Labiotech article: "Rethinking precision oncology drug development: AI and tumor biology for smarter therapeutic programs"
We are happy to share our latest article on how Indivumed is advancing precision oncology by combining patient-derived tumor biology with AI-driven data integration.
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Why do so many promising cancer drugs fail in late-stage clinical development?
In our latest Labiotech article, we explore how the answer often lies in decisions made much earlier in the R&D process. Successful precision oncology starts with a deep understanding of tumor biology and the ability to identify the right therapeutic target, the right treatment modality, and - most importantly - the right patient population.
By combining our globally standardized biobank of high-quality patient samples with comprehensive clinical data and multi-omics analyses, we generate a detailed, biologically relevant understanding of cancer. This enables us to identify novel therapeutic targets, define patient subgroups with greater precision and validate new approaches using patient-derived models that closely reflect human disease.
As Dr. Jonathan Woodsmith, our VP Therapeutic Development Program, explains: "To develop targeted, effective therapies, our R&D team starts as close to the patient as possible. We ask: What is the right target for this disease? Which patient group will truly benefit? And what modality will best deliver on that promise?"
Our article highlights the critical role of AI. Integrated across our R&D workflow, it helps bridge research and clinical application to support processes in target identification, patient stratification and modality selection.
We are pleased to share this new article, featured online on Labiotech.