My group performs research that is broadly focused on drug discovery and pharmacoinformatics with a strong emphasis on the interface among structural bioinformatics, chemoinformatics, and clinical informatics. We pursue this research on three fronts: (1) development of novel algorithms and continued enhancement of the Computational Analysis of Novel Drug Opportunities (CANDO) multiscale drug discovery platform, (2) data analytics applied to electronic health records and other patient-centric datasources to identify and understand risks associated with various diseases, and (3) application of our predictive and generative methods to numerous diseases, including non-small cell lung cancer (NSCLC), COVID19, and opioid misuse, abuse, and overdose, with the goal of greater understanding of these indications and design of therapeutics to treat them. I lead a data-centric computational group who leverage multiple heterogeneous datasets and libraries, e.g., chemicals, macromolecular targets, diseases/indications, electronic health record, and medicaid claims, all towards greater understanding of drug effects and mechanisms of action in a multiscale manner. My group, in close collaboration with Prof. Ram Samudrala, has integrated many data sources into our CANDO platform as part of our continuous effort to improved generation and prediction of small molecule therapeutics. We have also developed software tools and platform extensions for drug-drug interaction prediction within CANDO, RNA editing site identification (RNAsee), and small molecule-protein binding affinity prediction using machine learning (BARDOCK), and deep learning based drug design using proteomic level objectives (CGGM). My group is currently focused on applying many of our developed methods to different indications and disease areas. First, we have applied the repurposing component of CANDO towards discovery of an effective therapeutic to treat COVID19 and/or related symptoms using already approved drugs. Secondly, we have pursued designing and synthesizing novel therapeutics for NSCLC. A much larger area of our research pertains to addiction and the opioid crisis, which involves the (1) design of novel non-addictive analgesics and/or overdose rescue drugs and (2) clinical analytics applied to a large corpus of client and claims data for alcohol use disorder patients towards illuminating overdose/abuse risks and prediction of outcomes based upon patient information. We collaborate with numerous groups in academia and industry to accomplish our research goals. Through these close collaborations and our research program, our group strives to integrate bioinformatics, clinical informatics, data science, and computational chemistry towards identifying, elucidating, and mitigating biological and clinical problems.