Precision medicine is reshaping drug development. Improved biological measurements are enabling evidence-based decisions to be made regarding patient selection, response and variability. In many programmes, biomarker data quality determines whether this personalised approach to healthcare is achieved in practice or remains aspirational.
At its core, patients differ. Even within the same diagnosis, condition-related drivers, immune profiles and disease stages can significantly affect treatment efficacy and safety. Delivering more tailored therapies therefore requires a deeper, data-driven understanding of patients.
Prognostic, diagnostic and predictive biomarkers are central to this. They enable researchers, drug developers and clinicians to stratify patient populations and interpret both disease biology and treatment-driven biological responses with greater confidence. Emily Letton speaks to Ardena’s Jeremie Trochu to dive deeper into the subject of biomarkers in precision medicine.
From biomarker strategy to actionable insight
Selecting a relevant biomarker demands alignment with disease pathology, the mechanism of action of the therapy and the practical realities of how the biomarker is used. A biomarker that cannot be implemented consistently or doesn’t support a clear decision risks becoming an academic signal rather than a development tool.
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