Trends in Industry Collaborations: How Biobank Providers Can Better Align with Research Requests
Based on a recent analysis of sample and data requests received by Specie Bio, clear trends are emerging in what industry researchers need from biobank providers in 2025. For providers looking to maximize collaboration match rates, understanding the shift toward deeply annotated, multi-modal datasets is critical.
The following are the high-level trends shaping biospecimen and data demands today:
1. Blood Derivatives And Tissue Outpace Other Sample Types
Demand is exceptionally heavy for both oncology tissues (such as FFPE) and blood derivatives (including PBMCs, whole blood, plasma, and serum) compared to other sample types. Because the immune system is a cross-cutting theme across cancer, autoimmune, infectious, and metabolic diseases, PBMC demand is high across the board, mirroring the consistent need for oncology tissues. In fact, both FFPE tissue and PBMCs rank among the most frequently requested specimen types making both of these sample types highly strategic and safe investments for biobanks
2. Oncology Focus: Specific Sub-Diseases Lead the Way
Oncology remains the largest major category, driving the majority of all requests. Within this space, industry researchers are heavily focused on specific sub-diseases. The highest demand is seen in lung cancers, breast cancers, and hematologic malignancies/blood cancers.
3. Key Patterns Beyond Oncology
While cancer research dominates, several non-oncology categories are driving significant sample volume:
Immunology: Because immune biology touches on many different fields, the demand for Peripheral Blood Mononuclear Cells (PBMCs) is strong even outside of cancer and spans across autoimmune diseases, infectious diseases, and metabolic conditions. Additionally, for autoimmune conditions, researchers frequently request more than just a single time-point sample. As a result, capturing serial sampling, treatment exposure annotations, and progression or response data are of higher demand.
Cardiometabolic Diseases: There is a major need for large-volume plasma, stroke imaging paired with genomics, and obesity/metabolic drug exposure cohorts.
The Critical Need for Healthy Controls: A considerable portion of requests explicitly require healthy controls. Researchers are looking for age-matched controls, pre-disease baseline samples, and normal tissue adjacent to tumors. Providers should systematically collect and deeply phenotype healthy controls, not just disease cases.
4. The Push for Multi-Modal Datasets and AI
Based on our analyses, the highest-value requests tend to combine samples with multi-modal data.
Growing Data Requests: There is a growing trend for digital pathology images and slides (H&E, IHC, WSI), which accounts for many of the data requests. Genomics and longitudinal outcomes are also highly requested.
The Rise of AI/ML: Artificial intelligence and machine learning model development is a rapidly rising research aim. Foundation model training and pathology image modeling require large case numbers, clean annotations, and highly standardized metadata.
5. Longitudinal Tracking is a Major Driver
Researchers increasingly require serial sampling, treatment exposure annotations, and progression or response data across various diseases. Collecting only single-time-point samples is becoming less in demand. Common "must-have" criteria for samples now typically include one or a combination of treatment/therapy annotations, pathology annotations (stage/grade), and longitudinal survival data.
Some Strategic Takeaways for Providers
To maximize industry match rates, providers could align with these high-level demands:
Integrate Data: Datasets that link biospecimens to digital pathology, imaging (CT/MRI), genomics, and clinical outcomes win the most collaborations.
Systematically Collect and Deeply Phenotype Healthy Controls While it is common to focus primarily on disease cases, a considerable fraction of industry requests explicitly require healthy control samples. Researchers are actively seeking age-matched healthy controls, normal tissue adjacent to tumors, or pre-disease baseline samples.
Optimize Datasets for AI and Machine Learning Readiness Projects driven by Artificial Intelligence and Machine Learning— such as foundation model training, pathology image analysis, and AI-based biomarker discovery—are rapidly rising. To attract these collaborations, providers can design datasets that favor large case numbers, clean annotations, and highly standardized metadata.
Maintain Flexibility in Storage and Handling Workflows Looking at top storage requirements, FFPE blocks remain highly requested, but there is also a very strong demand for fresh (time-sensitive) samples, fresh or frozen flexible formats, and cryopreserved materials.
Track the Patient Journey: Prioritize longitudinal tracking over single-point collection.
Interested in learning how your biobank can better align with researcher demand? Reach out to us —>