Precision medicine holds immense potential not only within oncology but also across chronic diseases, which affect billions of people and account for more than 80% of the $10T healthcare spending worldwide. Chronic diseases represent populations with huge unmet medical need, whether that is as basic as having their disease diagnosed quickly and accurately (as with endometriosis, long COVID or ME/CFS), or finding new therapeutic options and tools to help select the right therapy for a specific patient.

Chronic diseases such as endometriosis, cardiovascular disorders, diabetes, neurodegenerative conditions, and autoimmune diseases are very often multifactorial in nature, resulting from combinations of genetic predisposition, environmental influences, and lifestyle factors. Like cancer where different mutations respond to different medicines, this means that within a disease population, a treatment which is effective for one subgroup of patients may not be effective for others with the same diagnosis. However, because combinations of multiple genes and other factors are involved, identifying the real drivers of complex diseases has been more challenging.

The opportunity for biopharma is in understanding which targets and treatments will work for each distinct subgroup of patients within a single diagnostic label. By revealing these drivers of disease with mechanism-based patient stratification, I will share a new combinatorial approach that is now enabling precision medicine in multiple complex chronic diseases.

As our understanding of complex disease biology continues to advance, we will see precision medicine becoming a central pillar of how we approach and manage chronic diseases, with personalized diagnosis, treatment, and prevention strategies that are tailored to the specific needs of patient subgroups, ultimately improving patient outcomes and quality of life.

April 4, 2024