Scientists are only beginning to understand the multifactorial nature of diseases, but with large-scale biobanking, it may be just a matter of time before the dots connect. Genomics is paving the way for precision medicine and suitable treatment options for rare and difficult-to-treat conditions. This calls for large population-based biorepositories reflecting gene-gene and gene-environment interactions over time. If any success is to be achieved, there’s a need for international collaboration to achieve the required statistical power. This blog discusses the need and relevance of population biobanks as key drivers of clinical research in the future.

What is a Population Biobank?

A population biobank is best described as donations of thousands of biological specimens collected from members of the general population who might or might not be suffering from any disease. Most of these biological specimens are genetic material. However, a population biobank should not be confused with a genetic biobank which is a biorepository that only handles DNA material in order to understand the genetic determinants of disease, regardless of whether the samples were collected from the general population or not.

Population biobanks play a major role in identifying and analyzing genetic susceptibility to diseases and how lifestyle and environmental factors contribute to diseases. Population biobanks facilitate this by enabling researchers to analyze molecular data as well as the associated data such as clinical, imaging, and lab reports. A number of countries are already in the process of setting up population biobanks.

The Human Genome Project Laid The Foundation for Population Biobanks

The highly acclaimed Human Genome Project provided the stage for major breakthroughs in precision medicine, having successfully managed to sequence the entire human genome. This scientific miracle made it possible for researchers to begin to explore the link between genetics, disease, and response to treatment. However, translating this preliminary understanding into clinical benefits remains a challenge. A population-based approach to biobanking will give scientists multiple, varied and unbiased samples that will allow them to explore complex disease susceptibility genes.

Population Biobanks Are Powerful Tools in the Prevention of Chronic and Rare Diseases

Population biobanks play host to millions of genetic material as well as the related lifestyle, environmental, and clinical information. Researchers are able to analyze all this information and identify multifactorial causes of disease. This may provide breakthroughs in the treatment of chronic diseases such as Alzheimer’s, schizophrenia, cancer, diabetes, and asthma among others. This may also help scientists to establish triggers for adverse outcomes such as congenital birth defects and preterm births.

Population Biobanks Can be Used to Estimate Allele Frequency

Because of the diversity of varied specimens (from a large cross-section of participants from different ethnicities) in population biobanks, researchers are able to estimate allele frequency. This is the proportion of people in a population with a specific gene frequency that is instrumental in understanding the interplay between genetic and environmental factors and disease causation.

Population Biobanks Provide Modern Tools for Disease Prevention

In spite of major breakthroughs in genomics, their translation into clinical benefits has remained a mirage. Population biobanks are however promising to translate discoveries at the genetic level into a better understanding of complex diseases and hence the discovery of new and better drugs. What has been discovered from genomics so far has not been sufficient to alter current recommendations for patient care unless on a case-by-case basis. Research driven by population-based biobanking will bridge this gap and allow scientists to exploit the interplay between genetics and environmental risk factors for diseases. This research is needed not only for drug development but also for devising disease prevention strategies as well.

Role of a Biospecimen Management System in Population Biobanks

Population biobanks handle and process a ton of samples and sensitive patient data that’s the bedrock of clinical research. A Biospecimen Management System, also known as a Laboratory Information Management System (LIMS), offers a turnkey solution for labs through automation. A biospecimen management system offers end-to-end sample tracking and management and streamlines the entire biobanking workflow. A cloud-hosted biospecimen management system ensures remote access to biobank data and promotes collaboration while at the same time guarantees maximum data protection and security.

How Population Biobanks Can Shape the Future of Clinical Research

The world is at an unprecedented time with the evolution of -omics and precision-driven medicine. However, translational research remains elusive. Population-based biobanks store large volumes of biosamples harnessed from the general population. Population biobanks enable researchers to analyze genetic biomarkers in relation to medical history and environmental factors. They go a step further to offer information about allele and gene frequency in a population. The integration of population-based genomics with modern biobanking will provide scientists with the rare opportunity to tackle rare and complex diseases right at the genetic level. A biospecimen management system streamlines and automates operations of population biobanks, helps them overcome regulatory challenges, and assures data security at all times.

Biospecimen acquisition in industry represents a serious challenge that slows down innovation. The number of biobanks has increased around the world due to the growing requirement of biospecimens by industry. However, the lack of connection between biobanks and industry has slowed down the possibilities to use biospecimens for testing new therapies, developing vaccines and strategies for diagnosis. Private companies face difficulties accessing high-quality specimens because they mostly originate from public sector healthcare facilities and companies have limited access to such facilities. It is important to bridge the gap between biobanks and industry so that researchers can easily access carefully processed, high-quality biospecimens to support research and development.

Pharma and biotech companies mainly procure biospecimens for research from commercial brokers who charge a fee for providing samples from biobanks. However, the use of intermediaries leads to uncertainty about sample quality and adequacy for the required experiments. Big pharma companies manage to procure samples from hospitals and in-house biobanks. They also conduct clinical trials which give them access to hospitals, doctors, and patients. Access to biosamples becomes more complicated for small biotech companies as they find it harder to establish collaborations with hospitals and biobank networks.

Challenges Faced by Industry in Obtaining Quality Samples

Commercial brokers are apprehensive about the direct interaction between a researcher and the biobank as this could lead to a loss of profits. Due to this, brokers usually do not prefer to disclose the sample source. Unfortunately, this leads to a lack of provenance information such as sample processing history, donor information and medical history, and geographic origin of samples.

Researchers need to know the identity of the source biobank. The source biobank should have obtained the appropriate license and certification as it assures sample quality and reliability. Knowing the geographic origin of samples is also important to understand the environmental, socio-economic, and genetic factors of samples. Biobanks should maintain donors’ consent for all samples stored in their biobanks and must have standard operating procedures (SOPs) in place for procuring, processing, and distributing samples. It also helps prevent the use of illegally sourced samples. Obtaining biospecimens internationally also poses a challenge of miscommunication between the source and the end-user.

Solutions

To overcome such challenges, commercial brokers can allow direct communication between the source biobanks and end-users with an agreement to ensure brokers’ commission. Companies can build their networks of biobanks to supply them with the required biospecimens. However, it is challenging to find suitable biobanks with the necessary samples in stock. Therefore, many small to medium-sized biotechs end up obtaining samples from unreliable brokers, compromising the quality and reliability of samples.

The direct connection between biobanks and industry represents a great opportunity for both sectors. Some proposals to address the challenges outlined above are:

• Promote regulations that protect the ethical usage of biospecimens while allowing biobanks to charge a fee for sample processing.
• Establish high standards for biosamples collection, processing and storage, with adequate documentation and data provenance to assure sample reliability.
• Promote patients’ approval to participate in private sector research by educating them about the importance of biotech and pharma health innovations.
• Encourage industry to procure samples from biobanks that meet regulatory compliance and best practices, such as ISO 20387:2018, EU GDPR, HIPAA, and ISBER Best Practices, and follow pre-defined SOPs to maintain quality standards.

A commercial biobank can play an important role in overcoming the sample supply deficit. Commercial biobanks are experienced in interacting with industry and meeting their requirements. Unlike academic biobanks, commercial biobanks act quickly to meet administrative and regulatory requirements to provide samples to companies to facilitate their research.

How a Biospecimen Management System Can Help Biobanks Maintain Data Provenance & Maintain High-quality Samples

Companies can rely on biobanks that use a Laboratory Information Management System (LIMS) for managing data and standardizing their operations. A LIMS effectively manages samples and associated data to facilitate their tracking through sample acquisition, collection, preparation, storage, testing, analysis, and distribution. It helps in safeguarding data by assigning role-based, secure data access to authorized users. A biospecimen management system, also known as a biobanking LIMS, helps biobanks manage sample genealogy, track sample locations, and manage the shipment of samples when working with collaborators. It maintains a chain of custody to regulate the internal or external transfer of biospecimens from one custodian to another.

A biospecimen management system manages standard operating procedures (SOPs) and controls access to confidential documents, thus ensuring data security. It records details such as training details, qualifications, and competency of each staff involved in biobanking activities. Furthermore, a LIMS helps biobanks follow regulatory guidelines such as ISO 20387, HIPAA, EU GDPR, and 21 CFR Part 11.

A LIMS enables commercial biobanks to publish their sample collections along with detailed sample information on a personalized web catalog. Researchers from industry can easily find samples of their interest on the web catalog, place an order for the samples they need, and track the status of their requests.

Conclusion

Biobanks are responsible for providing high-quality, well-documented biosamples to industry to facilitate the development of new drugs, therapies, and diagnostic products for improving patient care. Pharmaceutical and biotech companies should procure biospecimens from biobanks that maintain strict quality and ethical standards and provide reliable data provenance information. A biospecimen management system is a secure and reliable system for collecting, storing, processing, analyzing, and reporting all types of biobank data. It helps biobanks securely manage data, streamline workflows, comply with regulations, and follow sample management best practices.

“Research should pursue science advancement and public health development while respecting the dignity, autonomy, privacy and confidentiality of individuals.”
The Taipei declaration

 

The European Union’s General Data Protection Regulation (GDPR), which came into full effect in 2018, has increased regulatory oversight and subsequent potential sanctions that have caused uneasiness within the biobanking and databanking circles. The EU GDPR has posed stringent restrictions on the use of banked data and associated biospecimens for use in secondary research. Consequently, the protection of health and genomic data is of significant importance in the implementation of the EU General Data Protection Regulation (GDPR).

Oversight of the GDPR

GDPR is overseen by ethics committees and data access committees (DACs) that limit the access and use of personal data. Ideally, these committees should be equipped with the expertise to regulate the use and sharing of genomic data and provide overall governance over personal data processing taking into account individual or social concerns that may not be explicitly laid out in the legal provisions. Unfortunately, the oversight bodies may sometimes lack adequate tools to carry out their full function. Recent advances in data science and bioinformatics may further complicate the process as the parameters may become “moving targets.”

DACs provide an extra layer of oversight over the research ethics committee oversight which is given at the start of the research. They receive direct data access requests from researchers and either approve or disapprove their access to data. As much as they are not mentioned in the GDPR, they have a crucial role to play in the governance of data access and data sharing in compliance with the overarching GDPR principles.

Data Access Models in the View of the GDPR

The governance of biobanks in view of the GDPR has three major models of data access: open access, controlled-access, and registered access.

Open-Access

Open-access models means that the data is available through various online platforms and can be easily accessed without any constraint. This is mainly used when the data being shared is mainly aggregate data and not personal level information.

Controlled-Access

In this model, data controllers set rules to limit access to health and genomic data. Data Access Committees (DACs) may be used to review data access requests and either approve or disapprove them. Data access agreements are used to ensure accountability and prevent the potential misuse or abuse of the protected data.

Registered Access

Registered access is mostly used for data that is low risk (or non-stigmatizing) and access granted to bona fide researchers who have to be registered. This model requires authentication, authorization and attestation.

Biobanking Challenges Created by the GDPR

The GDPR fails to provide clear legal guidance on the processing of personal data for secondary research purposes. The GDPR interpretation of pseudonymized and anonymized data as identifiable data (recital 26) have a far reaching impact on the implementation of privacy laws.

Pseudonymized Data

As defined in Article 4(5), this is data that ‘can no longer be attributed to a specific data subject without the use of additional information, provided such additional information is kept separately and is subject to technical and organizational measures to ensure that the personal data is not attributed to an identified or identifiable natural person’.

In summary, this refers to key-coded data which can be (potentially) traced back to research participants but still preserves the de-identification of the personal data in the day-to-day operations. Consequently, pseudonymized data is considered to be personal data which falls under the scope of the GDPR.

Anonymized Data

This is where the GDPR differs conspicuously from the Health Insurance Portability and Accountability Act (HIPAA) and other data protection laws. The GDPR’s definition of anonymized data is contextual. In some instances, if there is a ‘reasonable likelihood’ of re-identification, the data is considered as non-anonymous.

In this regard, key-coded data sets must be treated as fully identifiable data and are therefore subject to all requirements that apply. This imposes a new compliance obstacle to biobanks that routinely hold biospecimens and the related phenotypic and demographic data for secondary research purposes.

The GDPR also places restrictions on the cross-border transfer of personal data outside the EU. It has specific conditions for transferring data and biospecimens to non-EU countries. These materials can only be transferred to countries that implement similar standards to protect subjects’ privacy as well as their rights and freedoms.

Secondary research refers to research conducted using data or biospecimens that were collected for a different research or for non-research purposes, this includes clinical care.

‘Research Exemption’ in Light of the GDPR

Article 89(1) of the GDPR emphasizes technical measures that are needed to safeguard the rights of the data subjects during the collection and processing of such data for purposes of scientific research, but this has certain exemption rules.

Article 89(2) of the GDPR grants Member States some rights to exemptions from some of the data subjects’ rights. However, a certain threshold must be met for these rights to be waived:

1. Exemption must be necessary for the research purpose to be fulfilled
2. Failure to exempt will seriously impair the research process

These exemptions may be seen as an impediment, in light of the ethical requirements, to the protection of the privacy, autonomy, and confidentiality of the study participants.

Why Should Biobanks Comply with the GDPR Rules

The GDPR has both an oversight mechanism and a sanctions mechanism. The sanctions may come in the form of liability and compensation or administrative sanctions. Indeed, the huge potential for sanctions and administrative fines are precipitating factors for compliance with data protection laws.

How Can a BioSpecimen Management System Help Biobanks Overcome Regulatory Challenges Imposed by the GDPR?

A regulatory-compliant, configurable biospecimen management system can help biobanks overcome logistical and regulatory challenges and comply with GDPR privacy requirements. A biospecimen management system can help biobank staff to adhere to validated standard operating procedures (SOPs) while tracking and managing archived samples and active samples from multiple studies. Furthermore, it can help to harmonize and integrate data from different sources while adhering to GDPR data sharing requirements.

Conclusion

The General Data Protection Regulation (GDPR) was created to protect individuals’ personal data. However, it can place considerable constraints on the scientific research process. This may also pose a significant risk for biobanks that fail to comply with the GDPR and subsequent sanction risks are an imminent risk.

A biobanking LIMS solution allows biobanks to adhere to the strict GDPR requirements by limiting access to the data, providing a complete audit trail, and ensuring that data integrity is maintained through the entire biospecimen and data lifecycle.

What is a Biobank Information Management System (BIMS)?

Specifically designed for biobanks and biorepositories, a BIMS provides an ideal solution to manage and track samples. A BIMS records and manages donor information, including donor consent. It keeps records of all specimens whether in process, storage, or shipment. Along with collecting, storing, and processing specimens, it also supports ISBER Best Practices recommendations and biobanking regulatory requirements. A BIMS not only helps in the secure management of sample and patient data but also assigns role-based access to authorized users, removes data silos, and generates personalized reports.

Importance of a Biobank Information Management System (BIMS)

Biorepositories are a key element in a growing number of organizations in biotechnology, pharmaceutical, and clinical research. Biobanks need to follow stringent regulatory guidelines and have data security measures in place as they contain biological samples from different sources and also sensitive patient data including their medical records and demographic information. The set-up and operation of a biobank also require legal, ethical, and safety considerations that not only pose challenges in managing the vast amounts of data collected from biosamples but also ensuring compliance with the regulatory requirements, such as HIPAA, 21 CFR Part 11, ISO 20387. Apart from this, biobanks also face numerous challenges such as managing biospecimens and patient data, tracking stored samples, automating workflows, assuring sample integrity, and following regulatory guidelines. This calls for the necessary safety framework, standardization, and harmonization of sample collection, processing, and storage protocols. Deploying a robust and configurable biospecimen management system to manage biobanking data and meet workflow automation requirements can assist biobank managers in streamlining day-to-day processes, ensuring reproducibility and traceability of workflows, and thereby preserving sample integrity.

Top Factors for Choosing a BIMS

Biobanks differ in size or capacity. Additionally, the set-up and operation of a biobank require various legal and ethical considerations. To make sure you choose the right one, we have enlisted the crucial factors to consider before deciding on a biospecimen management system. Primarily, it is best to spend some time brainstorming about the most significant issues and the pressing needs as well. The very first we could consider is,

 

 

1. Data Management & Collaboration

The essential task of any BIMS is managing samples and associated metadata. Biobanking nowadays is as much about data storage and management as it is about the storage of high-quality samples. With the increase of omics technologies and incoming samples, biobankers have observed an exponential increase in data generated per sample. Since each new technology comes with its own data processing peculiarities, it also accompanies diverse file formats. Therefore, a good BIMS must have the functionalities required for sharing different file types to address the needs of all collaborative partners. Apart from this, it is also necessary to keep in mind the personalized data management needs of your biobank. This may include getting a comprehensive or specific overview of the biobanking processes, the need to quickly trace records, or the need to collect comprehensive information on not only samples, but also patients, questionnaires, or protocols.

2. Scaling Options

Once a streamlined data flow is ensured, it is important to consider what scaling options does the software offer. Many times biobanks exist in organizations that also conduct clinical trials or pre-clinical research. In such cases, the data management process is more challenging since it involves the harmonization of data types from multiple sources to setting up and automating necessary workflows to streamline various processes. Hence, it becomes necessary to ensure if your biobanking software meets the complex and diverse data management needs of your biobank. A biobanking LIMS must also have the option to add or remove users when you scale your operations. It is best to choose a system that could be upgraded seamlessly according to the requirements of your biobank.

3. Data Integrity Features

In a biobank, the sample data commonly change over time. To track sample data changes, a BIMS must be able to capture and record every change made by all users to every sample record with a date and time stamp. A biobank must retain a history of its sample data changes to support data accuracy.

A biospecimen management system functions more effectively when it is integrated with other systems and applications in a biobank. Instrument and software integration facilitates data interoperability between different systems, eliminates data redundancy, and automates workflows. It also improves the data quality and integrity by eliminating transcription errors. It saves a lot of time as every process is automated. A BIMS must be integrated with software such as Laboratory Information System (LIS), Electronic Medical Records (EMR), temperature monitoring systems for smooth management of samples and associated data.

4. User-Oriented

Before zeroing in on a biobank management software, it is worth considering the opinion of all users. An effective BIMS should be easy to learn and intuitive to navigate, accessible to users outside the organization for easy collaboration, and have the functionality to assign different role groups with varying permissions and restrictions. Each biobank should map out all potential users who could be lab technicians, coordinators, lab managers, and evaluate if a BIMS can meet the distinct requirements of all users. A correctly chosen BIMS ensures maximal efficiency at all stages of the biobanking processes by aligning with users’ convenience and requirements.

5. Privacy, Security, and Compatibility

In addition to serving research needs, biobanks also need to comply with necessary regulatory requirements such as HIPAA, ISO 20387, EU GDPR, and others. Patient privacy is of utmost importance for biobanks as they not only store sample data but also maintain donor data. Hence, it is crucial to choose a biospecimen management system that allows the sharing of information with researchers intending to use the samples for research without compromising data security and privacy. Although patient privacy must be maintained but not at the expense of limiting sample availability. A good BIMS should therefore address confidentiality issues while ensuring a secure chain of custody and efficient data sharing among collaborating research institutions.

6. Research and Networking

Current research practices frequently involve collaboration with contract research organizations (CROs). Biobanks and biorepositories need to make sure that they provide high-quality services to these organizations in a cost-effective manner. Deploying a unified system also smoothens the flow of information and communication. Furthermore, a system can be configured to meet the evolving demands and enable efficient data transmission in addition to ensuring procedural compliance.

Conclusion

Choosing a BIMS for sample management at your biobank could be a complex and time-consuming process. Although there may be features that may not contribute much value, certain key features are essential when it comes to choosing a biobanking LIMS software. An effective BIMS should be configurable according to your specific needs so that it can capture any data elements and data fields related to your samples. It should be able to record the precise location of every sample in your biobank. Biobanks usually have numerous samples and hence a good BIMS should enable you to create and batch update a considerable number of sample records. A biospecimen management system should maintain a record of the history of every sample information, be it freeze-thaw cycle count, processing details, or storage location. This functionality is also essential to meet regulatory requirements. A BIMS should enable you to search and filter through samples to retrieve specific sample records, allowing you to easily and quickly respond to requests for specific samples. These crucial factors must be considered while selecting the right BIMS.