Sapient’s Post

Transcript

Now when we think about this personalization of therapy, we oftentimes think about the host, the individual themselves and what we find, while all of us are slightly different, the differences between us are really quite minimal, whether it be through genetic variation, lifestyle variation, etcetera. We really are fundamentally not that dissimilar from one another. However, what is very different from one individual to another individual is our actual disease and our disease processes. While we think of disease as this singular event, oftentimes which is defined by a pathologic finding on biopsy, we know diseases have many, many different etiologies that allow you to go from a normal phase to an abnormal state. Being able to classify disease according to this subsetting of pathobiology is critical towards this personalization of therapy. Now of course we've seen this evolution occur in the cancer space whereby the use of these markers to subset cancer has really proven transformative. When we think about lung cancer, going back approximately 40 years ago, our traditional view of lung cancer was really one of that broke down into three categories, again largely based upon underlying pathology, or how it looked on a pathologic specimen. And of course this is the classic breakdown of adenocarcinoma versus squamous cell carcinoma versus large cell carcinoma. As this advanced in the early 80s, we began to identify that there are molecular markers that can denote specific subsets of lung cancer according to particular mutation status. And that allowed us to subset lung cancers initially into KRAS positive versus KRAS negative, and subsequently, KRAS and EGFR positive in the early 2000s. And if we look today, there are dozens of subsets of lung cancer, each of which is defined by a specific biomarker that denotes the mechanism by which tumor genesis has occurred. And of course for any of us in this area that works in drug development, typically therapies are targeted towards specific subsets of these individuals based upon this biomarker. Now this has obviously worked quite well using genetics in the oncology space, particularly since these genetic measures allow us to subset tumors according to their molecular pathogenesis, but what about what happens when we think about the non cancer space? Are there other markers that we can leverage for which genetics may not be ideal to identify subpopulations of disease?