How do we support the validation of predictive biomarkers together with the development companion diagnostics? That’s the question that Clare Balendran, Vice President and Head of Translational Development at Novo Nordisk, sets out to answer in her presentation.
Balendran has over 15 years of experience in monitoring biomarkers, companion diagnostics, and diagnostics in large pharma. She’s worked at all stages of the drug discovery and development process, from early pre-projects which build biomarker hypotheses right up until due diligence and licensing. The Translational Development department at Novo Nordisk focuses on biomarkers from phase one decision making to patient selection in later phases.
Balendran showed an all-too-familiar slide showcasing the textbook drug-diagnostic co-development model. This model neatly tracks the drug development pipeline: biomarker selection (research), feasibility studies (preclinical), prototype assay (phase I), analytical validation (phase II), clinical validation (phase III), regulatory submission, and post approval.
However, as Balendran notes, this tidy and linear pathway does not end up being the case in practice. In Balendran’s 15 years of experience, she has never had an example of a project being this straightforward. While the textbook approach to drug and diagnostic co-development is ideal, in reality, biomarker selection and feasibility often take longer, pushing diagnostic development into later phases.
Therefore, diagnostic development is squeezed to fit the uncertainties of novel drug development. This is the case for a variety of reasons. Interventional studies are required to identify or validate predictive biomarkers for novel drug targets. The attrition rate of early projects restricts broad frontloading and at-risk investment Increased pressure on trial designs with fast and lean development programmes. And broad non-selected populations are still seen as preferable options outside of oncology.
Balendran said that the way to mitigate this is through effective panning and strategy. Effective planning, including preclinical and retrospective clinical studies, and aligning project strategies between diagnostic and clinical teams are crucial for success. It is also important to be aware of risks. Having flexible strategies and being prepared to adapt to changes are essential for successful biomarker and diagnostic development.
