Skip to main content

Conference Program

Subpage Hero

Loading

Streamlining Drug Repurposing: Optimizing Candidate Prioritization and Evaluating Candidates in Polycystic Kidney Disease and SETBP1-Associated Disorders

Clinical Genetics and Therapeutics
  • Primary Categories:
    • Genomic Medicine
  • Secondary Categories:
    • Genomic Medicine
Introduction:
Drug repurposing, identifying FDA-approved drugs for new indications, is a growing and promising field because it reduces the time and money required for a drug to reach the clinic. While many drug repurposing approaches have been developed, a gold standard has yet to be determined. However, researchers are capitalizing on in silico predictions incorporating increasingly available clinical, omics, and imaging data. While these often yield many potential candidates, downstream testing, especially for rare conditions, faces significant limitations due to low patient numbers, exacerbating power issues to account for critical clinical variables and effective evaluation. While attrition rates for drug repurposing studies are lower than for drug discovery (likely due to more information on safety profiles), they still often fail. Thus, prioritizing the optimal candidates for pre-clinical and clinical trials is critical, given patient needs and limited resources. In addition, patients often advocate for physicians to prescribe off-label for identified repurposing candidates from the biomedical literature, further highlighting the need for comprehensive support for identified repurposing candidates. To improve drug repurposing pipeline success rates, repurposing analyses must tackle these limitations.

Methods:
We developed a framework to implement 1) drug-specific (e.g., pharmacokinetics, drug interactions), 2) target-specific (e.g., pathways relevant to pathogenesis and pathophysiology), and 3) disease-specific (e.g., disease-associated manifestations, presentation onset, appropriate dosing) considerations, addressing these challenges in drug repurposing efforts. Our drug prioritization approach optimizes safety, efficacy, and other practical considerations like drug costs to improve pre-clinical and clinical trial success, clinical adoption, and, ultimately, patient care. Our framework for optimal candidate prioritization includes a stepwise evaluation process and vetted resources for each consideration to guide investigators in evaluating the potential clinical viability of candidates. We applied this framework to two classes of Mendelian disease as test cases: polycystic kidney disease (PKD) and SETBP1-associated disorders (Schinzel-Giedion Syndrome and SETBP1 haploinsufficiency disorder). We chose these monogenetic conditions due to their complex, varying clinical presentations (i.e., associated complications, phenotype, temporal onset, etc.), which complicate the identification of improved treatment options to slow or stop disease progression. Previously, we applied transcriptomic signature reversion approaches by leveraging the Library of Integrated Network-Based Cellular Signatures (LINCS) database. We identified 16 repurposing candidates in autosomal dominant PKD and 15 repurposing candidates for SETBP1-associated disorders. Our study here utilizes our newly designed framework to effectively prioritize these candidates from our prior work for additional downstream studies.

Results:
By applying our framework, we identified top candidates for downstream pre-clinical and clinical studies for both the PKD (e.g., bromocriptine, mirtazapine) and SETBP1-associated disorders (e.g., simvastatin, fluvastatin) test cases based on their 1) drug-specific, 2) target-specific, and 3) disease-specific considerations. In particular, we evaluated the expression levels of these drugs’ targets in disease-manifesting tissues, analyzed the transcriptomic signatures responsible for the original drug repurposing candidate identification in light of the prioritization considerations, assessed the drug safety-efficacy profiles from both the past and present clinical trials, and determined if these drugs or their known targets are associated with critical clinical features like increased association with adverse events.

Conclusion:
Our findings support the application of our framework for drug prioritization to improve pre-clinical and clinical trial success based on 1) drug-specific, 2) target-specific, and 3) disease-specific considerations. While our test cases here were for PKD and SETBP1-associated disorders, they are clinically variable in presentation, further highlighting how this framework may also be beneficial for other Mendelian diseases, complex/polygenic disorders, as well as guiding drug discovery. In summary, our work aims to improve pre-clinical and clinical trial success rates through a rigorous prioritization schema, which has the potential to broadly impact therapeutic selection.

Agenda

Sponsors