer system by clearing memory and reloading the operating system. A distinction can be made between a warm boot and a cold boot. A cold boot means starting the system from a powered-down state. A warm boot means restarting the computer while it is powered-up. Important differences between the two procedures are; 1) a power-up self-test, in which various portions of the hardware [such as memory] are tested for proper operation, is performed during a cold boot while a warm boot does not normally perform such self-tests, and 2) a warm boot does not clear all memory.


“bootstrap” means a short computer program that is permanently resident or easily loaded into a computer and whose execution brings a larger program, such an operating system or its loader, into memory.


“boundary value” means a data value that corresponds to a minimum or maximum input, internal, or output value specified for a system or component.


“boundary value analysis” means a selection technique in which test data are chosen to lie along “boundaries” of the input domain [or output range] classes, data structures, procedure parameters, etc.


“branch analysis” means a test case identification technique which produces enough test cases such that each decision has a true and a false outcome at least once.


“calibration” means ensuring continuous adequate performance of sensing, measurement, and actuating equipment with regard to specified accuracy and precision requirements.


“certification” means technical evaluation, made as part of and in support of the accreditation process, that establishes the extent to which a particular computer system or network design and implementation meet a pre-specified set of requirements.


“change control” means the processes, authorities for, and procedures to be used for all changes that are made to the computerized system and/or the system's data. Change control is a vital subset of the Quality Assurance [QA] program within an establishment and should be clearly described in the establishment's SOPs.


“check summation” means a technique for error detection to ensure that data or program files have been accurately copied or transferred.


“compiler” means computer program that translates programs expressed in a high-level language into their machine language equivalents.


“computer system audit” means an examination of the procedures used in a computer system to evaluate their effectiveness and correctness and to recommend improvements.


“computer system security” means the protection of computer hardware and software from accidental or malicious access, use, modification, destruction, or disclosure.


“concept phase” means the initial phase of a software development project, in which user needs are described and evaluated through documentation.


“configurable, off-the-shelf software” means application software, sometimes general purpose, written for a variety of industries or users in a manner that permits users to modify the program to meet their individual needs.


“control flow analysis” means a software V&V task to ensure that the proposed control flow is free of problems, such as design or code elements that are unreachable or incorrect.


“controller” means hardware that controls peripheral devices such as a disk or display screen. It performs the physical data transfers between main memory and the peripheral device.


“conversational” means pertaining to a interactive system or mode of operation in which the interaction between the user and the system resembles a human dialog.


“coroutine” means a routine that begins execution at the point at which operation was last suspended, and that is not required to return control to the program or subprogram that called it.


“corrective maintenance” means maintenance performed to correct faults in hardware or software.


“critical control point” means a function or an area in a manufacturing process or procedure, the failure of which, or loss of control over, may have an adverse affect on the quality of the finished product and may result in an unacceptable health risk.


“data analysis” means evaluation of the description and intended use of each data item in the software design to ensure the structure and intended use will not result in a hazard. Data structures are assessed for data dependencies that circumvent isolation, partitioning, data aliasing, and fault containment issues affecting safety, and the control or mitigation of hazards.


“data integrity” means the degree to which a collection of data is complete, consistent, and accurate.


“data validation” means a process used to determine if data are inaccurate, incomplete, or unreasonable. The process may include format checks, completeness checks, check key tests, reasonableness checks and limit checks.


“design level” means the design decomposition of the software item; e.g., system, subsystem, program or module.


“design phase” means the period of time in the software life cycle during which the designs for architecture, software components, interfaces, and data are created, documented, and verified to satisfy requirements.


“diagnostic” means pertaining to the detection and isolation of faults or failures.


“different software system analysis” means Analysis of the allocation of software requirements to separate computer systems to reduce integration and interface errors related to safety. Performed when more than one software system is being integrated.


“dynamic analysis” means analysis that is performed by executing the program code.


“encapsulation” means a software development technique that consists of isolating a system function or a set of data and the operations on those data within a module and providing precise specifications for the module.


“end user” means a person, device, program, or computer system that uses an information system for the purpose of data processing in information exchange.


“error detection” means techniques used to identify errors in data transfers.


“error guessing” means the selection criterion is to pick values that seem likely to cause errors.


“error seeding” means the process of intentionally adding known faults to those already in a computer program for the purpose of monitoring the rate of detection and removal, and estimating the number of faults remaining in the program.


“failure analysis” means determining the exact nature and location of a program error in order to fix the error, to identify and fix other similar errors, and to initiate corrective action to prevent future occurrences of this type of error.


“Failure Modes and Effects Analysis” means a method of reliability analysis intended to identify failures, at the basic component level, which have significant consequences affecting the system performance in the application considered.


“FORTRAN” means an acronym for FORmula TRANslator, the first widely used high-level programming language. Intended primarily for use in solving technical problems in mathematics, engineering, and science.


“life cycle methodology” means the use of any one of several structured methods to plan, design, implement, test and operate a system from its conception to the termination of its use.


“logic analysis” means evaluates the safety-critical equations, algorithms, and control logic of the software design.


“low-level language” means the advantage of assembly language is that it provides bit-level control of the processor allowing tuning of the program for optimal speed and performance. For time critical operations, assembly language may be necessary in order to generate code which executes fast enough for the required operations.


“maintenance” means activities such as adjusting, cleaning, modifying, overhauling equipment to assure performance in accordance with requirements.


“modulate” means varying the characteristics of a wave in accordance with another wave or signal, usually to make user equipment signals compatible with communication facilities.


“Pascal” means a high-level programming language designed to encourage structured programming practices.


“path analysis” means analysis of a computer program to identify all possible paths through the program, to detect incomplete paths, or to discover portions of the program that are not on any path.


“quality assurance” means the planned systematic activities necessary to ensure that a component, module, or system conforms to established technical requirements.


“quality control” means the operational techniques and procedures used to achieve quality requirements.


“software engineering” means the application of a systematic, disciplined, quantifiable approach to the development, operation, and maintenance of software.


“software engineering environment” means the hardware, software, and firmware used to perform a software engineering effort.


“software hazard analysis” means the identification of safety-critical software, the classification and estimation of potential hazards, and identification of program path analysis to identify hazardous combinations of internal and environmental program conditions.


“software reliability” means the probability that software will not cause the failure of a system for a specified time under specified conditions.


“software review” means an evaluation of software elements to ascertain discrepancies from planned results and to recommend improvement.


“software safety change analysis” means analysis of the safety-critical design elements affected directly or indirectly by the change to show the change does not create a new hazard, does not impact on a previously resolved hazard, does not make a currently existing hazard more severe, and does not adversely affect any safety-critical software design element.


“software safety code analysis” means verification that the safety-critical portions of the design are correctly implemented in the code.


“software safety design analysis” means verification that the safety-critical portion of the software design correctly implements the safety-critical requirements and introduces no new hazards.


“software safety requirements analysis” means analysis evaluating software and interface requirements to identify errors and deficiencies that could contribute to a hazard.


“software safety test analysis” means analysis demonstrating that safety requirements have been correctly implemented and that the software functions safely within its specified environment.


“system administrator” means the person that is charged with the overall administration, and operation of a computer system. The System Administrator is normally an employee or a member of the establishment.


“system analysis” means a systematic investigation of a real or planned system to determine the functions of the system and how they relate to each other and to any other system.


“system design” means a process of defining the hardware and software architecture, components, modules, interfaces, and data for a system to satisfy specified requirements.


“top-down design” means pertaining to design methodology that starts with the highest level of abstraction and proceeds through progressively lower levels.


“traceability analysis” means the tracing of Software Requirements Specifications requirements to system requirements in concept documentation.


“validation” means establishing documented evidence which provides a high degree of assurance that a specific process will consistently produce a product meeting its predetermined specifications and quality attributes.


“validation, process” means establishing documented evidence which provides a high degree of assurance that a specific process will consistently produce a product meeting its predetermined specifications and quality characteristics.


“validation, prospective” means validation conducted prior to the distribution of either a new product, or product made under a revised manufacturing process, where the revisions may affect the product's characteristics.


“validation protocol” means a written plan stating how validation will be conducted, including test parameters, product characteristics, production equipment, and decision points on what constitutes acceptable test results.


“validation, retrospective” means validation of a process for a product already in distribution based upon accumulated production, testing and control data. Retrospective validation can also be useful to augment initial premarket prospective validation for new products or changed processes. Test data is useful only if the methods and results are adequately specific. Whenever test data are used to demonstrate conformance to specifications, it is important that the test methodology be qualified to assure that the test results are objective and accurate.


“validation, software” means, determination of the correctness of the final program or software produced from a development project with respect to the user needs and requirements. Validation is usually accomplished by verifying each stage of the software development life cycle.


“structured query language” means a language used to interrogate and process data in a relational database. Originally developed for IBM mainframes, there have been many implementations created for mini and micro computer database applications. SQL commands can be used to interactively work with a data base or can be embedded with a programming language to interface with a database.


“Batch” means a specific quantity of a drug or other material that is intended to have uniform character and quality, within specified limits, and is produced according to a single manufacturing order during the same cycle of manufacture.


“Component” means any ingredient intended for use in the manufacture of a drug product, including those that may not appear in such drug product.


“Drug product” means a finished dosage form, for example, tablet, capsule, solution, etc., that contains an active drug ingredient generally, but not necessarily, in association with inactive ingredients. The term also includes a finished dosage form that does not contain an active ingredient but is intended to be used as a placebo.


“Active ingredient” means any component that is intended to furnish pharmacological activity or other direct effect in the diagnosis, cure, mitigation, treatment, or prevention of disease, or to affect the structure or any function of the body of man or other animals. The term includes those components that may undergo chemical change in the manufacture of the drug product and be present in the drug product in a modified form intended to furnish the specified activity or effect.


“Inactive ingredient” means any component other than an active ingredient.


“In-process material” means any material fabricated, compounded, blended, or derived by chemical reaction that is produced for, and used in, the preparation of the drug product.


“Lot number, control number, or batch number” means any distinctive combination of letters, numbers, or symbols, or any combination thereof, from which the complete history of the manufacture, processing, packing, holding, and distribution of a batch or lot of drug product or other material can be determined.


“Quality control unit” means any person or organizational element designated by the firm to be responsible for the duties relating to quality control.


“Acceptance criteria” means the product specifications and acceptance/rejection criteria, such as acceptable quality level and unacceptable quality level, with an associated sampling plan, that are necessary for making a decision to accept or reject a lot or batch.


II.) Software Program (Computer Product)


The invention provides for a software program that is programmed in a high-level or low-level programming language, preferably a relational language such as structured query language which allows the program to interface with an already existing program or a database. Preferably, however, the program will be initiated in parallel with the manufacturing process or quality assurance (“QA”) protocol. This will allow the ability to monitor the manufacturing and QA process from its inception. However, in some instances the program can be bootstrapped into an already existing program that will allow monitoring from the time of execution (i.e. bootstrapped to configurable off-the-shelf software).


It will be readily apparent to one of skill in the art that the preferred embodiment will be a software program that can be easily modified to conform to numerous software-engineering environments. One of ordinary skill in the art will understand and will be enabled to utilize the advantages of the invention by designing the system with top-down design. The level of abstraction necessary to achieve the desired result will be a direct function of the level of complexity of the process that is being monitored. For example, the critical control point for monitoring an active ingredient versus an inactive ingredient may not be equivalent. Similarly, the critical control point for monitoring an in-process material may vary from component to component and often from batch to batch.


One of ordinary skill will appreciate that to maximize results the ability to amend the algorithm needed to conform to the validation and QA standards set forth by the quality control unit on each step during manufacture will be preferred. This differential approach to programming will provide the greatest level of data analysis leading to the highest standard of data integrity.


The preferred embodiments may be implemented as a method, system, or program using standard software programming and/or engineering techniques to produce software, firmware, hardware, or any combination thereof. The term “computer product” as used herein is intended to encompass one or more computer programs and data files accessible from one or more computer-readable devices, firmware, programmable logic, memory devices (e.g. EEPROM's, ROM's, PROM's, RAM's, SRAM's, etc.) hardware, electronic devices, a readable storage diskette, CD-ROM, a file server providing access to programs via a network transmission line, wireless transmission media, signals propagating through space, radio waves, infrared signals, etc. Those of skill in the art will recognize that many modifications may be made without departing from the scope of the present invention.


III.) Analysis


The invention provides for a method of analyzing data that is compiled as a result of the manufacturing of pharmaceuticals. Further the invention provides for the analysis of data that is compiled as a result of a QA program used to monitor the manufacture of drugs in order to maintain the highest level of data integrity. In one embodiment, the parameters of the data will be defined by the quality control unit. Generally, the quality control unit will provide endpoints that need to be achieved to conform to current Good Manufacturing Practices regulations or in some instances an internal endpoint-that is more restrictive to the minimum levels that need to be achieved.


In a preferred embodiment, the invention provides for data analysis using boundary value analysis. The boundary value will be set forth by the quality control unit. Using the boundary values set forth for a particular phase of manufacture the algorithm is defined. Once the algorithm is defined, an algorithm analysis (i.e. logic analysis) takes place. One of skill in the art will appreciate that a wide variety of tools are used to confirm algorithm analysis such as an accuracy study processor.


One of ordinary skill will appreciate that different types of data will require different types of analysis. In a further embodiment, the program provides a method of analyzing block data via a block check. If the block check renders an affirmative analysis, the benchmark has been met and the analysis continues to the next component. If the block check renders a negative the data is flagged via standard recognition files known in the art and a hazard analysis and hazard mitigation occurs.


In a further embodiment, the invention provides for data analysis using branch analysis. The test cases will be set forth by the quality control unit.


In a further embodiment, the invention provides for data analysis using control flow analysis. The control flow analysis will calibrate the design level set forth by the quality control unit which is generated in the design phase.


In a further embodiment, the invention provides for data analysis using failure analysis. The failure analysis is initiated using the failure benchmark set forth by the quality control unit and then using standard techniques to come to error detection. The preferred technique will be top-down. For example, error guessing based on quality control group parameters which are confirmed by error seeding.


In a further embodiment, the invention provides for data analysis using path analysis. The path analysis will be initiated after the design phase and will be used to confirm the design level. On of ordinary skill in the art will appreciate that the path analysis will be a dynamic analysis depending on the complexity of the program modification. For example, the path analysis on the output of an end product will be inherently more complex that the path analysis for the validation of an in-process material. However, one of ordinary skill will understand that the analysis is the same, but the parameters set forth by the quality control unit will differ.


The invention provides for a top-down design to software analysis. This preferred embodiment is advantageous because the parameters of analysis will be fixed for any given process and will be set forth by the quality control unit. Thus, performing software safety code analysis then software safety design analysis, then software safety requirements analysis, and then software safety test analysis will be preferred.


The aforementioned analysis methods are used for several non-limiting embodiments, including but not limited to, validating QA software, validating pharmaceutical manufacturing, and validating process designs wherein the integration of the system design will allow for more efficient determination of acceptance criteria in a batch, in-process material, batch number, control number, and lot number and allow for increased access time thus achieving a more efficient cost-saving manufacturing process.


IV.) Kits/Articles of Manufacture


For use in basic input/output systems, hardware calibrations, software calibrations, computer systems audits, computer system security certification, data validation, different software system analysis, quality control, and the manufacturing of drug products described herein, kits are within the scope of the invention. Such kits can comprise a carrier, package, or container that is compartmentalized to receive one or more containers such as boxes, shrink wrap, and the like, each of the container(s) comprising one of the separate elements to be used in the method, along with a program or insert comprising instructions for use, such as a use described herein.


The kit of the invention will typically comprise the container described above and one or more other containers associated therewith that comprise materials desirable from a commercial and user standpoint, programs listing contents and/or instructions for use, and package inserts with instructions for use.


A program can be present on or with the container. Directions and or other information can also be included on an insert(s) or program(s) which is included with or on the kit. The program can be on or associated with the container.


The terms “kit” and “article of manufacture” can be used as synonyms.


The article of manufacture typically comprises at least one container and at least one program. The containers can be formed from a variety of materials such as glass, metal or plastic.


EXAMPLES

Various aspects of the invention are further described and illustrated by way of the several examples that follow, none of which is intended to limit the scope of the invention.


Example 1
Implementation in Clinical Manufacturing Process

In one embodiment, the invention comprises the validation and quality control of drug products manufactured during the clinical phase of development. Generally, A phase I human clinical trial is initiated to assess the safety of doses of a drug product candidate in connection with the treatment of a disease. In the study, the safety of single doses when utilized as therapy is assessed. The trial design includes delivery of single doses of a drug product candidate escalating from approximately about 25 mg/m2 to about 275 mg/m2 over the course of the treatment in accordance with a pre-defined schedule (i.e. parameters defined by quality control unit).


Patients are closely followed for one-week following each administration of the drug product candidate. In particular, patients are assessed for safety concerns (i.e. toxicity, fever, shaking, chills, the development of an immunogenic response to the material.) Standard tests and follow-up are utilized to monitor each of these safety concerns. Patients are also assessed for clinical outcome and particularly treatment of the disease being evaluated.


The drug product candidate is demonstrated to be safe and efficacious, Phase II trials confirm the efficacy and refine optimum dosing.


The drug product candidate is safe in connection with the above-discussed trial, a Phase II human clinical trial confirms the efficacy and optimum dosing for monotherapy. Such trial is accomplished, and entails the same safety and outcome analyses, to the above-described trial with the exception being that patients do not receive other forms of treatment concurrently with the receipt of doses of the drug product candidate.


Once again, as the therapy discussed above is safe within the safety criteria discussed above, a Phase III human clinical trial is initiated.


As previously set forth, the acceptance criteria of all components used in the drug product manufacture for the purposes of the clinical trial are determined by the quality control unit. The analysis of the software and hardware occurs using any of the methods disclosed herein. (See for example FIG. 1 and FIG. 3). The program monitors and processes the data and stores the data using standard methods. The data is provided to an end user or a plurality of end users for assessing the quality of the batch. Furthermore, the data is stored for comparative analysis to previous batches to provide a risk-based assessment in case of failure. Using the historical analysis will provide a more streamlined manufacturing approach and will provide cost-saving over time. In addition, the invention comprises monitoring the data from initial process, monitoring the data at the end process, and monitoring the data from a routine maintenance schedule to ensure the system maintain data integrity and validation standard predetermined by the quality control unit.


Example 2
Implementation in Post-Clinical Commercial Manufacturing Process

Provided the drug product candidate has been awarded regulatory approval and is manufactured for commercial use. The invention comprises a method for monitoring the acceptance criteria of all components used in the drug product manufacture. The analysis of the software and hardware occurs using any of the methods disclosed herein. (See for example FIG. 1 and FIG. 3). The program monitors and processes the data and stores the data using methods known in the art. The data is provided to an end user or a plurality of end users for assessing the quality of the batch. Furthermore, the data is stored for comparative analysis to previous batches to provide a risk-based assessment in case of failure. Using the historical analysis will provide a more streamlined manufacturing approach and will provide cost-saving over time. In addition, the invention comprises monitoring the data from initial process, monitoring the data at the end process, and monitoring the data from a routine maintenance schedule to ensure the system maintain data integrity and validation standard predetermined by the quality control unit.


Example 3
Integration of Program into Manufacturing Hardware System

The invention comprises the integration of the computer product into a manufacturing hardware system. In this context, the term “hardware” means any physical device used in the pharmaceutical manufacturing process including, but not limited to, blenders, bio-reactors, capping machines, chromatography/separation systems, chilled water/circulating, glycol, coldrooms, clean steam, clean-in-place (CIP), compressed air, D.I./R.O. watersystems, dry heat sterilizers/ovens, fermentation equipment/bio reactors, freezers, filling equipment, filtration/purification, HVAC: environmental controls, incubators/environmentally controlled chambers, labelers, lyophilizers/freeze, dryers, mixing tanks, modular cleanrooms, neutralization systems, plant steam and condensate, process tanks/pressure, vessels, refrigerators, separation/purification equipment, specialty gas, systems, steam generators/pure steam systems, steam sterilizers, stopper washers, solvent recovery systems, tower water systems, waste inactivation systems/“kill” systems, vial inspection systems, vial washers, water for injection (WFI) systems, pure water systems, washers (glass, tank, carboys, etc.).


It will be understood by one of skill in the art that the computer product integrates the hardware via generally understood devices in the art (i.e. attached to the analog device via an analog to digital converter).


The computer product is integrated into the manufacturing system on a device by device basis. As previously set forth, the acceptance criteria of all devices used in the drug product manufacture for the purposes of the manufacturing process are determined by the quality control unit. The analysis of the software and hardware occurs using any of the methods disclosed herein. (See for example FIG. 1 and FIG. 3). The program monitors and processes the data and stores the data using standard methods. The data is provided to an end user or a plurality of end users for assessing the quality of data generated by the device. Furthermore, the data is stored for comparative analysis to previous batches to provide a risk-based assessment in case of failure. Using the historical analysis will provide a more streamlined manufacturing approach and will provide cost-saving over time. In addition, the invention comprises monitoring the data from initial process, monitoring the data at the end process, and monitoring the data from a routine maintenance schedule to ensure the system maintain data integrity and validation standard predetermined by the quality control unit.


Example 4
Integration of Program into Manufacturing Software System

The invention comprises the integration of the computer product into a manufacturing software system. In this context, the term “software” means any device used in the pharmaceutical manufacturing process including, but not limited to user-independent audit trails, time-stamped audit trails, data security, confidentiality systems, limited authorized system access, electronic signatures, bar codes, dedicated systems, add-on systems, control files, Internet, LAN's, etc.


The computer product is integrated into the manufacturing system on a device-by-device basis. As previously set forth, the acceptance criteria of all devices used in the drug product manufacture for the purposes of the manufacturing process to are determined by the quality control unit. The analysis of the software and hardware occurs using any of the methods disclosed herein. (See for example FIG. 1 and FIG. 3). The program monitors and processes the data and stores the data using standard methods. The data is provided to an end user or a plurality of end users for assessing the quality of data generated by the device. Furthermore, the data is stored for comparative analysis to previous batches to provide a risk-based assessment in case of failure. Using the historical analysis will provide a more streamlined manufacturing approach and will provide cost-saving over time. In addition, the invention comprises monitoring the data from initial process, monitoring the data at the end process, and monitoring the data from a routine maintenance schedule to ensure the system maintain data integrity and validation standard predetermined by the quality control unit.


Example 5
Integration of Program into Quality Assurance System

The invention comprises the integration of the computer product into a quality assurance system. In this context, the term “quality assurance” means the planned systematic activities necessary to ensure that a component, module, or system conforms to established technical requirements. A quality assurance system will compliment either of the systems set for in the examples entitled “Integration of program into manufacturing hardware system” or “Integration of program into manufacturing software system” to ensure data integrity and reliability from the data that is generated set forth in either of the examples entitled “Implementation in Clinical Manufacturing Process” or “Implementation in Post-Clinical Commercial Manufacturing Process”.


The computer product is integrated into the manufacturing system on a device-by-device basis. As previously set forth, the acceptance criteria of all devices used in the drug product manufacture for the purposes of the manufacturing process are determined by the quality control unit. The analysis of the software and hardware occurs using any of the methods disclosed herein. (See for example FIG. 1 and FIG. 3). The program monitors and processes the data and stores the data using standard methods. The data is provided to an end user or a plurality of end users for assessing the quality of data generated by the device. Furthermore, the data is stored for comparative analysis to previous batches to provide a risk-based assessment in case of failure. Using the historical analysis will provide a more streamlined manufacturing approach and will provide cost-saving over time. In addition, the invention comprises monitoring the data from initial process, monitoring the data at the end process, and monitoring the data from a routine maintenance schedule to ensure the system maintain data integrity and validation standard predetermined by the quality control unit.


Example 6
Integration of Program and Methods into a Comprehensive Cost-Saving System

The invention comprises a program and method integrated into a comprehensive cost-saving pharmaceutical manufacturing system. A user, preferably a system administrator, logs onto the system via secure means (i.e. password or other security measures known in the art) and inputs the boundary values for a particular component of the drug manufacturing process. The input is at the initial stage, the end product state, or any predetermined interval in between that has been established for routine maintenance by the quality control unit. The data is generated using any one of the various analysis methods described herein (as previously stated the type of analysis used is functional to the device or protocol being monitored or evaluated). Subsequent to the data analysis, any modifications or corrective action to the manufacturing process is implemented. The data is then stored by standard methods known in the art. Scheduled analysis of the stored data is maintained to provide a preventative maintenance of the manufacturing process. Over time, costs are reduced due to the tracking of data and analysis of troubled areas and frequency of hazards that occur on any given device in the manufacturing process. The system is implemented on every device which plays a role in drug manufacturing. The data compiled from every device is analyzed using the methods described herein.


The present invention is not to be limited in scope by the embodiments disclosed herein, which are intended as single illustrations of individual aspects of the invention, and any that are functionally equivalent are within the scope of the invention. Various modifications to the models and methods of the invention, in addition to those described herein, will become apparent to those skilled in the art from the foregoing description and teachings, and are similarly intended to fall within the scope of the invention. Such modifications or other embodiments can be practiced without departing from the true scope and spirit of the invention.

Claims
  • 1. A method for monitoring a pharmaceutical manufacturing process using at least a dry heat sterilizer, said method comprising: a) deriving an algorithm implemented in computer executable instructions that performs data analysis on said pharmaceutical manufacturing process using at least a dry heat sterilizer;b) performing “logic analysis” on said algorithm;c) performing “software safety code analysis” on said algorithm;d) performing “software safety design analysis” on said algorithm;e) performing “software safety requirements analysis” on said algorithm;f) performing “software safety test analysis” on said algorithm;g) integrating the said algorithm into a pharmaceutical manufacturing process whereby actual monitoring of the manufacturing process is attained.
  • 2. The method of claim 1, wherein the “data analysis” is selected from the group consisting of “boundary value analysis”, “block check”, “branch analysis”, “control flow analysis”, “failure analysis”, and “path analysis”.
  • 3. The method of claim 1, wherein the pharmaceutical manufacturing occurs in a clinical manufacturing process.
  • 4. The method of claim 1, wherein the pharmaceutical manufacturing occurs in a post-clinical commercial manufacturing process.
  • 5. A computer memory having computer executable instructions to perform the method according to claim 1.
  • 6. A kit comprising the computer memory having computer executable instructions of claim 5.
US Referenced Citations (333)
Number Name Date Kind
4443861 Slater Apr 1984 A
4558413 Schmidt et al. Dec 1985 A
4646229 Boyle Feb 1987 A
4687662 Schobel Aug 1987 A
4813013 Dunn Mar 1989 A
4852047 Lavallee et al. Jul 1989 A
4860204 Gendron et al. Aug 1989 A
4894511 Caledonia et al. Jan 1990 A
5006992 Skeirik Apr 1991 A
5029179 Harrison Jul 1991 A
5038138 Akiyama et al. Aug 1991 A
5041195 Taylor et al. Aug 1991 A
5041197 Gelb Aug 1991 A
5084144 Reddy et al. Jan 1992 A
5122717 Hayashi Jun 1992 A
5132193 Reddy et al. Jul 1992 A
5133842 Taylor et al. Jul 1992 A
5134560 Ferriter et al. Jul 1992 A
5191534 Orr et al. Mar 1993 A
5235605 Rines et al. Aug 1993 A
5235610 Finch et al. Aug 1993 A
5247693 Bristol Sep 1993 A
5278979 Foster et al. Jan 1994 A
5301336 Kodosky et al. Apr 1994 A
5315530 Gerhardt et al. May 1994 A
5325481 Hunt Jun 1994 A
5333265 Orimo et al. Jul 1994 A
5345457 Zenzie et al. Sep 1994 A
5358695 Helble et al. Oct 1994 A
5367624 Cooper Nov 1994 A
5377003 Lewis et al. Dec 1994 A
5392207 Wilson et al. Feb 1995 A
5447708 Helble et al. Sep 1995 A
5461477 Marinelli et al. Oct 1995 A
5528368 Lewis et al. Jun 1996 A
5532928 Stanczyk et al. Jul 1996 A
5548535 Zvonar Aug 1996 A
5552412 Cameron et al. Sep 1996 A
5556447 Srinivasachar et al. Sep 1996 A
5565073 Fraser et al. Oct 1996 A
5576946 Bender et al. Nov 1996 A
5586313 Schnittker et al. Dec 1996 A
5603894 Aikus et al. Feb 1997 A
5647968 Fraser et al. Jul 1997 A
5652911 Van Venrooy et al. Jul 1997 A
5664112 Sturgeon et al. Sep 1997 A
5712990 Henderson Jan 1998 A
5726984 Kubler et al. Mar 1998 A
5732397 DeTore et al. Mar 1998 A
5734026 Florin-Robertsson et al. Mar 1998 A
5734380 Adams et al. Mar 1998 A
5740190 Moulton Apr 1998 A
5767941 Ferguson Jun 1998 A
5774489 Moulton et al. Jun 1998 A
5774875 Medeiros et al. Jun 1998 A
5787000 Lilly et al. Jul 1998 A
5793013 Read et al. Aug 1998 A
5796403 Adams et al. Aug 1998 A
5831859 Medeiros et al. Nov 1998 A
5832449 Cunningham Nov 1998 A
5835922 Shima et al. Nov 1998 A
5847957 Cohen et al. Dec 1998 A
5860020 Van Venrooy et al. Jan 1999 A
5864483 Brichta Jan 1999 A
5892947 DeLong et al. Apr 1999 A
5901879 Duhaime et al. May 1999 A
5953688 Su et al. Sep 1999 A
5956938 Brandenburg Sep 1999 A
5970503 Eisenberg Oct 1999 A
5997155 Ducharme et al. Dec 1999 A
5997361 Driscoll et al. Dec 1999 A
6025769 Chu et al. Feb 2000 A
6034768 Fraser et al. Mar 2000 A
6049742 Milne et al. Apr 2000 A
6055507 Cunningham Apr 2000 A
6067549 Smalley et al. May 2000 A
6083281 Diec et al. Jul 2000 A
6106274 Ritchie et al. Aug 2000 A
6112130 Fukuda et al. Aug 2000 A
6122622 Wiitala et al. Sep 2000 A
6123964 Asgharnejad et al. Sep 2000 A
6141647 Meijer et al. Oct 2000 A
6169928 Olson et al. Jan 2001 B1
6215898 Woodfill et al. Apr 2001 B1
6223343 Hopwood et al. Apr 2001 B1
6226369 Lim et al. May 2001 B1
6235938 Hartwig et al. May 2001 B1
6243615 Neway et al. Jun 2001 B1
6256640 Smalley et al. Jul 2001 B1
6263438 Walker et al. Jul 2001 B1
6272506 Bell Aug 2001 B1
6279026 Clarke et al. Aug 2001 B1
6324522 Peterson et al. Nov 2001 B2
6347533 Tung Feb 2002 B1
6370422 Richards-Kortum et al. Apr 2002 B1
6385768 Ziebell May 2002 B1
6393458 Gigliotta et al. May 2002 B1
6397115 Basden May 2002 B1
6419953 Qiu et al. Jul 2002 B1
6441552 Brandenburg et al. Aug 2002 B1
6446136 Pohlmann et al. Sep 2002 B1
6456737 Woodfill et al. Sep 2002 B1
6470227 Rangachari et al. Oct 2002 B1
6483112 Lewis Nov 2002 B1
6501869 Athale Dec 2002 B1
6505085 Tuttle et al. Jan 2003 B1
6509145 Torrianni Jan 2003 B1
6567788 Johnson May 2003 B1
6581020 Buote et al. Jun 2003 B1
6606524 Byun et al. Aug 2003 B1
6631630 Pourboghrat et al. Oct 2003 B1
6645529 Gergely et al. Nov 2003 B2
6687558 Tuszynski Feb 2004 B2
6687887 Teig et al. Feb 2004 B1
6690464 Lewis et al. Feb 2004 B1
6691070 Williams et al. Feb 2004 B1
6692764 Katdare et al. Feb 2004 B2
6697783 Brinkman et al. Feb 2004 B1
6707122 Hines et al. Mar 2004 B1
6718291 Shapiro et al. Apr 2004 B1
6732019 Spool et al. May 2004 B2
6735748 Teig et al. May 2004 B1
6738450 Barford May 2004 B1
6776486 Steele et al. Aug 2004 B2
6778882 Spool et al. Aug 2004 B2
6816793 Chow et al. Nov 2004 B2
6850809 Callar et al. Feb 2005 B1
6852219 Hammond Feb 2005 B2
6857112 Teig et al. Feb 2005 B1
6862488 Mansour-Awad Mar 2005 B2
6865508 Ueki et al. Mar 2005 B2
6883148 Teig et al. Apr 2005 B1
6892366 Teig et al. May 2005 B1
6904370 Levinson et al. Jun 2005 B1
6907591 Teig et al. Jun 2005 B1
6944512 Breimesser et al. Sep 2005 B2
6944662 Devine et al. Sep 2005 B2
6965895 Smith et al. Nov 2005 B2
6966235 Paton Nov 2005 B1
6968292 Boyer Nov 2005 B2
6977385 Struye et al. Dec 2005 B2
6979578 Venugopal Dec 2005 B2
6980852 Jersey-Willuhn et al. Dec 2005 B2
7006882 Chang et al. Feb 2006 B2
7020876 Deitz et al. Mar 2006 B1
7027883 Shen Apr 2006 B2
7031784 Lai et al. Apr 2006 B1
7033023 Steele et al. Apr 2006 B2
7050875 Cribbs et al. May 2006 B2
7051293 Teig et al. May 2006 B1
7069101 Arackaparambil et al. Jun 2006 B1
7079912 Stack et al. Jul 2006 B2
7089072 Chia Aug 2006 B2
7103524 Teig et al. Sep 2006 B1
7112351 Affinito Sep 2006 B2
7113845 Behm et al. Sep 2006 B1
7123974 Hamilton Oct 2006 B1
7127330 Spool et al. Oct 2006 B2
7133727 Van Dyk et al. Nov 2006 B2
7162534 Schleiss et al. Jan 2007 B2
7169107 Jersey-Willuhn et al. Jan 2007 B2
7174230 Arackaparambil et al. Feb 2007 B2
7174353 Friske et al. Feb 2007 B2
7184820 Jersey-Willuhn et al. Feb 2007 B2
7184964 Wang Feb 2007 B2
7187992 Tuszynski Mar 2007 B2
7197405 Pruett et al. Mar 2007 B1
7207505 Bender et al. Apr 2007 B2
7216007 Johnson May 2007 B2
7216084 Brinkman et al. May 2007 B2
7231398 Schlereth et al. Jun 2007 B2
7233830 Callaghan et al. Jun 2007 B1
7240119 Ascoli et al. Jul 2007 B2
7249356 Wilson et al. Jul 2007 B1
7257501 Zhan et al. Aug 2007 B2
7269640 Huntley, Jr. et al. Sep 2007 B2
7280893 Spool et al. Oct 2007 B2
7299102 Ouchi Nov 2007 B2
7302307 Anderson et al. Nov 2007 B1
7305278 Enright et al. Dec 2007 B2
7317959 Pfander et al. Jan 2008 B2
7322048 Nortung Jan 2008 B2
7343605 Langkafel et al. Mar 2008 B2
7347613 Ditzig et al. Mar 2008 B2
7359760 Kishi et al. Apr 2008 B2
7367242 Xi et al. May 2008 B2
20010042068 Yoshida et al. Nov 2001 A1
20010054032 Goldman et al. Dec 2001 A1
20020011852 Mandelis et al. Jan 2002 A1
20020015176 Takao et al. Feb 2002 A1
20020042762 McQuade et al. Apr 2002 A1
20020044128 Hayashi et al. Apr 2002 A1
20020046290 Andersson et al. Apr 2002 A1
20020113151 Forber Jones et al. Aug 2002 A1
20020116083 Schulze Aug 2002 A1
20020128886 Wang Sep 2002 A1
20020138510 Tan Sep 2002 A1
20020147569 Lay et al. Oct 2002 A1
20020156548 Arackaparambil et al. Oct 2002 A1
20020165806 Kataria et al. Nov 2002 A1
20020187137 Bates et al. Dec 2002 A1
20020198964 Fukazawa et al. Dec 2002 A1
20030018400 Tuttle et al. Jan 2003 A1
20030040844 Spool et al. Feb 2003 A1
20030040845 Spool et al. Feb 2003 A1
20030041016 Spool et al. Feb 2003 A1
20030041017 Spool et al. Feb 2003 A1
20030041037 Spool et al. Feb 2003 A1
20030041038 Spool et al. Feb 2003 A1
20030041039 Spool et al. Feb 2003 A1
20030046252 Spool et al. Mar 2003 A1
20030069795 Boyd et al. Apr 2003 A1
20030069894 Cotter et al. Apr 2003 A1
20030074223 Hickle Apr 2003 A1
20030125904 Ueki et al. Jul 2003 A1
20030139939 Spool et al. Jul 2003 A1
20030149501 Tuszynski Aug 2003 A1
20030149608 Kall et al. Aug 2003 A1
20030149717 Heinzman Aug 2003 A1
20030150909 Markham et al. Aug 2003 A1
20030154144 Pokorny et al. Aug 2003 A1
20030172371 Offenmuller Sep 2003 A1
20030176981 Chow et al. Sep 2003 A1
20030180957 Koopmann et al. Sep 2003 A1
20030183777 Struye et al. Oct 2003 A1
20030200130 Kall et al. Oct 2003 A1
20030207795 Pilon et al. Nov 2003 A1
20030216630 Jersey-Willuhn et al. Nov 2003 A1
20030216662 Jersey-Willuhn et al. Nov 2003 A1
20030216663 Jersey-Willuhn et al. Nov 2003 A1
20030223033 Steele et al. Dec 2003 A1
20030225124 Spireas Dec 2003 A1
20040006486 Schmidt et al. Jan 2004 A1
20040011288 Affinito Jan 2004 A1
20040015521 Hudicka Jan 2004 A1
20040032592 Venugopal et al. Feb 2004 A1
20040032593 Venugopal Feb 2004 A1
20040034543 Bartsch Feb 2004 A1
20040068454 Jacobus et al. Apr 2004 A1
20040068455 Jacobus et al. Apr 2004 A1
20040077075 Jensen et al. Apr 2004 A1
20040078732 Meaney Apr 2004 A1
20040107415 Melamed et al. Jun 2004 A1
20040117126 Fetterman et al. Jun 2004 A1
20040123864 Hickey et al. Jul 2004 A1
20040153171 Brandt et al. Aug 2004 A1
20040158475 Juzeszyn et al. Aug 2004 A1
20040167648 Tuszynski Aug 2004 A1
20040177055 Heidemann et al. Sep 2004 A1
20040186648 Zheng et al. Sep 2004 A1
20040204972 Anant et al. Oct 2004 A1
20040205406 Kaliappan et al. Oct 2004 A1
20040243260 Law et al. Dec 2004 A1
20050012895 Steele et al. Jan 2005 A1
20050015166 Kataria et al. Jan 2005 A1
20050015741 Langkafel et al. Jan 2005 A1
20050033468 Pate et al. Feb 2005 A1
20050033977 Zurita et al. Feb 2005 A1
20050038565 Power et al. Feb 2005 A1
20050055110 Tuszynski Mar 2005 A1
20050065818 Brinkman et al. Mar 2005 A1
20050106355 Kohlman et al. May 2005 A1
20050107895 Pistikopoulos et al. May 2005 A1
20050137735 Loy et al. Jun 2005 A1
20050197786 Kataria et al. Sep 2005 A1
20050251276 Shen Nov 2005 A1
20050267611 Ishigaki Dec 2005 A1
20050278052 Bett et al. Dec 2005 A1
20050288979 Guest Dec 2005 A1
20060000470 Clarke et al. Jan 2006 A1
20060002986 Clarke et al. Jan 2006 A1
20060010426 Lewis et al. Jan 2006 A1
20060013473 Woodfill et al. Jan 2006 A1
20060015536 Buchanan et al. Jan 2006 A1
20060016830 Clarke et al. Jan 2006 A1
20060017916 Clarke et al. Jan 2006 A1
20060020578 Hood Jan 2006 A1
20060026193 Hood Feb 2006 A1
20060035395 Venugopal Feb 2006 A1
20060047453 Reeve et al. Mar 2006 A1
20060047705 Reade et al. Mar 2006 A1
20060056732 Holmes Mar 2006 A1
20060064182 Ford, Jr. et al. Mar 2006 A1
20060070014 Liu et al. Mar 2006 A1
20060074522 Liang et al. Apr 2006 A1
20060074917 Chand et al. Apr 2006 A1
20060089739 Sherriff et al. Apr 2006 A1
20060095545 Dreyer et al. May 2006 A1
20060100786 Choi May 2006 A1
20060124443 Tuschel et al. Jun 2006 A1
20060129259 Tornquist et al. Jun 2006 A1
20060129265 Ouchi Jun 2006 A1
20060149407 Markham et al. Jul 2006 A1
20060155410 Yamartino Jul 2006 A1
20060167579 Fujii et al. Jul 2006 A1
20060184264 Willis et al. Aug 2006 A1
20060199260 Zhang et al. Sep 2006 A1
20060206368 Bamberger et al. Sep 2006 A1
20060208191 Kessler et al. Sep 2006 A1
20060214948 Murthy Sep 2006 A1
20060239116 Ditzig et al. Oct 2006 A1
20060259500 Hood et al. Nov 2006 A1
20060267852 Ahn et al. Nov 2006 A1
20060282223 Lewis et al. Dec 2006 A1
20070005307 Sato Jan 2007 A1
20070011227 Johnson Jan 2007 A1
20070011415 Kaakani et al. Jan 2007 A1
20070011660 Garyali et al. Jan 2007 A1
20070016542 Rosauer et al. Jan 2007 A1
20070037570 Donovan et al. Feb 2007 A1
20070049267 Kota et al. Mar 2007 A1
20070050070 Strain et al. Mar 2007 A1
20070061166 Ramasubramanian et al. Mar 2007 A1
20070067458 Chand Mar 2007 A1
20070088534 MacArthur et al. Apr 2007 A1
20070100471 Kumar et al. May 2007 A1
20070100472 Johnson et al. May 2007 A1
20070100894 Manninen et al. May 2007 A1
20070101091 Kaakani et al. May 2007 A1
20070104949 Bunge May 2007 A1
20070112442 Zhan et al. May 2007 A1
20070112531 Zhan et al. May 2007 A1
20070113051 Salpakari May 2007 A1
20070136667 Gerhart et al. Jun 2007 A1
20070142941 McGreevy et al. Jun 2007 A1
20070144240 Andle Jun 2007 A1
20070149586 Giordani et al. Jun 2007 A1
20070200781 Ahn et al. Aug 2007 A1
20070214520 Scheibel et al. Sep 2007 A1
20070239367 Odegard et al. Oct 2007 A1
20080009959 Enright et al. Jan 2008 A1
20080066019 Worek et al. Mar 2008 A1
20080077617 Schulz et al. Mar 2008 A1
Foreign Referenced Citations (33)
Number Date Country
0696001 Feb 1996 EP
0700680 Nov 1999 EP
0999506 May 2000 EP
0999506 Oct 2000 EP
1117007 Jul 2001 EP
1136951 Sep 2001 EP
0593114 Feb 2002 EP
1349177 Oct 2003 EP
0503521 Nov 2005 EP
1481294 Oct 2006 EP
1714695 Oct 2006 EP
1830386 May 2007 EP
1798814 Jun 2007 EP
WO 9716434 May 1997 WO
WO 0115705 Mar 2001 WO
WO 0216924 Feb 2002 WO
WO 02087546 Nov 2002 WO
WO 03058533 Jul 2003 WO
WO03063680 Aug 2003 WO
WO2004059531 Jul 2004 WO
WO 2004072868 Aug 2004 WO
WO2004107087 Dec 2004 WO
WO 2005038821 Apr 2005 WO
WO2005114138 Dec 2005 WO
WO2006017808 Feb 2006 WO
WO 2006069797 Jul 2006 WO
WO2006071808 Jul 2006 WO
WO 2006071808 Jul 2006 WO
WO2006113450 Oct 2006 WO
WO 2007017552 Feb 2007 WO
WO2007017738 Feb 2007 WO
WO 2007050013 May 2007 WO
WO2007064624 Jun 2007 WO
Reissues (1)
Number Date Country
Parent 10840732 May 2004 US
Child 12313804 US