The first is an emphasis on helping our development teams make informed decisions on key assets across the pipeline – from oncology and hematology to immunology, fibrosis and cardiovascular diseases. We are looking for data around biomarkers that can help guide patient stratification, or data regarding the selectivity of a compound, to name just a few, all with the intention of guiding programs in an efficient and efficacious manner. To use an example from our pipeline, our teams work to reverse-translate biomarker data from our solid tumor oncology programs back into research and early development, applying key learnings to drive decision-making for our next generation of cancer medicines.

The second pillar is more exploratory in nature and is focused on helping to build a greater understanding of our assets – in other words, researching how an investigational asset is different from existing therapies mechanistically and in which scenarios or patient populations it may be most effective. An example of this in practice is the work the team has done to refine our understanding of the TYK2 pathway, which plays a key role in several immune-mediated diseases distinct from other therapeutically targeted pathways.

Finally, the third pillar is where the translational medicine team leverages genetic, genomic, and molecular profiling to inspire and guide new opportunities and areas of research. This work sits above any particular asset, utilizing computational research, artificial intelligence, machine learning and other sophisticated technologies to garner robust insights from our clinical trials, partner trials and real-world data to make larger conclusions about key disease areas. This could help us refine therapeutic hypotheses or explore indications; it also helps our scientists better understand difficult to treat diseases as they work to build a framework for new research.

At Bristol Myers Squibb, we place a strong emphasis on human biology and large-scale clinical data sets, which inform our work across the pillars but particularly guide pillar three. We use this data to guide decisions that fuel the next wave of drug discovery, enabling focused purpose and innovation in our scientific research.