Insight into clinical sample and consent tracking
Clinical specimens, clinical trial samples and the information associated with
them are precious resources that require careful curation. CLI caught up with David Kaye [Vice President and General Manager of BioFortis (a Q2 Solutions company)] to find out more about what this entails.
Paint a picture for me, please, of the kind of path that a sample would take in a traditional clinical trial and what the methods are typically for sample documentation/tracking
Biological samples and clinical data derived from human subjects drive clinical research. A biobank serves as a biorepository, collecting, processing, storing and supplying specimens and related research. Sponsors of clinical trials make significant investments in conventional biobanks, building out infrastructure in terms of necessary hardware (e.g. freezers, automation, etc.) and developing or purchasing first-generation biobanking management software with a particular focus on enhancing operational efficiency in sample collection, storage and processing.
Traditionally, samples were collected for specific uses and stored in a biorepository, then shipped to labs and then back to a centralized biorepository. The shipping, tracking and consent-related activities related to samples were frequently managed using manual and paper-based processes. With all the movement of samples, there was an unmet need to track samples and the consent associated with them among the various stakeholders engaging in clinical trials..
What might the path of a sample in a clinical trial be now?
To support recent research needs, which are becoming more complex by the day, sample-management activities must not only support biospecimen operational activities but also function as the knowledge hub for an integrated translational and clinical research ecosystem. Biobanking activities and the corresponding sample-tracking needs that have emerged in today’s environment must track samples and integrate a wide array of data across an entire ecosystem, including data from eClinical systems, sponsors, collection sites, central labs, specialty testing labs, third-party labs and biorepositories. In recent years, this ecosystem has vastly expanded in geographic scope, and sample collection, tracking, shipping, analysis and storage are often done across several different countries or regions and locations within individual countries.
What are the limitations of the original methods of sample documentation/tracking, and what are the consequences of inadequate sample documentation?
Traditional biobanking activities were often focused on amassing large amounts of samples for a relatively limited set of research purposes. This practice did not focus on the quality of the samples obtained or actively managing samples to optimize their use, not only in specific research studies but potentially in future studies. In addition, original methods suffered from:
• limited ways to reconcile issues that occurred with samples (e.g. damage or loss);
• less focus on determining how samples could be used for future research;
• limited ways for various stakeholders to collaborate in the management and use of samples, due to the constraints of using manual systems, or legacy software systems, which do not foster real-time exchange of information among users; and
• operational and compliance challenges, including such regulations as 21 CFR Part 11 [1] and HIPAA [2], record-keeping and reporting, and the difficulty in tracking the history and full chain of custody for each sample.
Although many organizations used software-based solutions to catalogue the location of samples within a biobank, there are critical shortcomings of relying upon traditional biobanking solutions to optimize the use and tracking of samples in clinical trial settings.
How have the goals of clinical trial research changed over time, and how does this affect consent gathering and consent tracking?
Biomarker-driven precision medicine (personalized medicine) is fundamentally changing life sciences research. Central to biomarker research is access to quality biospecimens that have been extensively annotated with clinical, molecular, patient and consent data. A researcher’s focus on samples should not be measured by how many samples it has in storage but by the utilization of these samples to drive investigational research, as well as the ability to actively manage samples during the course of a clinical trial. This shift poses challenges for traditional, first-generation biobanks and sample-management approaches.
With increasing importance of biospecimen collection and use in clinical trials, clinical operations and scientific teams alike face these new challenges regarding sample and consent tracking.
First, there is an increased demand for rigor and timeliness of sample information. Deep science behind biomarker-based studies demands more stringent biospecimen tracking and management. Samples collected from clinical trials must be of high quality, with detailed annotations, as well as proper study participant consent, which allows the sample to be used for a permitted purpose, while adhering to ethical and regulatory guidelines that protect patients. As data from samples are used for making critical in-study decisions, sample-tracking information must be accurate and timely in order to provide study teams with actionable insights that can drive more informed decision-making. In fact, losing a few study samples in today’s research landscape may jeopardize an ongoing trial if researchers cannot secure key efficacy and cohort enrolment measures.
Additionally, pharmaceutical and biotech sponsors often outsource clinical trial execution to clinical research organization partners. In turn, sponsors and contract research organizations must manage an ecosystem of other vendors (e.g. central labs, specialty testing labs, storage facilities, etc.) who all handle trial samples. This is a stark contrast to the much simpler set-up of managing samples in one central facility. The handling, processing, testing and data management of biospecimens in this complex ecosystem is commonly duct-taped together with paper, Excel spreadsheets and manual manipulations. In this intricate workflow of sample handling and management, a manual approach can come apart under stress. Therefore, a centralized, comprehensive sample- and consent-tracking database application is critical to ensure the informational integrity of the entire ecosystem with near real-time oversight of progress.
Lastly, we face increasing regulatory scrutiny, changing legal requirements and differing guidelines across geographical regions. These factors contribute to difficulties in determining what can and cannot be done with trial samples, which puts further burden on clinical trial sponsors and stakeholders, including site teams and lab teams.
What would best practices for clinical trial sample and consent tracking look like now?
The collection and use of samples must support science by shifting from a focus on primarily operational and in-house sample inventory management activities (i.e. hoarding samples) to driving deeper scientific insights by encouraging the optimal use of samples. Linking biospecimens with patient clinical and molecular data as well as patient consent and tracking samples across the full lifecycle of a study is now critical. Several key components must be established in a holistic informatics solution in order to improve clinical trial sample and consent tracking.
There has to be an effective sample collection plan detailing the samples to be collected from patients at various times as determined by experts, including the principal investigator for the clinical trial. This plan must address important areas, such as which samples and for which assay types need to be collected at each visit, which shipping and processing facilities these samples will go to and what actions (processing, assay, storage, etc.) will be performed on the samples at each site, lab or facility.
It is critical to compare and reconcile the samples that are collected against the sample plan to determine which samples have actually been collected and processed. This would include the identification of which samples have been collected or created (including sample derivation/lineage information) at each site, central lab, testing lab and storage facility; which samples have been shipped from each facility to each intended location; and which samples were actually received at each facility.
Another key component is the tracking of individual patients’ consent responses for how biological samples and derivatives can be used in a specific clinical study and beyond. Furthermore, as set by the study team and sites, standard consent parameters/ restrictions must be incorporated into computable data elements. In doing so, stakeholders can then reconcile these data against a particular patient’s consent responses to derive the allowable use for each donated sample. Information regarding patient consent must:
• detail any consent restrictions at the study and site levels;
• identify any additional country or regional restrictions;
• determine which patients have signed which form of consent (both mandatory and optional); and
• determine which consent version applies to each collected sample.
This information must also allow stakeholders to determine allowable uses for the samples from each patient (both for the ongoing study and future use), including what types of additional testing are allowed for study.
In an effective sample collection plan, detailed information regarding collection progress can be held against the sample collection plan, and clear insights into the parameters of consent regarding each sample can be noted. Through a strategic plan, study teams can receive reconciliation reports that enable them to monitor the health of the trial from a sample-centric perspective, and when required, intervene in a timely fashion to improve trial quality and shorten trial time.
From an informatics perspective, the main objective is to be able to acquire, standardize and combine the multitude of study data sources (e.g. study protocol, ICD, IVRS, IWRS, EDC, sites, central labs, test labs and storage facilities/biobanks) from clinical trial stakeholders and partners. Once this has been done, meaningful calculations and additional business intelligence can be derived from these various data elements. This approach provides all stakeholders in a clinical trial the ability to promptly identify any issues regarding the collection, storage, shipping, handling, consent or testing of samples across an increasingly complex and distributed ecosystem to efficiently monitor and manage the health of their clinical trial and optimize the use of biospecimens in their clinical research.
Abbreviations
EDC: electronic data capture
ICD: informed consent document
IVRS: interactive voice response systems
IWRS: interactive web response systems
References
1. 21 CFR Part 11. Guidance for Industry. Part 11, of Title 21 of
the Code of Federal Regulations; Electronic Records; Electronic Signatures (21 CFR Part 11). U.S. Food and Drug Administration 2003 (https://www.fda.gov/regulatory-information/search-fda-guidance-documents/part-11-electronic-records-electronic-signatures-scope-and-application).
2. HIPAA. Health Insurance Portability and Accountability Act of 1996. Office of the Assistant Secretary for Planning and Evaluation 1996 (https://aspe.hhs.gov/reports/health-insurance-portability-accountability-act-1996).
The interviewee
David Kaye BBA, JD
Vice President and General Manager,
BioFortis (a Q2 Solutions company)
BioFortis LLC, 10320 Little Patuxent Parkway,
Suite 410, Columbia, MD 21044, USA
E-mail: dkaye@biofortis.com
