I was born in India, but raised in multiple countries. After obtaining my Bachelor’s degree in Chemistry at Mount Holyoke College, where I studied the surface hydrophilization of poly(dimethylsiloxane), I joined RPI for my graduate studies in Chemical Engineering in 2015. My initial research focused on examining Alzheimer’s Disease experimentally and computationally through molecular dynamics. I am currently working on utilizing AI and machine learning tools in the field of drug toxicology.
M.S. in Chemical Engineering, Rensselaer Polytechnic Institute, Dec 2015
B.S. in Chemical Engineering, Rensselaer Polytechnic Institute, May 2013
I am coadvised by Prof. Jonathan S. Dordick and Prof. James A. Hendler. My research focus is on the use of AI and machine learning to enhance the accuracy of predicting drug toxicity from the myriad data that exists in vitro, in vivo and from human clinical records.
In the past decade there has been a dramatic increase in the number of new chemical entities (NCEs) and screenable drug targets due to combinatorial chemistry and advances in omics technologies. Nevertheless, these advances have poorly translated into new drug approvals, because of difficulties in accurately predicting drug efficacies and toxicities in humans, in part due to inherent differences among individuals. Moreover, poor concordance between in vitro and animal tests to human toxicity results in drug toxicity being a major limiting step in drug discovery. Thus, it is critical to improve this concordance and with the large amounts of a variety of in vitro and in vivo data that has been collected to decipher potential drug candidates’ toxicity, a machine learning approach provides an excellent starting point to use to better predict human outcomes.