Lifesaving pharmaceuticals, such as penicillin and insulin, have created great advances in modern healthcare and the quality of life. However, the cost of bringing a new drug on the market is estimated to be $1.8 billion and steadily rising and there is a steady decrease in the number of new drugs on the market per billion US dollars spent on commercial drug research and development. Therefore, there is still much room for improvement in the throughput and cost-effectiveness of the drug discovery pipeline, enabling lifesaving medicines to be available to anyone who needs them and new drugs to cure more diseases. With today’s ever growing computational power at our fingertips, there is an exciting opportunity for computational scientists to leverage this power for the good of humanity.
One of my current interests is the acceleration of large scale inverse molecular docking on massively parallel machines, such as Titan (Oak Ridge National Laboratory – ORNL) and Kraken (University of Tennessee (UT) and XSEDE), which can be used to automatically investigate potential side-effects and toxicity of lead drugs, which is a common cause for drugs failing in the late stage of the drug discovery pipeline and has negative effects on the costs of successful drugs (which must compensate for the financial loss of failed drugs).
I develop efficient and easy-to-use applications that help researchers make impactful scientific discoveries. I enjoy working with researchers in many different interdisciplinary settings and helping them find ways to achieve better results while saving time and budgets.