Method and system for organizing, tracking, and using informed consent data for human specimen research

Abstract

To provide methods and systems for organizing, tracking, and using informed consent data for human specimen research.SOLUTION: The subject matter described herein includes methods, systems, and computer program products for the organization, tracking, and use of informed consent data for human specimen research. According to one method, the informed consent document is structured and consent rules are attached to the specimen. The agreement terms and any changes to the agreement terms are tracked. An authorized use analysis of the specimens and associated data is performed and a regulatory information knowledge base (RIK) is provided that includes global regulatory data derived from private and public sources. The consent form is automatically generated using the codified informed consent document and the RIK.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] (CROSS-REFERENCE TO RELATED APPLICATIONS) This application claims the benefit of priority to U.S. Provisional Patent Application No. 62 / 256,756, entitled "A Method and System for Codification, Tracking, and Use of Informed Consent Data For Human Specimen Research," filed November 18, 2015, which is hereby incorporated by reference in its entirety.

[0002] (background) (Technical field) The present invention relates to consent data for human specimen research, and more particularly to methods and systems for organizing, tracking, and using informed consent data for human specimen research. [Background technology]

[0003] Description of Related Art Human specimen research is a critical step on the pathway to precision medicine. The acquisition, analysis, and storage of specimens obtained from human subjects during clinical trials, research studies, patient registries, and institutionalized biobanks are enablers of the search for new drugs and diagnostics. Specimens collected during the course of clinical trials are highly annotated and provide a rich resource for both study outcomes and prospective biomedical research (FBR).

[0004] Regulations in the form of informed consent govern the acquisition, use, analysis, and destruction of specimens and data. Patients and research subjects sign informed consent, allowing for the collection, storage, and use of data associated with their specimens. Obtaining informed consent and its tracking associated with specimens and data about specimens is critical to regulatory compliance for both testing activities and future biomedical research. The consequences of failing to properly track consent can be severe in terms of regulatory fines (monetary), loss of goodwill for organizations that use specimens or data without proper knowledge of consent, and loss of ability to conduct future biomedical research using biological resources. Summary of the Invention [Problem to be solved by the invention]

[0005] Therefore, there is a need for improved methods and systems for managing informed consent data for human specimen research. [Means for solving the problem]

[0006] (Brief summary of the invention) The subject matter described herein includes methods, systems, and computer program products for organizing, tracking, and using informed consent data for human specimen research. According to one embodiment of the present invention, a method for organizing, tracking, and using informed consent data for human specimen research may include organizing, by a server, an informed consent document; attaching, by the server, consent terms to the specimen; tracking, by the server, the consent terms and any changes to the consent terms; performing, by the server, a permitted use analysis of the specimen and associated data; and automatically generating, by the server, the organized informed consent document and consent form using a Regulatory Information Knowledgebase (RIK), where the RIK includes global regulatory data derived from private and public sources.

[0007] According to some embodiments, codifying the informed consent document by the server may further include using machine learning to convert the informed consent document into a set of classes, where the classes encode the informed consent document into a machine-actionable format or set of rules, and the rules define what is to be done with the specimen and data to which the patient consented.

[0008] According to some embodiments, the codification of the informed consent document by the server may be linked to and based on universal global, national, regional, and local regulations in effect at the time of codification.

[0009] According to some embodiments, attaching the consent terms to the specimen by the server may include linking a consent profile to the specimen and data derived from the specimen.

[0010] According to some embodiments, the server may attach consent terms to specimens on a patient, collection facility, sample type, country, and region basis.

[0011] According to some embodiments, tracking the consent terms by the server may further include dynamically tracking changes in restrictions on what may be done to the specimen and / or whether the patient has revoked their consent.

[0012] According to some embodiments, performing the permitted use analysis by the server may further include providing a rules-based query for specific consent profiles.

[0013] According to some embodiments, performing the permitted use analysis by the server may further include providing a risk assessment from a consent perspective.

[0014] According to some embodiments, RIK may be used to create risk-based models for specimen and data collection.

[0015] In some embodiments, RIK may further inform its risk-based model by learning from the behavior of internal review boards (IRBs), ethics committees, health authorities, and other organizations involved in consent approval.

[0016] According to some embodiments, behavior may include one or more of implementation, speed of approval, interpretation of local and global regulations, level of vigilance, and trends over time.

[0017] According to some embodiments, automatically generating the consent form by the server may further include generating the consent form based on a desired consent summary, required consent categories, and regulations.

[0018] According to some embodiments, a global consent landscape portal may provide a global consent landscape analysis.

[0019] According to some embodiments, the global consensus landscape portal may include visual indicators that provide a fast visual assessment or risk, which, along with filters, are overlaid on a map to allow interactive visualization of different risk categories.

[0020] According to yet another embodiment of the present invention, a system for organizing, tracking, and using informed consent data for human specimen research may comprise a Regulatory Information Knowledge Base (RIK), where the RIK contains global regulatory data derived from private and public sources. The system may further comprise a server with a processor and memory configured to organize informed consent documents, attach consent terms to specimens, track the consent terms and any changes to the consent terms, perform permitted use analysis of the specimens and associated data, and automatically generate consent documents using the organized informed consent documents and the RIK.

[0021] According to yet another embodiment of the present invention, a computer program product for organizing, tracking, and using informed consent data for human specimen research may comprise computer code for organizing informed consent documents; computer code for attaching consent terms to specimens; computer code for tracking the consent terms and any changes to the consent terms; computer code for performing permitted use analysis of the specimens and associated data; and computer code for automatically generating consent documents using the organized informed consent documents and a Regulatory Information Knowledge Base (RIK), the RIK including global regulatory data derived from private and public sources. The present specification also provides, for example, the following items: (Item 1) 1. A method comprising: organizing, by a server, an informed consent document; attaching, by the server, consent terms to the specimen; tracking, by said server, said agreement terms and any changes thereto; performing, by said server, a permitted use analysis of said sample and associated data; automatically generating, by a server, a consent document based on the structured information and a regulatory information knowledge base (RIK), the RIK including global regulatory data derived from private and public sources; A method comprising: (Item 2) 10. The method of claim 1, wherein codifying, by the server, the informed consent document comprises using machine learning to convert the informed consent document into a set of classes, the classes encoding the informed consent document into a machine-actionable format or set of conventions, the conventions defining what will be done with the specimen and the data to which the patient consented. (Item 3) 10. The method of claim 1, wherein the codification of the informed consent document by the server is linked to and is based on universal global, national, regional, and local regulations in effect at the time of codification. (Item 4) Item 10. The method of item 1, wherein attaching the consent terms to the specimen by the server includes linking a consent profile to the specimen and data derived from the specimen. (Item 5) 2. The method of item 1, wherein attaching consent terms to specimens by the server is performed on a patient, collection facility, sample type, country, and region basis. (Item 6) 10. The method of claim 1, wherein tracking the consent terms by the server includes dynamically tracking changes in restrictions on what can be done to the specimen and / or whether the patient has revoked their consent. (Item 7) 2. The method of claim 1, wherein performing the permitted use analysis by the server includes providing a terms-based query for specific consent profiles. (Item 8) 2. The method of claim 1, wherein performing, by the server, the authorized use analysis includes providing a risk assessment from a consent perspective. (Item 9) 2. The method of claim 1, wherein the RIK is used to create a risk-based model for specimen and data collection. (Item 10) 10. The method of claim 1, wherein the RIK further informs the risk-based model by learning from the behavior of internal review boards (IRBs), ethics committees, health authorities, and other organizations involved in consent approval. (Item 11) 11. The method of claim 10, wherein the behavior includes one or more of implementation, speed of approval, interpretation of local and global regulations, level of vigilance, and trends over time. (Item 12) 2. The method of claim 1, wherein automatically generating the consent form by the server includes generating the consent form based on a desired consent summary, required consent categories, and regulations. (Item 13) Item 1, wherein the global consent landscape portal provides global consent landscape analysis. (Item 14) Item 14. The method of item 13, wherein the global consensus landscape portal includes visual indicators that provide a fast visual assessment of risk, the visual indicators of risk being overlaid on a map together with filters to enable interactive visualization of different risk categories. (Item 15) 1. A system comprising: a Regulatory Information Knowledge Base (RIK), said RIK containing global regulatory data derived from private and public sources; and A server with a processor and memory Equipped with The processor and memory Systematizing informed consent documents and Attach a consent form to the specimen, and Tracking said agreement terms and any changes thereto; and conducting a permitted use analysis of said samples and associated data; automatically generating a consent form using the systematized information-based consent document and the RIK; and A system that is configured to: (Item 16) 1. A computer program product comprising: The computer program product comprises: computer code for codifying informed consent documents; computer code for attaching consent terms to specimens; computer code for tracking said agreement terms and any changes to said agreement terms; computer code for performing a permitted use analysis of said samples and associated data; computer code for automatically generating consent forms using a consent document based on said structured information and a Regulatory Information Knowledge Base (RIK), said RIK including global regulatory data derived from private and public sources; and A computer program product comprising: [Brief explanation of the drawings]

[0022] [Figure 1] FIG. 1 is a flowchart illustrating steps of an exemplary consent codification process for codifying, tracking, and using informed consent data for human specimen research, according to an embodiment of the present invention. [Figure 2] FIG. 2 is a flowchart illustrating steps of an exemplary consent tracking process for organizing, tracking, and using informed consent data for human specimen research, according to an embodiment of the present invention. [Figure 3] FIG. 3 is a flowchart illustrating steps of an exemplary permitted use analysis process for organizing, tracking, and using informed consent data for human specimen research, according to an embodiment of the present invention. [Figure 4] 4A and 4B are depictions of an exemplary global consent landscape portal for organizing, tracking, and using informed consent data for human specimen research, according to an embodiment of the present invention. [Figure 5] FIG. 5 is a block diagram illustrating exemplary components and functionality associated with a regulatory information knowledge base for organizing, tracking, and using informed consent data for human specimen research, according to an embodiment of the present invention. [Figure 6] FIG. 6 is a block diagram illustrating exemplary components and functionality associated with a machine-driven informed consent builder for organizing, tracking, and using informed consent data for human specimen research, according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0023] (Detailed explanation) The subject matter described herein includes systems and methods designed to organize, track, and manage the use of informed consent data for human specimen research. Generally, existing informed consent documents can be reverse-engineered to generate new and more useful "organized" informed consent documents. This organized informed consent document may be machine-readable and machine-actionable, allowing it to be stored and retrieved in an electronic database. When a patient provides a specimen, the system may create a consent profile for the patient that links various information to the specimen. It is then easier to track the patient's consent and any changes (e.g., revocation of consent) to ensure that organizations manage specimens and their associated data in compliance with applicable consent terms and regulations. Analytics can provide rapid assessments of risk or other metrics based on searches of various granularities using interactive visual portals, such as web pages or interactive applications. Finally, the system may be used to automatically generate new consent documents based on desired specifications, so that consent documents can be assembled very quickly and automatically by people without legal training.

[0024] 1, a flowchart illustrating steps in an exemplary consent codification process for an informed consent document, according to an embodiment of the present invention, is shown. In step 100, an informed consent document may be received. The informed consent form or document may explain to the patient the permissions they may agree to regarding the use of their specimens and data, and such a document may be constructed during the research setting and reviewed and approved by an Internal Review Board (IRB). The informed consent form may be written taking into account global and local (national) regulations and the specific needs of the institution.

[0025] In step 102, a combination of expert assessment, natural language processing, and machine learning may be used to translate or "reverse engineer" the meaning of the informed consent document into a set of classes. These classes may encode the informed consent document into a machine-actionable format or set of rules. The rules may, in turn, define what the patient has consented to in terms of what may be done with their specimens and data. Codification may be an initial step in the process of tracking consent. Traditional methods of simply linking signed consent documents to specimens are cumbersome because they do not allow for automated assessment of consent and therefore rely on humans to read, interpret, and act on the consent.

[0026] In step 104, one or more consent categories may be determined. Codification may be based on universal world, national, regional, and local regulations and may therefore be linked to regulations in effect at the time of codification. In this way, for example, specimens collected in 2005 under universal regulations of that year may be used even if regulations changed in 2007 to restrict the use of certain forms of analysis on those specimens.

[0027] In step 106, the consent terms may be written to a database. For example, the structured information-based consent document may be stored in one or more machine-readable formats in an electronic database for easier processing. Details of the database and its use will be described in more detail below.

[0028] In step 108, the consent codification process may also include attaching consent terms to the specimen. For example, the system may integrate consent terms with specimens and data on a patient, collection facility, sample type, country, and region basis. In this way, a patient's consent "profile" may be irreversibly linked to the specimen and the data derived from that specimen. Furthermore, any derivatives of that parent specimen, of any type, may also be linked to the consent profile.

[0029] 2, a flowchart is shown illustrating steps in an exemplary consent tracking process for organizing, tracking, and using informed consent data for human specimen research, according to an embodiment of the present invention. Consent terms and any changes to those terms, such as changes to restrictions on what can be done to specimens or whether a patient's consent is revoked, may be tracked. Dynamic consent tracking can ensure that organizations using specimens and data remain compliant at all times.

[0030] In step 200, a permitted use query may be compiled and in step 202, the query may be submitted to a database 204. For example, the query may include, "What is the destruction date for the tissue specimen from patient X?"

[0031] In step 206, the permitted use cases may be analyzed based on the consented use profile. For example, the consented use profile may indicate that patient X's tissue sample must be destroyed by December 2015, but can be used for FBR until that date.

[0032] In step 208, authorized user reports and risk assessments may be generated and provided.

[0033] Referring now to FIG. 3, a flowchart illustrating steps in an exemplary permitted use analysis process for organizing, tracking, and using informed consent data for human specimen research, according to an embodiment of the present invention, is shown. Some embodiments of the present invention enable rapid determination of permitted uses of specimens and data and policy-based queries regarding specific consent profiles. For example, "tissue samples available for genomic analysis from Brazil." The subject matter described herein may also provide "risk assessments" from a consent perspective when specimens and data are queried or browsed during analysis, inventory lookup, cohort creation, third-party sample acquisition, and other interactions where understanding permitted use risks is important.

[0034] In step 300, a patient consent profile may be created. The patient consent profile may indicate all details regarding what the patient has consented to regarding their human specimen and associated data. Specimen collection and data collection may also occur in step 300. This may include, for example, collecting tissue samples, biographical or medical information, or similar items obtained from human subjects during clinical trials, research studies, patient enrollment, or diagnostics.

[0035] Additionally, in step 300, the consent data is loaded and in step 306 it is determined whether the consent profile has changed. If so, the consent profile is updated in step 308. This may include updating the consent profile when a patient revokes their consent, or vice versa, and adjusting any details regarding the consent (e.g., time, location, mode).

[0036] 4A and 4B, a wireframe is shown illustrating an exemplary global consent landscape portal for organizing, tracking, and using informed consent data for human specimen research, according to an embodiment of the present invention. Some embodiments of the present invention may provide a global consent landscape analysis, allowing organizations to quickly determine the risks of study administration, specimen collection, and patient enrollment from a consent perspective. Visual indicators may provide a fast visual assessment of risk. The global landscape analysis may be represented in the form of a map with risk indicators overlaid on the map, along with filters, allowing interactive visualization of different risk categories.

[0037] The global consent landscape analysis contains links to further information about the consent landscape, including actual written consent regulations and information about each location, which can help inform risk assessments derived from the Regulatory Information Knowledge Base (RIK). For example, as can be seen in Figure 4A, a geographic map is displayed with color-coded indicators of low, medium, and high risk. One or more risk filters may be adjusted by using risk filter sliders to provide for lower and higher risk limits to be displayed on the map.

[0038] In FIG. 4B, specific regulatory information may be linked, for example, in the form of a PDF file that may be used to display the linked related regulatory information in the database.

[0039] Referring now to FIG. 5, a block diagram illustrating exemplary components and functions associated with a regulatory information knowledge base for organizing, tracking, and using informed consent data for human specimen research, according to an embodiment of the present invention, is shown.

[0040] Some embodiments of the present invention may use data derived from multiple sources, both private and public, to build a global regulatory knowledge base. For example, regulatory data 500, IRB statements 502, and institutional consent data 504 may be processed in a machine learning step 506. RIK 508 may use machine learning 506 and statistical approaches to provide regulatory information to inform decisions to attempt, for example, the collection of genomic samples within a region of Germany and predictions of their risks.

[0041] RIK508 may also be used in conjunction with analytics to create risk-based models for specimen and data collection. Such models may be used as decision support tools, for example, when writing and negotiating consent in different areas.

[0042] RIK 508 may also learn the behavior of IRBs, ethics committees, health authorities, and other organizations involved in consent approval, which further informs the risk-based model. For example, RIK 508 may inform risk model 510 and risk assessment 512, which in turn may inform the global regulatory landscape 514. Such behavior may include, but is not limited to, implementation, speed of approval, interpretation of local and global regulations, whether they are overly cautious or restrictive, trends over time, and so on.

[0043] Referring now to FIG. 6 , a block diagram illustrating exemplary components and functionality associated with a machine-driven informed consent builder for codifying, tracking, and using informed consent data for human specimen research, according to an embodiment of the present invention, is shown. Some embodiments of the present invention may use RIK 606 and a codification database to “forward engineer” consent forms based on desired consent profiles, required consent categories, regulations, etc. Such consent forms can be assembled in a very rapid and automated manner by people without legal training. Consent forms constructed in this manner benefit from the assembled corpus of consent information within RIK 606.

[0044] For example, first consent criteria 600, second consent criteria 602, and third consent criteria 604 may be entered into a regulatory information database 606. RIK 606 may be used for a forward engineering process 608.

[0045] In step 610, a summary of desired consents, required consent categories, and regulatory consent forms are automatically generated.

[0046] As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method, or computer program product. Thus, 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, all of which may be generally referred to herein as a "circuit," "module," or "system." Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer-readable medium(s) having computer-readable program code embodied thereon.

[0047] Any combination of one or more computer-readable media may be utilized. The 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). The computer-readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (non-exhaustive list) of computer-readable storage media 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 specification, a computer-readable storage medium may be any tangible medium of expression that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0048] A computer-readable signal medium may include a propagated data signal with computer-readable program code embodied therein, for example, 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, electromagnetic, optical, 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 can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0049] The program code embodied on the computer readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, fiber optic cable, RF, etc., or any suitable combination of the foregoing.

[0050] Computer program code for carrying out operations related to 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++, or the like, 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, partially on the user's computer, partially on the user's computer and partially on a remote computer, as a standalone software package, or entirely on a 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 the connection may be to an external computer (e.g., through the Internet using an Internet Service Provider).

[0051] Aspects of the present invention are described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (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, a special-purpose computer, or other programmable data processing apparatus to manufacture a machine, such that the instructions, executing via a processor of the computer or other programmable data processing apparatus, create means for implementing the function(s) / acts specified in the block or blocks of the flowchart and / or block diagrams.

[0052] These computer program instructions may also be stored in a computer-readable medium that may instruct a computer, other programmable data processing apparatus, or other device to function in a particular manner to produce an article of manufacture, where the instructions stored in the computer-readable medium include instructions that implement the function / acts defined in a block or blocks of the flowcharts and / or block diagrams.

[0053] Computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device such that a series of operational steps to be performed on the computer, other programmable apparatus, or other device cause a computer-implemented process, such that the instructions, executing on the computer or other programmable apparatus, provide a process for implementing the function(s) / act(s) defined in the flowchart and / or block diagram block or blocks.

[0054] The flow charts and / or 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 a flow chart or block diagram may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). 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 in parallel, and the blocks may sometimes be executed in the reverse order, depending on the functionality involved. It should also be noted that each block of the block diagrams and / or flow chart illustrations, and combinations of blocks in the block diagrams and / or flow chart illustrations, may be implemented by a dedicated hardware-based system that performs the specified function(s) or function(s), or a combination of dedicated hardware and computer instructions.

[0055] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly dictates otherwise. Furthermore, it will be understood that the terms "comprises" and / or "comprising," as used herein, specify the presence of certain features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0056] Corresponding structure, material, acts, and equivalents of all means or steps, as well as functional elements, in the following claims are intended to include any structure, material, or act for performing the function as specifically claimed in combination with other claimed elements. The description of the present invention has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the invention. The embodiments were chosen and described to best explain the principles and practical application of the invention and to enable those skilled in the art to understand the invention in various embodiments, with various modifications as may be suitable for the particular use contemplated.

[0057] The description of various embodiments of the present invention has been presented for purposes of illustration and is not intended to be exhaustive or limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein has been chosen to best explain the principles of embodiments, practical applications, or technical improvements over the art found in the marketplace, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method, the method comprising: using machine learning to codify existing informed consent documents into machine actionable protocols that define what the patient has consented to be done with the specimen and associated data; linking a consent profile to the specimen and the associated data, the consent profile including the machine actionable terms; tracking changes to the machine-actionable terms in the consent profile; and generating a new consent document based at least in part on global regulatory data for a plurality of locations by using the machine-actionable contract with any of the tracked changes and a regulatory information knowledge base (RIK) configured to learn regulatory data and consent approval behaviors, wherein the RIK includes the global regulatory data; and using an analysis of consent approvals to display regulatory information for at least one of the plurality of locations based on the new consent document and the consent profile; and A method comprising:

2. The method of claim 1, further comprising displaying multiple risk metrics for the collection of the specimen associated with the new consent document at the multiple locations.

3. The method of claim 1, further comprising displaying a plurality of visual risk indicators using color coding corresponding to a plurality of risk metrics, and the associated data comprising data regarding the patient, collection facility, sample type and data derived from the specimen.

4. The method of claim 2, further comprising irreversibly linking the data derived from the specimen with the consent profile.

5. The method comprises: receiving an authorized use query for the specimen; generating a permitted use report based on at least some of the machine-actionable rules in response to the permitted use query; The method of claim 1 further comprising:

6. The method of claim 1, further comprising displaying a plurality of visual risk indicators associated with representations of the plurality of locations.

7. A system, comprising: using machine learning to codify existing informed consent documents into machine actionable protocols that define what the patient has consented to be done with the specimen and associated data; linking a consent profile to the specimen and the associated data, the consent profile including the machine actionable terms; tracking changes to the machine-actionable terms in the consent profile; and generating a new consent document based at least in part on global regulatory data for a plurality of locations by using the machine-actionable contract with any of the tracked changes and a regulatory information knowledge base (RIK) configured to learn regulatory data and consent approval behaviors, wherein the RIK includes the global regulatory data; and using an analysis of consent approvals to display regulatory information for at least one of the plurality of locations based on the new consent document and the consent profile; and A system comprising a processor and memory for performing the steps of:

8. The system described in claim 7, further comprising the processor and memory configured to display multiple risk metrics for the collection of the specimen associated with the new consent document at the multiple locations.

9. The system of claim 7, further comprising the processor and memory configured to display a plurality of visual risk indicators using color coding corresponding to a plurality of risk metrics, and the associated data includes data regarding the patient, collection facility, sample type and data derived from the specimen.

10. The system of claim 8, further comprising the processor and memory configured to irreversibly link the data derived from the specimen with the consent profile.

11. The system comprises: receiving an authorized use query for the specimen; generating a permitted use report based on at least some of the machine-actionable rules in response to the permitted use query; The system of claim 7 , further comprising the processor and memory configured to:

12. The system of claim 7, further comprising the processor and memory configured to display a plurality of visual risk indicators associated with representations of the plurality of locations.

13. A non-transitory computer-readable storage medium having stored thereon a computer program, the computer program, when executed by a computer, using machine learning to codify existing informed consent documents into machine actionable protocols that define what the patient has consented to be done with the specimen and associated data; linking a consent profile to the specimen and the associated data, the consent profile including the machine actionable terms; tracking changes to the machine-actionable terms in the consent profile; and generating a new consent document based at least in part on global regulatory data for a plurality of locations by using the machine-actionable contract with any of the tracked changes and a regulatory information knowledge base (RIK) configured to learn regulatory data and consent approval behaviors, wherein the RIK includes the global regulatory data; and using an analysis of consent approvals to display regulatory information for at least one of the plurality of locations based on the new consent document and the consent profile; and A non-transitory computer-readable storage medium that causes the computer to perform the above.

14. A non-transitory computer-readable storage medium as described in claim 13, wherein the computer program further causes the computer to display multiple risk metrics for collection of the specimen associated with the new consent document at the multiple locations.

15. The non-transitory computer-readable storage medium of claim 13, wherein the computer program further causes the computer to display a plurality of visual risk indicators using color coding corresponding to a plurality of risk metrics, and the associated data includes data regarding the patient, collection facility, sample type and data derived from the specimen.

16. A non-transitory computer-readable storage medium as described in claim 14, wherein the computer program further causes the computer to irreversibly link the data derived from the specimen with the consent profile.

17. The computer program comprises: receiving an authorized use query for the specimen; generating a permitted use report based on at least some of the machine-actionable rules in response to the permitted use query; The non-transitory computer-readable storage medium of claim 13 , further causing the computer to perform:

18. A non-transitory computer-readable storage medium as described in claim 13, wherein the computer program further causes the computer to display a plurality of visual risk indicators associated with representations of the plurality of locations.

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