Concept

Building massive patient repositories have intrinsic value but clearer views on how to get relevant magnitude of samples (100,000s) in most predictive modality is critical. Normally biobank ambitions will be paired with a low-regulation diagnostic service called laboratory developed tests to provide cash flow while biobank is being built.

Longer Description

We're now seeing the emergence of biobanks that go beyond mere storage facilities to become critical hubs in the healthcare and pharmaceutical ecosystem. These next-generation biobanks are not just passive repositories but active contributors to medical research, drug discovery, and personalized medicine.

The biobank landscape is currently fragmented, with various players including medical centers, individual investigators, tech transfer offices, diagnostic companies, and consumer health companies. However, the most successful biobanks of the future will likely integrate sample collection, storage, and analysis with patient testing and data aggregation.

Key challenges in the current market include:

1. The need for separate solutions for data transfer, inventory management, metadata analysis, and downstream processing across different sites.
2. Much of the data collected to date lacks immediate value for drug discovery or clinical pathways due to insufficient associated health data or outdated processing methods.
3. Quality data, in particular those combined with medical records, as opposed to large data, correlates with a higher impact in science, innovation, and disease.

Recent developments demonstrate the potential of this approach:

• Companies like Tempus and Caris Life Sciences have successfully integrated biobanking with patient testing services, creating valuable datasets for research and clinical applications such as companion diagnostics and treatment suggestions.
• The rise of consumer testing companies like Nucleus Genomics, Viome, 23andme (to a lesser degree companies like Function Health and Maximus) has shown the potential for large-scale data collection, though these often lack the depth of health data required for comprehensive research.

Other thoughts

• Right now companies struggle with profitability but the tailwinds of decreasing sequencing costs and more on-prem deployment mean different capitalization structure in the near future
• Need to understand monopolistic dynamics normally in the form of distribution moats and killer sales teams
• A ‘Tempus-for-X’ should be built for neuro, immunology, dermatology, etc. Basically all areas of medicine and health.