Every cancer is unique. This fundamental reality has motivated innovation in drug development in precision oncology over recent decades, such that now ~half of cancer drug approvals use biomarkers to match the therapy to patients most likely to respond and see more durable outcomes. However, with ‘blockbuster’ targets like EGFR, HER2, and PD-L1 now heavily capitalized, the focus has continued to shift to rarer cancer subtypes, including lesser-known mutations as well as subtypes within subtypes to address the considerable heterogeneity between patients as well as within and between different types of tumors. With only 7.1% of cancer patients in the US participating in clinical trials, the requisite level of biological, mutational, and tumor diversity simply cannot be found among traditional trial cohorts. Drug targeting is like finding a needle in a haystack – but is handicapped by searching in only 7.1% of that haystack.
It has become more critical than ever before to de-risk drug development programs with (1) deeper clinico-genomic understanding of the mechanism of disease and link this to (2) measurement of an asset’s commercial prospects. Real-world data can help illuminate this, so that a greater diversity of patients and disease can be studied systematically to improve the odds of successful biomarker discovery and drug targeting. Strategic application of real-world data evidence can significantly enhance the development and commercialization of targeted oncology therapies by providing insights into patient and tumor heterogeneity, improved cohort selection, substantiated regulatory approvals, and efficient post-market surveillance.
In this session we will be discussing:
- The role of real world data (RWD) & analytics: as new sources of clinico-genomic data and new methods (e.g., natural language processing [NLP], artificial intelligence [AI]) are emerging at rapid pace, can the use of real world evidence (RWE) be optimized to close gaps in target identification/biomarker discovery, indication prioritization, and disease & market understanding?
- Strategic challenges in precision oncology: what are the barriers to mapping disease pathways and profiling possible patient targets? Where do investors need reassurance that a development program isn’t just a shot-in-the-dark but rather a well-informed drug targeting endeavor that addresses a true and significant unmet need?
- Approaches for navigating these uncertainties: how should drug developers balance scientific rigor vs. costs to get the inputs needed to effectively guide development efforts? When is a 4/10 vs. a 9/10 answer acceptable?
