Andrew Radin

CYT997 is a potentially efficacious and non-toxic drug candidate for HCC therapy. Its ability to down-regulate GPC3, β-catenin, and c-Myc highlights a novel mechanism of action.

Rheumatoid arthritis (RA) is an area of active drug development, with over 100 candidates in clinical trials. However, most of those drugs act on a small number of immunomodulatory targets. Drug candidates that act through new targets or mechanisms could expand treatment options for RA. We applied an integrative biomedical-informatics-based approach and in vivo testing to identify new drug candidates and therapeutic targets that could form the basis for future drug development in RA. A… Show more

Rheumatoid arthritis (RA) is an area of active drug development, with over 100 candidates in clinical trials. However, most of those drugs act on a small number of immunomodulatory targets. Drug candidates that act through new targets or mechanisms could expand treatment options for RA. We applied an integrative biomedical-informatics-based approach and in vivo testing to identify new drug candidates and therapeutic targets that could form the basis for future drug development in RA. A computational model of RA was constructed by integrating patient gene expression data, molecular interactions, and clinical drug-disease associations. Drug candidates were scored based on their predicted efficacy across these data types. FDA-approved treatments for RA were significantly enriched among the top-ranked candidates (p = 1.7x10-15). Ten high-scoring novel candidates were subsequently screened in the collagen-induced arthritis model of RA in rats. Treatment with three candidates, exenatide, olopatadine, and TXR-112, significantly reduced ankle size, alleviated limb inflammation, improved joint histopathology, and improved mobility as observed using a novel digital motion endpoint. These three drug candidates do not act on common RA therapeutic targets; however, links between known candidate pharmacology and pathological processes in RA suggest hypothetical mechanisms that could contribute to the observed efficacy. Future studies will help elucidate druggable targets, pathways, and mechanisms that could contribute to each candidate's efficacy in RA. The candidates may be modified and optimized to increase efficacy. Targets identified in these studies could also be the basis of new drug discovery initiatives.

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Using electronic health records (EHRs) and biomolecular data, we sought to discover drug pairs with synergistic repurposing potential. EHRs provide real-world treatment and outcome patterns, while complementary biomolecular data, including disease-specific gene expression and drug-protein interactions, provide mechanistic understanding.

Vertex coloring of graphs is an NP-complete problem. No polynomial time algorithm is known to color graphs optimally. The best we can do to handle vertex coloring of graphs is to create heuristics which provide a guess as to an optimal coloring. This thesis examines a number of known vertex coloring heuristics, and compares their performance to a brute-force optimal coloring. These comparisons are made for relatively small graphs with low numbers of vertices. The behaviors of the existing… Show more

Vertex coloring of graphs is an NP-complete problem. No polynomial time algorithm is known to color graphs optimally. The best we can do to handle vertex coloring of graphs is to create heuristics which provide a guess as to an optimal coloring. This thesis examines a number of known vertex coloring heuristics, and compares their performance to a brute-force optimal coloring. These comparisons are made for relatively small graphs with low numbers of vertices. The behaviors of the existing heuristics is examined to aid in the creation of new heuristics. The new heuristics are compared against the existing heuristics for both all small (n < 12) and relatively large random graphs. The result of this thesis is two new graph coloring heuristics. The first heuristic, the so called double interchange, provides the best coloring performance of the heuristics studied for small, connected graphs. The second heuristic, the annealing interchange, provides the best coloring performance of the heuristics studied for larger, random graphs.

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