The Lifecycle of a Sample

Transcription

1 The Lifecycle of a Sample Samples are the basis by which all research decisions are made. By following best practices in data management, it is possible to optimise collections, minimise the effect of pre-analytical variability and maximise the utility of a sample through ease of access to scientists during its lifecycle Katheryn Shea at BioStorage Technologies, Brooks Life Science Systems European Pharmaceutical Contractor February 2017 issue. Samedan Ltd 2017 pp14-19 Research samples are invaluable scientific assets that support the foundation of new drug discovery and development. Studies suggest that standardised management of these materials can contribute to budget savings, cost avoidance and clinical trial efficiencies that could reduce drug development timelines. However, many organisations still employ a siloed approach where samples are scattered between multiple laboratories and testing facilities based on specific initiatives. This model presents numerous bottlenecks, such as delays in finding biological materials, extended distribution times and additional expenditure due to the lack of economies of scale. By taking a holistic approach to comprehensive sample management Retrieve Analyse Protect in which every stage of the lifecycle is considered a firm can maximise their inventories. Establishing biospecimen collections to support clinical trials and future research requires strategic planning. Key elements in the process include providing sufficient funds to create and sustain the collection; adequate facilities and equipment to ensure they are secure; experienced staff, preservation and logistics management of biospecimens and their associated data; plus curation of all data parameters that will be needed to select specimens for use. Financial resources are essential to create a quality biospecimen collection and to Dispose Plan preserve it for future use. Budget planners must consider supporting all institutions involved in the collection, processing, analysis and storage of the samples during the active phases of the trial and after the primary study has ended. Centralising processing and repository activities can drastically reduce the cost of a trial by decreasing the number of institutions in which infrastructure must be maintained, and minimising transportion costs required by sites having to send samples to multiple labs. The study design should also take the intended use of the specimens into account. While the tests for the main trial will be known, future uses are often Process Collect Transport

2 Time, temperature and technique are the three T s that must be taken into consideration when determining how best to plan for specimen logistics. The types of samples to be collected will depend on the downstream assays to be performed, and this also affects processing parameters undefined. Designers must be aware that the types of analysis they envision will be performed on the specimens in the future based on the studied disease and the planned strategic research direction of the organisation. Determining how broad to make the informed consent, what material types whole blood, peripheral blood mononuclear cells, serum, plasma and so forth to collect and how to gather the relevant clinical and demographic data all necessitate deliberate planning and expertise. Informed Consent Considerations Study participants must be acquainted with the intended use of the samples and information. Their consent must contain specific elements, including how the samples will be identified, who will have access to them and how long they will be stored. The type of research they will be used for must also be clear. This could be anything from a very broad definition such as open for all research activity that has been approved by an ethics board to a very narrow one like a specific disease or pathway of a disease. This information should also be included, especially when genetic studies or the generation of cell lines are planned. Geographical regions all have different regulations on what must be contained in the consent and could also have specific requirements on how broad it can be or for how long specimens may be retained. Once the informed consent has been drafted and approved by the appropriate ethics committees, the variables that govern permitted uses and restrictions must be annotated in a system that allows for efficient query. These include information on what the participant consented to broad or specific use and types of research that may be performed, for instance access requirements and expiration dates. It is also important to capture key parameters around the consent process, since changes in regulations may be applied retrospectively to specimen collections and their data. The date and location in which the informed consent was applied and permission given are the two most important criteria for determining the impact of regulatory changes to existing collections. Informed consent is traditionally managed using paper-based records, which creates special challenges in terms of efficiency and data connectivity. These documents are typically lengthy and include complex information, making them difficult for participants to understand clearly. From an administrative perspective, different consent forms are required for each study and, even within a single trial, multiple versions may be required to support various locations, and revisions could be necessary during the study. This can make it hard to connect specific consent language to a given specimen. In consent, as with other paper-based processes, electronic systems to capture and manage the procedure provide significant benefits and efficiency gains. Electronic informed consent (econsent) solutions are able to facilitate the operation and can include a variety of media such as text, audio and video features to support comprehension and enable a better experience from a patient perspective. econsent systems ensure that the exact version of the consent signed by a subject can be easily retrieved and connected with other data. They can also improve engagement with patients, allowing participants to be more easily contacted or review their consenting options in the future. For these reasons, interest in econsent is growing rapidly. Logistics, Processing and Storage Time, temperature and technique are the three T s that must be taken into consideration when determining how best to plan for specimen logistics. The types of samples to be collected will depend on the downstream assays Pre-analytical variable Description example Type of sample Type of primary container Pre-centrifugation (time and temperature) Blood (whole) Potassium EDTA < 2 hours, 2-10 C Centrifugation 2-10 C, mins, > 3,000g with brake Second centrifugation No centrifugation Post-centrifugation delay < 1 hour room temperature SPREC code BLD PED A D N B D Long-term storage Cryotube, 1-2mL, -85 to -60 C Table 1 Source: Lehmann et al, International Society for Biological and Environmental Repositories (ISBER) working group on biospecimen science. Standard preanalytical coding for biospecimens: Review and implementation of the sample PREanalytical code (SPREC), Biopreservation and Biobanking 10(4): pp , doi: /bio

3 to be performed, and this also affects processing parameters. When designing a collection for future use, the study protocol should include procedures to collect sufficient material quantities. The plan should also address ancillary studies and potential future research needs. For example, certain assays may specify or exclude: Images: Brooks Life Science Systems Material types: whole blood, serum, plasma, peripheral blood mononuclear cells, CD4 cells and so on Anticoagulant or collection tube type: ethylenediaminetetraacetic acid (EDTA), Na- Heparin, acid citrate dextrose and so forth Isolation or processing method prior to analysis Time to initiate processing Time to stabilise: freeze or fix Preservation method: control rate freezer, plunge freezing and so on Storage temperature Exposure to freeze and thaw cycles Pre-Analytical Variables Pre-analytical variables are sample fluctuations that are known to affect assay results and can also have an impact on the scientific utility of a biospecimen. There are many different ones to take into consideration when conducting research. The College of American Pathologists Diagnostic Health Information Technology working group identified more than 150 variables that could be impactful based on the type of research and disease areas that may be studied. Some common ones that are important for all types of research include: Specimen collection techniques Preservatives used Processing methods Processing materials and reagents Quantities required Vials/containers (volume, type and material) Storage conditions Freezing and thawing methods Exposure to freeze and thaw cycles (number and timing of events) Temperature and time elapsed at each handling or processing step The International Society for Biological and Environmental Repositories Biospecimen working group developed a standard pre-analytical code (SPREC) tool to capture some of the most common variables in a standardised code list (see Table 1).

4 Automated repository units allow for the most consistent and efficient storage of specimens that are expected to have a high level of activity or that require a high level of regulatory oversight. An inherent benefit of these systems is that all handling parameters are tracked, offering an auditable chain of custody that does not rely on an operator capturing their activities manually The first step in regulating these variables is to control the collection materials themselves. Well-designed collection kits will provide all of the components needed to gather specimens from a participant at a particular site; the lot number and expiration date for each should be tracked as these factors could lead to variation in results. Collection and Storage Data elements for collection, processing and storage should be recorded for each biospecimen to provide researchers with all of the information that they will need. The resulting information must be joined to the pre-analytical data to further enrich the resource. In addition to the assay result, the following elements should be captured: Common name for the analyte measured Commercial kit, part number and manufacturer or lab-developed assay The platform used and its version Pre-analytical sample preparation methods Assay validation parameters Limit of detection Percent coefficient of variation Linear range Unit of measure Expected reference range There must also be adequate facilities to hold and maintain the collection. Storage units, constant temperature monitoring, qualification and maintenance programmes are required to ensure that samples are kept in appropriate conditions. Equipment often includes ultralow temperature units and adequate dedicated backup units. Samples should be retained in a manner that allows for efficient transfer in the event of a freezer failure or major temperature fluctuation, and a strategy needs to be in place that takes into account efficient acquisition and later retrieval. Automated repository units allow for the most consistent and efficient storage of specimens that are expected to have a high level of activity or that require a high level of regulatory oversight. An inherent benefit of these systems is that all handling parameters are tracked, offering an auditable chain of custody that does not rely on an operator capturing their activities manually. When contemplating automated storage either

5 immediately or in the future, automationfriendly cryovials and labelling schemes should be employed. Use of these kinds of vials will further facilitate analysis since many testing platforms also utilise automation. Information Management and Access Models In order to realise research value, the clinical, ethical and sample information must be available to researchers in a manner that is easy to access and analyse. It is very common for these various types of information to be kept in different systems and even for there to be multiple parties that store the same type of data. For instance, samples may be held at different biorepositories or labs, making it difficult to see the entire collection in one query. Virtual biobank systems allow for sample information from all involved to be combined so that all sample assets can be found in a single search. Joining relevant sample and scientific data on a solitary platform makes it simple for researchers to find the resources they need. While one approach is to bring all information into one central system, it is also possible to create a platform that enables queries to be run across systems and data sources. The benefit of the latter is that it allows for new sources, in disparate formats, to be easily added to the process. A centralised technological platform solution can support elements of both information warehousing and virtualisation. Records related to sample sets from both internal and external sources can be connected and viewed in real time with speed and agility, accelerating specimen access and research processes. Virtual solutions enable a collection to be displayed through different lenses depending on the case required. A centric lens should connect samples throughout their lifecycle and across one or multiple collections. Best-in-class tools will allow a parent sample from a patient to be traced through all the applicable processing steps to archived end products like DNA and tissue microarrays. Virtual biobanking tools can be invaluable in tracking down all samples related to a given parent sample, irrespective of where they were kept, which can be very important in auditing, consent withdrawal and expiry scenarios. It is also possible to connect samples to quality metrics around their storage and processing, as well as their biomarker and genomic data from lab analysers and sequencers something which can be essential to determining the future use and value of a sample. A subject and study-centric lens should allow samples to be connected to people especially through demographic, phenotypical and epidemiological data. This information may need to be anonymised and the best solutions ensure data security. Connecting samples to undisclosed subject information unlocks intelligence by highlighting the data that makes them useful for research this can then enable researchers to search and analyse a collection by tissue type, patient diagnosis and demographic. These views are essential to realising the research value and enabling a sample s future use. Indeed, these tools can be powerful to ensure the sustainability of biobanks. As the Head of Global Operations for BioStorage Technologies, a Brooks Life Science Systems Company, Katheryn Shea is responsible for all operational aspects of the business across Asia, Europe and the US. She also provides technical leadership for specimen management, processing, storage and distribution activities and is instrumental in the development of business alliances and collaborations. Katheryn received her Bachelor of Science in Biology from St Mary s College in Maryland, US, and is an expert on biological sample management best practices and regulations. kathi.shea@brooks.com