Methods and systems for the compilation, tracking, and use of informed consent data for human specimen research

Abstract

The subject matter described herein includes methods, systems, and computer program products for the compilation, tracking, and use of informed consent data for human specimen research. According to one method, an informed consent document is compiled and consent rules are attached to the specimen. The consent rules and any changes to the consent rules are tracked. A permitted use analysis is performed on the specimen and associated data, and a Regulatory Intelligence Knowledgebase (RIK) is provided, the RIK including global regulatory data derived from proprietary and public sources. An informed consent document is automatically generated using the compiled informed consent document and the RIK.

Description

[0001] This application is a divisional application of the patent application for invention titled "Method and System for Codification, Tracking, and Use of Informed Consent Data for Human Specimen Research" with the application date of November 18, 2016, application number 201680067417.7.

[0002] Cross - reference to related applications

[0003] This application claims the benefit of the priority of U.S. Provisional Patent Application No. 62 / 256,756, titled "A Method and System for Codification, Tracking, and Use of Informed Consent Data for Human Specimen Research", filed on November 18, 2015, which is incorporated herein by reference in its entirety. Technical field

[0004] The present invention relates to consent data for human specimen research, and more particularly to methods and systems for the codification, tracking, and use of informed consent data for human specimen research. Background art

[0005] Human specimen research is a key step towards precision medicine. The acquisition, analysis, and storage of specimens obtained from human subjects during the processes of clinical trials, research studies, patient registries, and institutional biobanks are enablers for finding new drugs and diagnostics. Specimens collected during clinical trials are highly annotated and provide a rich resource for trial results as well as future biomedical research (FBR).

[0006] Regulations govern the acquisition, use, analysis, and destruction of specimens and data in the form of informed consent. Patients and study subjects sign informed consent to allow the collection, storage, and use of data related to the specimens. Capturing and tracking informed consent related to specimens and data about specimens is key to regulatory compliance for trial activities and future biomedical research. The consequences of failing to properly track consent can be severe in terms of regulatory fines (in dollars), loss of organizational trust for using specimens or data without proper informed consent, and loss of the ability to use biological resources to drive future biomedical research.

[0007] Accordingly, there is a need to improve methods and systems for managing informed consent data for human specimen research. Summary of the invention

[0008] The subject matter described herein includes methods, systems, and computer program products for the compilation, tracking, and use of informed consent data for human specimen research. According to one embodiment of the present invention, a method for the compilation, tracking, and use of informed consent data for human specimen research may include: compiling an informed consent document by a server; attaching consent rules to a specimen by the server; tracking the consent rules and any changes to the consent rules by the server; performing an allowable use analysis of the specimen and associated data by the server; and automatically generating a consent document by the server using the compiled informed consent document and a Regulatory Intelligence Knowledgebase (RIK), where the RIK includes global regulatory data derived from proprietary and public sources.

[0009] According to some embodiments, compiling an informed consent document by a server may further include using machine learning to translate the informed consent document into a set of classes that encode the informed consent document into a machine-operable format or a set of rules that define what the patient has consented to do with the specimen and data.

[0010] According to some embodiments, compiling an informed consent document by a server may be linked to and enforced based on current global, national, regional, and local regulations in effect at the time of compilation.

[0011] According to some embodiments, attaching consent rules to a specimen by a server may include linking a consent profile to the specimen and the data derived from the specimen.

[0012] According to some embodiments, attaching consent rules to a specimen by a server may be performed on a patient, collection site, sample type, country, and region basis.

[0013] According to some embodiments, tracking consent rules by a server may further include dynamically tracking changes to the restrictions on what can be done with the specimen and / or whether the patient has withdrawn consent.

[0014] According to some embodiments, performing an allowable use analysis by a server may further include providing a rule-based query for a specific consent profile.

[0015] According to some embodiments, performing an allowable use analysis by a server may further include providing a risk assessment from the perspective of consent.

[0016] According to some embodiments, the RIK may be used to create a risk-based model for specimen and data collection.

[0017] According to some embodiments, the RIK also informs the risk-based model by learning about the actions of internal review boards (IRBs), ethics committees, health authorities, and other groups involved in consent approvals.

[0018] According to some embodiments, the behavior may include one or more of the following: performance, approved speed, interpretation of local and global regulations, level of prudence, and trends over time.

[0019] According to some embodiments, automatically generating a consent document by the server may further include generating the consent document based on a summary of the desired consent, consent categories required, and regulations.

[0020] According to some embodiments, a global consent landscape portal may provide a global consent landscape analysis.

[0021] According to some embodiments, the global consent landscape portal includes visual indicators along with filters, the visual indicators provide a quick visual risk assessment, wherein the visual risk indicators are overlaid on a map, and the filters allow for interactive visualization of different risk categories.

[0022] In still other embodiments of the present invention, a system for the compilation, tracking, and use of informed consent data for human specimen research may include: a Regulatory Intelligence Knowledgebase (RIK), wherein the RIK includes global regulation data derived from proprietary and public sources. The system may further include a server having a processor and a memory, the server being configured to: compile an informed consent document, attach consent rules to the specimen, track the consent rules and any changes to the consent rules, perform an analysis of the permitted use of the specimen and associated data, and automatically generate a consent document using the compiled informed consent document and the RIK.

[0023] In still other embodiments of the present invention, a computer program product for the compilation, tracking, and use of informed consent data for human specimen research may include: computer code for compiling an informed consent document, computer code for attaching consent rules to the specimen, computer code for tracking the consent rules and any changes to the consent rules, computer code for performing an analysis of the permitted use of the specimen and associated data, and computer code for automatically generating a consent document using the compiled informed consent document and a Regulatory Intelligence Knowledgebase (RIK), wherein the RIK includes global regulation data derived from proprietary and public sources. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a flowchart illustrating steps of an example consent compilation process for the compilation, tracking, and use of informed consent data for human specimen research according to an embodiment of the present invention.

[0025] Figure 2 is a flowchart illustrating steps of an example consent tracking process for the compilation, tracking, and use of informed consent data for human specimen research according to an embodiment of the present invention.

[0026] Figure 3 is a flowchart illustrating steps of an example process for the compilation, tracking, and use of informed consent data for human specimen research that permits the use of the analysis process.

[0027] Figure 4A and 4B is a description of an example global consent situation portal for the compilation, tracking, and use of informed consent data for human specimen research in accordance with an embodiment of the present invention.

[0028] Figure 5 is a block diagram illustrating example components and functions associated with a regulatory intelligence knowledge base for the compilation, tracking, and use of informed consent data for human specimen research in accordance with an embodiment of the present invention.

[0029] Figure 6 is a block diagram illustrating example components and functions associated with a machine-driven informed consent builder for the compilation, tracking, and use of informed consent data for human specimen research in accordance with an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The subject matter described herein includes systems and methods designed to manage the compilation, tracking, and use of informed consent data for human specimen research. Generally, pre-existing informed consent documents can be reverse engineered to generate new and more useful "compiled" informed consent documents. Such compiled informed consent documents can be machine-readable and machine-operable such that they can be stored and retrieved in an electronic database. When a patient provides a specimen, the system can create a consent profile for the patient that links various information to the specimen. Thereafter, it is easier to track the patient's consent and any changes (e.g., withdrawal of consent) to ensure that the organization manages the specimen and its associated data in accordance with applicable consent rules and regulations. Analysis can provide a quick assessment of risks or other metrics using an interactive visualization portal (such as a web page or interactive application) based on various granular searches. Finally, the system can be used to help automatically generate new consent documents based on desired specifications such that the consent documents can be assembled very quickly and in an automated manner by individuals without legal training.

[0031] Now refer to Figure 1, a flowchart showing the steps of an exemplary consent compilation process that illustrates an informed consent document according to an embodiment of the present invention. At step 100, an informed consent document can be received. The informed consent form or document can explain to the patient what permissions they can give regarding the use of specimens and data. Such a document is established during the study setup and reviewed and approved by an Institutional Review Board (IRB). The informed consent form can be written according to global and local (national) regulations as well as site-specific requirements.

[0032] At step 102, the meaning of the informed consent document can be translated or "reverse engineered" into a set of classes using a combination of expert evaluation, natural language processing, and machine learning. These classes can encode the informed consent document into a machine-operable format or a set of rules. The rules can then define what the patient has consented to regarding what can be done with their specimens and data. Compilation can be an early step in the process of tracking consent. The traditional method of simply linking the signed consent document to the specimen does not allow for automated assessment of consent and is thus cumbersome as they rely on humans to read and interpret the consent and take action.

[0033] At step 104, one or more consent categories can be determined. The compilation can be performed based on current global, national, regional, and local regulations and can thus be linked to the regulations in effect at the time of compilation. In this way, for example, specimens collected in 2005 according to the rules in effect that year can be used even if the regulations change in 2007 to restrict certain forms of analysis of those specimens.

[0034] At step 106, the consent rules can be written into a database. For example, the compiled informed consent document can be stored in an electronic database in one or more machine-readable formats for easier processing. The details of the database and its use will be described in more detail below.

[0035] At step 108, the consent compilation process can also include attaching the consent rules to the specimens. For example, the system can integrate the consent rules with the specimens and data based on the patient, collection site, sample type, country, and region. In this way, the patient's consent "profile" can be irreversibly linked to the specimen and the data derived from that specimen. Additionally, any derivatives of any type of the parent specimen can also be linked to the informed consent.

[0036] Now referring to Figure 2 , a flowchart showing the steps of an exemplary consent tracking process that illustrates the compilation, tracking, and use of informed consent data for human specimen research according to an embodiment of the present invention. The consent rules and any changes to those rules (e.g., changes to the restrictions on what can be done with the specimen, or whether the patient withdraws consent) can be tracked. Dynamic consent tracking can ensure that organizations using specimens and data always comply with the regulations.

[0037] At step 200, a permission to use query can be formulated, and at step 202, the query can be submitted to the database 204. For example, the query can include "What is the destruction date of the tissue specimen from patient X?"

[0038] At step 206, the permission to use can be analyzed based on the consent to use profile. For example, the consent to use profile can indicate that the tissue sample of patient X must be destroyed before December 2015, but can be used for FBR before that date.

[0039] At step 208, a permission for the user to report and risk assessment can be generated and provided.

[0040] Now refer to Figure 3 , which shows a flowchart of steps of an example permission to use analysis process for the compilation, tracking, and use of informed consent data for human specimen research according to an embodiment of the present invention. Some embodiments of the present invention can allow for the rapid determination of the permission to use of specimens and data and rule-based queries of specific consent profiles. For example, "tissue samples from Brazil that can be used for genomic analysis". The subject matter described herein can also provide a "risk assessment" from the perspective of consent when querying or browsing specimens and data during analysis, inventory searches, group creation, obtaining samples from third parties, and other interactions, where understanding the risk of permission to use is important.

[0041] At step 300, a patient consent profile can be created. The patient consent profile can indicate all the details regarding what the patient has consented to with respect to his or her specimens and associated data. Specimen collection and data collection can also be performed at step 300. This can include collecting tissue specimens, biographical or medical information, or similar items obtained from human subjects during, for example, the course of a clinical trial, a research study, patient enrollment, or diagnosis.

[0042] Additionally, at step 300, consent data is loaded, and at step 306, it is determined whether the consent profile has changed. If it has changed, then at step 308, the consent profile is updated. This can include updating the consent profile when the patient withdraws his or her consent, or vice versa, and adjusting any details regarding his or her consent (e.g., time, place, manner).

[0043] Now refer to Figure 4A and Figure 4B, shows a wireframe of an example global consent situation portal that illustrates the compilation, tracking, and use of informed consent data for human specimen research. Some embodiments of the present invention may provide global consent situation analysis, allowing organizations to quickly determine the risks of conducting trials, collecting specimens, and recruiting patients from a consent perspective. Visual indicators can provide a quick visual risk assessment. The global situation analysis can be presented in the form of a map along with filters, with risk indicators superimposed on the map, and the filters allowing for interactive visualization of different risk categories.

[0044] The global consent situation analysis can include links to other information about the consent situation, such as actual written consent regulations, and "intelligence about each location" to help inform the risk assessment derived from the Regulatory Intelligence Knowledgebase (RIK). For example, from Figure 4A As can be seen, the geographical map is shown with color-coded indicators for low risk, medium risk, and high risk. One or more risk filters can be adjusted by using the risk filter slider to provide lower and higher risk limits to be displayed on the map.

[0045] In Figure 4B , specific regulatory information can be linked in the form of a PDF file. For example, it can be used to display relevant regulatory intelligence linked in the database.

[0046] Now referring to Figure 5 , shows a block diagram that illustrates example components and functions associated with a regulatory intelligence knowledgebase for the compilation, tracking, and use of informed consent data for human specimen research according to embodiments of the present invention.

[0047] Some embodiments of the present invention may use data derived from multiple sources (proprietary and public) to build a knowledgebase of global regulations. For example, regulatory data 500, IRB actions 502, and internal consent data 504 can be processed at machine learning step 506. The RIK 508 can use machine learning 506 and statistical methods to provide regulatory intelligence to inform decision-making and predict risks, such as regarding an attempt to collect genomic samples in a region of Germany.

[0048] The RIK 508 can also be used in conjunction with analytics to create risk-based models for specimen and data collection. For example, these models can be used as decision support tools when writing and negotiating consent in different regions.

[0049] RIK 508 can also learn the actions of IRBs, ethics committees, health authorities, and other groups involved in consent approvals, further informing the risk-based model. For example, RIK 508 can inform risk model 510 and risk assessment 512, which in turn inform the global regulatory landscape 514. These actions include, but are not limited to, performance, speed of approval, interpretation of local and global regulations, whether overly cautious or restrictive, trends over time, and others.

[0050] Now referring to Figure 6 , a block diagram is shown that illustrates example components and functions associated with a machine-driven informed consent builder for the compilation, tracking, and use of informed consent data for human specimen research in accordance with an embodiment of the present invention. Some embodiments of the present invention may use RIK 606 and a compilation database to "forward engineer" a consent document based on a summary of the desired consent, consent categories required, regulations, and so on. Such a consent document can be assembled very quickly and in an automated manner by a person without legal training. The consent document constructed in this way benefits from a corpus of consent information assembled in RIK 606.

[0051] For example, a first consent criterion 600, a second consent criterion 602, and a third consent criterion 604 can be input into a regulatory intelligence database 606. RIK 606 can be used for the forward engineering process 608.

[0052] At step 610, a consent document is automatically generated based on a summary of the desired consent, consent categories required, and regulations.

[0053] As will be appreciated by those skilled in the art, aspects of the present invention may be embodied as a system, method, or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, microcode, etc.), or an embodiment combining software and hardware aspects, which may generally all be referred to herein as a "circuit," "module," or "system." Additionally, aspects of the present invention may take the form of a computer program product embodied in one or more computer-readable media having computer-readable program code embodied thereon.

[0054] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium (including but not limited to a non-transitory computer-readable storage medium). A computer-readable storage medium may be, for example but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer-readable storage medium may be any tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0055] A computer-readable signal medium may include a propagated data signal embodying computer-readable program code (e.g., in baseband or as part of a carrier wave). Such a propagated signal may take any of a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination thereof. A computer-readable signal medium may be any computer-readable medium that is not a computer-readable storage medium but that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0056] The program code embodied on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0057] The computer program code for performing the operations of aspects of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, Smalltalk, C++, etc., and conventional procedural programming languages such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0058] Aspects of the present invention will be described below with reference to the flowchart illustrations and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions executed via the processor of the computer or other programmable data processing apparatus create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0059] These computer program instructions can also be stored in a computer-readable medium that can direct a computer, other programmable data processing apparatus, or other devices to operate in a particular manner, such that the instructions stored in the computer-readable medium produce an article of manufacture including instructions that implement the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0060] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus, or other devices to produce a computer-implemented process, such that the instructions executed on the computer or other programmable apparatus provide a process for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0061] The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code including one or more executable instructions for implementing the specified (one or more) logical functions. It should also be noted that in some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustrations, and combinations of blocks in the block diagrams and / or flowchart illustrations, can be implemented by special purpose hardware-based systems that perform the specified functions or actions, or combinations of special purpose hardware and computer instructions.

[0062] The terms used herein are for the purpose of describing particular embodiments only and are not intended to limit the invention. As used herein, unless the context clearly dictates otherwise, the singular forms "a," "an," and "the" are intended to include the plural forms as well. It will be further understood that when the terms "comprises" and / or "comprising" are used in this specification, they specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or combinations thereof.

[0063] All structural, material, acts, and equivalents of the components or steps plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements specifically claimed. The description of the invention has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the invention. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.

[0064] The description of the various embodiments of the invention has been presented for purposes of illustration, but is not intended to be exhaustive or limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein were chosen to best explain the principles of the embodiments, practical application, or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method for the compilation, tracking, and use of informed consent data for human specimen research, comprising: compiling, by a server using machine learning, pre - existing informed consent documents into machine - operable rules, where the machine - operable rules define what a patient has consented to do with specimens and data derived from the specimens at multiple locations; storing the machine - operable rules in a non - transitory memory in the server; tracking, by the server, changes to the machine - operable rules; using, by the server, the machine - operable rules with any changes and a machine - learning regulatory intelligence knowledge base RIK, to automatically generate a new consent document at least in part based on global regulatory data derived from proprietary and public sources, where the machine - learning RIK includes the global regulatory data; and interactively displaying, using consent - approval analysis, visual risk indicators for collecting the specimens associated with the new consent document and filter sliders to provide lower and higher risk limits to be displayed and / or provide interactive visualizations of different risk categories.

2. The method according to claim 1, wherein the compilation is linked to and performed based on current global, national, regional, and local regulations in effect when generating a new consent document at at least one of the multiple locations.

3. The method according to claim 1, wherein tracking changes to the set of machine - operable rules includes dynamically tracking changes to the restrictions on what can be done with the specimens and / or whether the patient has withdrawn consent.

4. The method according to claim 3, wherein dynamically tracking changes to the restrictions includes providing a rule - based query for a specific consent profile.

5. The method according to claim 3, wherein dynamically tracking changes to the restrictions includes providing a risk assessment from the perspective of consent.

6. The method according to claim 1, wherein automatically generating a new consent document by the server includes generating the new consent document based on a summary of the desired consent, the categories of consent required, and the regulations in at least one of the multiple locations.

7. A system for the compilation, tracking, and use of informed consent data for human specimen research, comprising: a machine - learning regulatory intelligence knowledge base RIK, where the machine - learning RIK includes global regulatory data derived from proprietary and public sources; and a server having a processor and a non - transitory memory, configured to: compile, using machine learning, pre - existing informed consent documents into machine - operable rules, where the machine - operable rules define what a patient has consented to do with specimens and data derived from the specimens at multiple locations; store the machine - operable rules in the non - transitory memory; track changes to the machine - operable rules; use the set of machine - operable rules with any changes and the machine - learning RIK to automatically generate a new consent document at least in part based on global regulatory data derived from proprietary and public sources, where the machine - learning RIK includes the global regulatory data; and Use consent-approved analytics to interactively display visual risk indicators associated with a new consent document for collecting the specimen, as well as filter sliders to provide lower and higher risk limits to be displayed and / or provide an interactive visualization of different risk categories.

8. The system of claim 7, wherein the codification is linked to and enforced based on current global, national, regional, and local regulations in effect when generating a new consent document at at least one of the plurality of locations.

9. The system of claim 7, wherein tracking changes to the set of machine-operable rules includes dynamically tracking changes to restrictions on what can be done with the specimen and / or whether the patient has withdrawn consent.

10. The system of claim 9, wherein dynamically tracking changes to restrictions includes providing a rule-based query for a specific consent profile.

11. The system of claim 9, wherein dynamically tracking changes to restrictions includes providing a risk assessment from the perspective of consent.

12. The system of claim 7, wherein automatically generating a new consent document by the server includes generating the new consent document based on a summary of the desired consent, the consent categories required, and the regulations in at least one of the plurality of locations.

13. A non-transitory computer-readable storage medium having stored thereon a computer program, which when executed by a computer causes the computer to: Use machine learning to codify pre-existing informed consent documents into machine-operable rules, wherein the machine-operable rules define what the patient has consented to do with the specimen and data derived from the specimen at a plurality of locations; Store the machine-operable rules in a non-transitory memory in a server; Track changes to the machine-operable rules; Use the machine-operable rules with any changes and a machine learning regulatory intelligence knowledge base (RIK) to automatically generate a new consent document at least in part based on global regulation data derived from proprietary and public sources, wherein the machine learning RIK includes the global regulation data; And Use consent-approved analytics to interactively display visual risk indicators associated with the new consent document for collecting the specimen, as well as filter sliders to provide lower and higher risk limits to be displayed and / or provide an interactive visualization of different risk categories.

14. The non-transitory computer-readable storage medium of claim 13, wherein the codification is linked to and enforced based on current global, national, regional, and local regulations in effect when generating a new consent document at at least one of the plurality of locations.

15. The non-transitory computer-readable storage medium of claim 13, wherein tracking changes to the set of machine-operable rules includes dynamically tracking changes to restrictions on what can be done with the specimen and / or whether the patient has withdrawn consent.

16. The non-transitory computer-readable storage medium of claim 15, wherein dynamically tracking changes to restrictions includes providing a rule-based query for a specific consent profile.

17. The non-transitory computer-readable storage medium according to claim 15, wherein dynamically tracking the change of the restriction includes providing a risk assessment from the perspective of consent.

18. The non-transitory computer-readable storage medium according to claim 13, wherein automatically generating a new consent document by the server includes generating the new consent document based on a summary of the desired consent, the categories of consent required, and the regulations in at least one of the plurality of locations.

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