The overwhelming majority of drugs in development fail. This is a major problem; solutions to this problem offer potential to benefit humanity by increasing the number of drugs available to treat and help ailing individuals. Drug companies have a set of tools that enable them to manipulate the biochemical properties of drugs, but the ultimate success or failure of a drug reflects how the drug affects physiological systems. This project is based on the idea better drug development strategies that result in wide and favorable therapeutic windows can be developed through the consideration of systems behaviors. The first major component of this project investigates the hypothesis that failed drugs can be converted into clinically useful drugs through co- treatment with another drug that targets the same biological network to ?open the therapeutic window?. New screening approaches will be developed that are optimized to detect therapeutic windows. These screens will then be applied to high-priority drug targets for which good drugs with favorable therapeutic windows have largely evaded development. Candidate window openers will be experimentally validated. The second major component of this project investigates the hypothesis that the mechanisms by which pathogenic variants promote disease within biological systems can be categorized into recurrent classes of ?disease network motifs?. Additionally, it is hypothesized that analysis of disease network motifs can identify targetable vulnerabilities that will apply to the different maladies that are promoted through the corresponding disease network motif. Mathematical and bioinformatic approaches will be used to classify disease network motifs and to identify their nodes that are likely to have therapeutic windows. Experiments will test the vulnerabilities identified through this analysis. One set of experiments will focus on existing drugs that can serve as archetype examples for the disease network motif vulnerabilities. The other set of experiments will utilize the disease network motif approach to identify new subsets of patients who may be treatable through currently FDA approved agents. Overall, the proposed research aims to provide a systems perspective to an area of drug development that needs new strategies to identify the drug targets most likely to result in clinically useful agent. If successful, this project could make the drug development process more efficient and more productive, in turn, providing more benefit to more patients more rapidly.
The majority of drugs in development, including drugs with excellent biochemical properties and which hit their target well, will fail because they elicit significant toxicities in non-diseased tissue and therefore do not have a therapeutic window. Here, we aim to identify strategies to create therapeutic windows for failed drugs and to establish principles for the a priori identification of drug targets likely to have a therapeutic window. We will do this through a combination of functional genomics and computational biology.
