Disease-Specific Biobanks: How Can a LIMS Help in Data Management?

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Biobanks have a fundamental role to play in ensuring successful outcomes in clinical research by providing quality biosamples. They host donations of biological materials such as cells, DNA, and tissues [1]. They also handle data that is related to the biosamples. Biobanks are found in hospitals, research institutes, and patient organizations. The role of patients in the biobanking process is becoming increasingly important. They are no longer regarded as mere donors but as participants in designing and executing the functions of biobanks.

What are Disease-specific Biobanks?

Disease-specific biobanks store biospecimens for a particular disease. They can be a part of a wider group of disease biobanks.

Disease-specific biobanks store the profile data of the participants and the information related to the samples. The disease-specific information of each participant helps researchers to have a better understanding of the samples. New data generated from the participants and their samples from longitudinal studies can be progressively added to the biobank to provide deeper insights into the disease under investigation.

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Disease-specific biobanks have evolved from being small bio-collections to being national population-based repositories. Current disease-specific biobanks operate at an international level and are not restricted by physical boundaries. A Laboratory Information Management System (LIMS) can help manage biospecimens and maintain the seamless flow of information across a network of clinicians and researchers.

Disease-specific biobanks may target specific purposes such as diagnostics, pharmacology, or research. They have a huge potential in enhancing biomedical research and offering personalized care to patients [2].

Importance of Disease-specific Biobanks

Disease-specific biobanks are essential for the identification of new disease biomarkers that facilitate the development of personalized medicine. A biomarker is an observable and measurable indicator of a disease. This may include alterations such as protein or gene mutation found in tissue, blood, or bodily fluids.

Disease-specific biobanks enable researchers to identify biomarkers of a specific disease and predict disease progression, outcomes, and response to treatment. The samples collected may include blood, tissue biopsies, and body fluids from patients affected by the disease, such as COVID-19 or cancers. Scientists can use this information to determine a patient’s predisposition to an illness and its possible treatment response [3].

Such biomarkers can also identify the beginning of a disease like cancer, diabetes, or cardiovascular disease. This is important so that early treatment can be started to improve treatment outcomes. It is also integral for advancing personalized medicine to improve patient management and outcomes [2].

Identifying disease-specific biomarkers requires a collection of well-characterized specimens from healthy and sick individuals together with the associated clinical and pathological outcomes. Bioimages can also be collected alongside other clinical data of patients to facilitate the biomarker discovery process. The images may involve the use of computer technologies for biomarker extrapolation. Genomic research data can also be included to improve patient diagnosis.

Once the samples are collected, the biobank may follow the sample donors for a predefined period which may extend up to 30 years. This mandates specialized software to track and manage datasets over time while ensuring a high level of data integrity.

Operational Challenges of Disease-specific Biobanks

Setting up disease-specific biobanks may pose several challenges, including the following:

  • Collecting and storing vast amounts of biological samples from patients or donors, especially considering that the process is continuous and on a long-term basis.
  • Managing patient privacy and data anonymity while still ensuring that participants remain re-identifiable to link clinically relevant information to the original donor.
  • Ensuring easy accessibility, and tracking of samples.
  • Maintaining the quality of the stored biospecimens.
  • Instituting an ethical and legal committee for governance to protect the rights of both the donors and all stakeholders.
  • Choosing and implementing a biospecimen management system for data and quality management and workflow automation.

Failure to address these challenges will limit the function and efficiency of disease-specific biobanks [3].

Figure 1: A schematic representation of samples stored in disease-specific biobanks (Figure courtesy of CloudLIMS)

The Role of Commercial Biobanks in Providing Disease-specific samples

Commercial biobanks collect and manage disease-specific samples and their associated metadata to facilitate research for different types of life-threatening diseases.

A commercial biobank provides the infrastructure for collecting and storing biospecimens and supplying samples to researchers, which could lead to the development of targeted and individualized therapies. This involves the management, interpretation, and maintenance of robust and predictive datasets. A biospecimen management system helps to maintain the quality and integrity of samples and streamlines commercial biobanking workflows.

LIMS: A Turnkey Solution to Address Operational Challenges Faced by Biobanks

Disease-specific biobanks struggling to overcome operational challenges can leverage a biobanking LIMS to streamline their workflows while maintaining the safety and integrity of the molecular, clinical, and disease-specific data collected from patients.

A cloud-based LIMS plays the following essential functions:

  • Helps in the management of disease-specific collections and their associated metadata.
  • Maintains a detailed record of profile information of patients, their diseases, and samples.
  • Manages disease information, including specific characteristics and stages of each disease.
  • Enables commercial biobanks to publish and share their sample collections on the web.
  • Enables researchers to place a request for their sample of interest and track the status of their request in real-time through a secure portal.
  • Enables biobanks to monitor freezer temperature and other parameters, such as humidity, differential pressure, by integration with monitoring systems.
Figure 2: Biospecimen tracking and management software to manage patient data and associated disease information (Figure courtesy of CloudLIMS)

A biospecimen tracking & management software helps to standardize biobanking workflows, assuring sample and data quality. It enables biobanks to enforce institution-wide pre-defined SOPs for collecting and storing samples, handling and maintaining freezers, and processing orders. It provides an end-to-end solution in the management of data for disease-specific biobanks.

A biospecimen tracking and management software records the personal details of participants, including specific information about their samples and the disease. This process is vital for the discovery and development of new drugs. This may involve a multi-disciplinary approach that combines biological, bioinformatics, and medical methods to promote human health.

Because of their diversity, disease-specific biobanks are associated with a broad array of legal and ethical issues. A cloud-based biospecimen tracking and management software helps a biorepository to remain compliant with the regulatory requirements.


Disease-specific biobanks are an essential resource that grant researchers access to quality biospecimens specific to a disease. This helps in understanding the underlying pathogenesis and hence creates opportunities for the discovery of targeted and personalized therapies. A cloud-based biospecimen tracking & management software is instrumental in helping disease-specific biobanks achieve operational efficiency and assure quality and thereby promote research.

Author: Shonali Paul, Chief Operating Officer, CloudLIMS.com


  1. Kinkorová J. Biobanks in the era of personalized medicine: objectives, challenges, and innovation: Overview. EPMA J. 2016;7(1):4. Published 2016 Feb 22. https://doi.org/10.1186/s13167-016-0053-7
  2. Mitchell, D., Geissler, J., Parry-Jones, A. et al. Biobanking from the patient perspective. Res Involv Engagem. Published 2015 Jun 25. https://doi:10.1186/s40900-015-0001-z
  3. Smith, M. E., & Aufox, S. Biobanking: The Melding of Research with Clinical Care. Curr Genet Med Rep. 2013;1(2):122-128. https://doi:10.1007/s40142-013-0014-6