Abstract
Research samples are invaluable scientific assets that support the foundation of new drug discovery. Research suggests that standardized management of these materials can contribute to budget savings, cost avoidance, and process efficiencies that can reduce development time. Unfortunately, many research organizations still employ a siloed approach where research samples are scattered between multiple laboratories and testing facilities based on specific research initiatives. This management model presents numerous bottlenecks, such as delay in finding materials, extended distribution times in shipping materials, and additional cost due to the lack of economies of scale. By taking a holistic approach to comprehensive sample management in which every stage of the sample lifecycle is considered, an organization can maximize their sample inventories.
Introduction
The Value of Samples
The value of research samples cannot be underestimated, therefore it should be assumed that all samples must be prepared and stored in optimal conditions to protect integrity. This is especially true as personalized medicine, biomarker research, and genomic-based discovery become the focal point of many research initiatives. As such, drug developers are becoming increasingly cognizant of the value of their sample inventories. Today, centralized, well-annotated, consented sample collections are critical intellectual property assets to research organizations.
However, not all samples are of equal importance or value. For instance, the disease under study could be rare or the samples could be difficult to obtain (e.g. cerebrospinal fluid). Even in more common disorders, samples kept during the progress of treatment or in pharmacokinetic studies typically become more valuable over time due to the accumulating analytical and clinical history.
From a business standpoint, increased merger and acquisition activity within the pharmaceutical industry is elevating the importance of proper sample care. If compounds are being in-licensed, due diligence may require the licensing company to use sample inventories to re-examine analytical methods and re-assay specimens collected during early development of the drug. Confirmation of the findings from stored samples adds important financial value to the acquisition of the product. Hence, even small companies should have a clearly defined sample storage policy and process.
Not uncommonly, the collection of samples and their associated data may not be in alignment with their intended requirement, which leads to wasteful repetition of studies. In addition, it is sometimes difficult to locate samples after a study is completed, which prompts the need for subsequent recollection of samples. 1 This creates added and unwanted expense. The ability to centralize and unify sample information into a single database allows comparison of data across multiple studies and sharing or reuse of sample assets.
A Comprehensive Solution that Addresses the Sample Lifecycle is the Goal
Lifecycle management plays an important role in maximizing the utility of research samples for current and future research. As such, the ultimate goals of any optimized life cycle approach are minimizing transportation hand-offs (i.e., touches) and eliminating unnecessary freeze-thaw cycles. This approach requires an organization to focus on partners who are dedicated to improving the effectiveness and efficiencies of the overall sample lifecycle.
The sample lifecycle process includes the planning, collection, transportation, protection, retrieval, and disposal of research samples. Sample protection includes critically sample preparation and storage.
Sample preparation supports improved lifecycle management
Sample preparation includes aliquoting, nucleic acid extraction, purification, and downstream processing. Aliquoting of parent samples enables organizations to provide the exact amount of biospecimen volumes to the research bench, which reduces the cost of shipping or storing extraneous sample volumes at testing labs. One example of insufficient planning is the duplication of storage partners. It is not uncommon for a research company to pay multiple storage fees for the same sample stored at different testing locations. Centralization of sample storage with a single biorepository and volumetric aliquoting of parent samples to meet specific testing volume requirements provides organizations with significant cost savings. From a preservation standpoint, aliquoting of volumetric samples prior to storage reduces the number of parent sample freeze thaw cycles.
Sample preparation enables researchers to evaluate the quality of the sample prior to storage. Since the site at which samples are procured is separate in proximity and time from its ultimate storage facility, many factors could impact the viability of the sample before it reaches the biorepository for storage. Garbage in, Garbage out (GIGO) is a principle well known to data management and IT colleagues who manage repositories of data, but it applies equally to sample collections. To ensure the quality of samples sent to, and stored at biorepositories for future research, one needs to establish sample management protocols that include clear and detailed instructions for preparing, collecting, processing, and storing samples (e.g., temperature range, stabilization agent, and centrifuge time).
Sample storage protects samples for future research
The Office of Biorepositories and Biospecimen Research at the National Cancer Institute defines high-quality biospecimens as those that most closely resemble the biospecimen prior to its removal from the human research participant. 2 As a golden rule, a sample that has been maintained at the appropriate storage temperature will yield better results than a sample that has undergone fluctuations in temperature due to poor handling or storage practices. 3 As a result, there has been an increasing amount of attention paid to Good Storage Practices (GSP) guidelines by regulatory bodies and governmental agencies and associations. Industry is also paying greater attention to sample management and storage. For example, the College of American Pathologist (CAP) announced plans in 2011 to begin its biorepository accreditation program starting in 2012. 4 This will be a 3-year, peer-based accreditation program developed to drive adoption of standards.
Additionally, the U.S. FDA, the Centers for Disease Control, and professional organizations such as the American Association of Tissue Banks, the National Cancer Institute, and the International Society for Biological and Environmental Repositories provide guidelines for biorepositories and human sample banks. Specific good storage practices to incorporate into SOPs when establishing a comprehensive sample management strategy include:
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• Secure facilities and redundant measures that ensure specimens are kept in compliant conditions at all times when in storage • Expert staff that has been trained specifically in sample storage and transportation to ensure all regulatory and custom issues are properly handled • Storage technologies capable of continuously monitoring the temperature of samples in order to provide a complete audit trail • Business continuity plans and redundant systems to protect sample integrity during emergencies
How to Develop Your Comprehensive Sample Management Plan
A comprehensive sample management plan provides detail on where and who will manage samples, as well as what resources will be required. Of equal importance is what processes will be used to manage samples and what technologies can be leveraged to improve access to these assets. Experience shows while most companies and institutions feel satisfied they have solved the “who” and “where” questions, the process and technologies elements are often underdeveloped. No sample management program is comprehensive unless it addresses all four of these factors.
Of course, the development of a good plan requires some insight into the ultimate strategy of sample use and this can be gathered by conducting a current, desired, and future state analysis of sample management within an organization.
Current state—Analysis phase
A current state analysis begins with the assessment of internal and external resources such as personnel, inventory, equipment, and supplies. The next step is the evaluation of the information technology systems and data management processes that store and report sample information. Finally, existing processes are assessed in order to determine areas of gap or improvement needs. This analysis yields information that supports the establishment of an organization's sample management goals.
Desired state—Goal setting phase
There are several sample management models to consider when developing a comprehensive sample management plan. The decision to insource, outsource, or develop a hybrid approach to sample management depends on the desired goals of the organization. For example, a possible organizational goal is to develop a plan that creates improved transparency of sample assets to support future prospective and retrospective research while reducing sample management costs.
Future state—Management evaluation phase
Any future state model must take into consideration the company's culture. Do we employ internal capital for sample management? Do we outsource all sample management functions completely? Or, do we employ a hybrid model that combines established assets with onsite expertise from outsourced providers? These are all questions that must be considered upfront. Another major factor in the model equation is the cost of building and maintaining a world-class biorepository. When incorporating the cost of compliant facilities, informatics systems, and a global logistics infrastructure along with staff to manage sample inventories, an onsite biorepository facility can easily require an investment of $9 million or more over a 10-year period. 6 This internal cost does not include the external cost of sample inventory loss or data management costs when managing samples not stored in onsite facilities.
Outsourced sample management models allow companies to eliminate capital and overhead expenses associated with sample management. The ability to integrate biospecimen data is essential to successful clinical operations. 2 An outsourced model provides sample management experts who focus on ensuring the viability of sample assets and consolidation of sample data within a single, centralized database that is accessible to the research customer. It is important to find an outsourcing partner with advanced technology solutions that can unify sample data from multiple research laboratories, CROs (Contract Resource Organizations), or biorepository facilities located in various areas around the world. The improved sample lifecycle management expertise and technology brought to a research organization by an outsourced sample management service provider enables a research organization to focus on their research core competencies and to speed future research advancements to the market.
Some companies have existing resources and infrastructure to leverage to support internal sample management, but lack the technology and sample lifecycle process expertise to manage their sample assets more efficiently. Complete insourcing (onsite) or hybrid models that combine insourcing and outsourcing approaches to sample management exist in which sample inventories are either fully or partially stored onsite. The onsite samples are managed by an outsourced provider who may supply expert staff, standard operating procedures, and data management technology. An insourcing or hybrid model allows a company to leverage existing capital resources, refocus staff resources on the science, and places the management of critical scientific sample assets with a service provider who has expertise in sample management. 7 This trend is especially advantageous for bioscience companies that require the flexibility to accommodate changes in the storage volume of their research sample inventories, but do not have the scalable operations and infrastructure to support the expansion or retraction of these inventories.
Conclusion
If a researcher knew today what was to be discovered in a sample tomorrow, one would not need a sample management strategy to preserve these materials and their associated data. Unfortunately, however, the prospective scientific value of a particular sample will only be realized post-analysis. In the post-genomic era, new advances in medical science are highly dependent on high-quality, properly preserved patient samples. Therefore, preserving the integrity of scientific sample assets has become increasingly important in nearly every medical research discipline, as these valuable materials can be exploited to support biomarker discovery, personalized medicine, and development of other genomic-based treatments. Additionally, the need for properly preserved samples will continue to grow due to the need for retrospective analysis of samples in a study. However, to realize the full potential of collected samples, a comprehensive strategy for sample management is required that includes the assessment of internal and external resources, development of consolidated information technology solutions for leveraging sample assets, and the utilization of improved sample lifecycle management processes. Formalized sample preparation processes, compliant sample collection, reliable transportation and chain of custody, Good Storage Practices, and robust IT and data management solutions are all important considerations when establishing a comprehensive sample asset management plan.
Footnotes
Disclosure Statement
No competing financial interests exist.