Building trust in clinical trial patient matching: Takeaways from DPHARM 2025

At this year’s DPHARM conference, Sano’s VP of Commercial, Ben Jackson, joined a panel on clinical trial patient matching moderated by a clinical expert from Novartis. Panelists included representatives from sponsors like BMS and Merck, vendors like Tempus, and research sites too – all sharing perspectives on one of the industry’s most pressing challenges: how to effectively match patients to trials while building trust across the ecosystem. In this blog, we highlight some key takeaways from the discussion.

Patient matching technology models

The panel opened with a discussion on how different organizations are approaching patient matching, revealing a wide variety of techniques. This included:

• Tempus: Evolved from a genomics provider to a fully integrated electronic medical records (EMR) partner. Their model combines AI-driven first-pass matching with verification from oncology nurses, and secure data exchange with sites for both structured and unstructured data. 
• Sano Genetics: Focused on rare diseases, Sano emphasizes genetic testing as well as patient education and contextualization of genetic diagnoses. This ensures patients arrive at sites better prepared for conversations about research participation, bridging the gap between a diagnosis and trial readiness. 
• Avera Cancer Institute (site): Shared success with just-in-time trial models, including five protocols opened last year with Tempus as a key partner. They emphasized the value of combining AI with human verification to reduce site burden. 

Who should pay for patient matching?

The panel reached broad consensus that sponsors should fund patient matching as part of their recruitment strategy. However, alternative funding approaches were also discussed, including pass-through costs via clinical trial agreements (CTAs), site-vendor arrangements, and mixed-model approaches for network-agnostic solutions. 

One challenge raised was how attribution and return on investment (ROI) can be calculated when multiple recruitment channels contribute to enrollment. For instance, Bristol Myers Squibb’s approach is to invest upfront and assess ROI after implementation.

Success metrics beyond randomization

Patient matching cannot be judged by randomization alone. Panelists suggested new metrics such as:

• Patient pull-through rates (from consent to cycle 1, day 1)
• Match accuracy against sponsor-defined criteria
• Site usability and feedback
• Pricing models linked to patients reaching treatment, reflecting confidence in the matching process
• Emerging need to measure patient motivation and engagement, not just data alignment

Expanding beyond oncology

Patient matching is most advanced in oncology, where the challenges of identifying eligible patients are especially acute. However, the value of the approaches developed in oncology are adaptable and have moved into other therapeutic indications. Rare disease programs in particular require diverse channels such as academic centers, community practices, and digital advocacy networks.

Accountability across stakeholders

Another recurring theme was accountability and open communication in the industry. This covered various stakeholders and multi-way interactions. For instance:

• Sites → sponsors: Share what’s not working and provide process feedback.
• Sponsors → vendors: Understand and respect decision-making layers in legal, compliance, and budgeting.
• Vendors → All stakeholders: Recognize that these technologies are evolving and commit to transparency and iteration.

Collaboration, rather than competition, was emphasized as the key to building a sustainable patient-matching ecosystem. 

Looking ahead

The panel closed with a call to action on several fronts:

• Pursue creative funding mechanisms for patient matching
• Develop attribution solutions for multi-channel recruitment
• Create metrics for patient motivation and engagement
• Scale successful oncology models into other therapeutic areas, including rare disease

These steps can help accelerate clinical trials while fostering trust and enhancing patient engagement. The next phase of innovation will be less about technology alone and more about how we collaborate across stakeholders to ensure patients are matched not only efficiently, but ethically and meaningfully.