Transforming Drug Development with “Virtual Clinical Trials”
Feilim Mac Gabhann seeks to improve drug discovery with an innovative modeling approach.
Hopkins researcher Feilim Mac Gabhann, Ph.D., has always been interested in the ability of computers to solve complex health problems. Combining this interest with a background in chemical engineering, Mac Gabhann uses innovative computational models to discover and evaluate new therapeutics in an approach that may transform the drug development process.
To evaluate the effectiveness of a new treatment, Mac Gabhann and his lab members build comprehensive, multi-scale models that predict not only how a drug interacts with its intended molecular target, but also how this interaction will be influenced by the surrounding cellular processes. As Mac Gabhann explained, “The [drug’s] target is part of a community; it interacts with and competes with proteins in this community.” To adequately represent this interconnectedness, Mac Gabhann incorporates detailed mechanistic research into his models and compares his simulations with experimental results.
Mac Gabhann then takes his models a step further. He runs what are known as “virtual clinical trials,” in which patient gene expression data are used to predict the effects of one or more drugs in individuals. These simulations can be used to identify whether certain subsets of patients are more likely to respond well to particular therapeutics. This method embodies an improvement over standard clinical trials, which typically evaluate only one drug at a time and are powered to find overall, rather than subgroup, effects.
By efficiently evaluating drug effectiveness, Mac Gabhann’s approach has the potential to both personalize treatment strategies based on patient characteristics and reduce the costs associated with developing successful drugs (estimated at $800 million per drug*). Although these models must be validated to fully demonstrate their utility, the broad applicability of Mac Gabhann’s methods – his current projects include applications in cancer, cardiovascular disease, and HIV treatments – hints at a brighter future in therapeutics research.