Deriving Drug Discovery Value from Large-Scale Genetic Bioresources: A Workshop
The beginnings of the successes from the human genome project are now evident, with novel technologies and therapies based on genomic information being implemented in clinical practice. However, at the same time, the cost of developing new therapies has been on the rise. New pharmaceuticals are estimated to cost on average more than $2 billion to develop and take 10 years to bring to market. With the number of new drug approvals by the U.S. Food and Drug Administration remaining fairly constant over the last 60 years, these rising development costs have led many pharmaceutical companies to examine innovative strategies to revitalize and create efficiencies in their drug development processes, including the adoption of genetically-guided strategies to reduce attrition rates and increase the odds of success. A recent analysis of approved medicines indicated that the impact of having genetic evidence for a drug indication could mean that the clinical success rate is double than that of a drug lacking genetic data support.
Several large cohort studies in both public and private sectors in the U.S. and around the world have incorporated or begun to include genetic data collection as part the study design. Recent advancements have been made in identifying potential drug targets by examining data from multiple genome-wide association studies. With the large volumes of genetic and phenotypic data that are planned to be collected, these efforts could provide a valuable trove of information for identifying and validating potential therapeutic targets, elucidation of underlying disease and mechanistic biology, and development of biomarker assays and targeted therapies. Recognizing the potential benefits of these datasets, pharmaceutical companies have started collaborating with organizations that have access to large databases of genomic information. These partnerships have spurred creative ideas for fostering innovative business models and precompetitive spaces to more fully leverage genomic data by integrating scientific and business expertise from across sectors.
Given the advances in thinking about how genetic data could be used to improve the efficiency of discovery and development of therapies for clinical use, questions remain about how large cohort studies are designed with such objectives in mind, the types of data that should be collected, and which business models could engage stakeholders effectively. The Roundtable on Translating Genomic-Based Research for Health and Forum on Drug Discovery, Development, and Translation hosted a workshop on March 22, 2016 that assessed the current landscape of genomic-enabled drug discovery and development activities in industry, academia, and government, examined enabling partnerships and business models, and considered gaps and best practices in how data from populations could be collected with the goal of improving the drug discovery process. Stakeholders, which included pharmaceutical and biotech companies, IT and data-science companies, research institutes, investors, providers, patients, payers and regulators were invited to present their perspectives and participated in discussions during the workshop.