5D-04 - Amalgamation of Real World Data, bioinformatics analysis and computational biology techniques for unveiling the mechanism of the signal detected for Rucaparib via Disproportionality Analysis

Background: Rucaparib has been approved by the FDA for the management of BRCA-mutated metastatic prostate and ovarian cancer. FDA designated Rucaparib as an orphan drug in 2016 and thus there is a need for more robust post marketing surveillance studies. Hence, this research focuses on disproportionality analysis for Rucaparib using the FAERS database to unveil signals. Subsequently, the study explored the possible mechanisms associated with the identified signal of Rucaparib via integrated bioinformatics and computational strategies.

Objectives: The objective of this study is to detect and analyze Adverse Drug Events (ADEs) associated with Rucaparib using the FAERS database, explore the mechanisms underlying the identified signal related to Rucaparib, and investigate the molecular interactions between Rucaparib and the target proteins associated with the signal.

Methods: Open vigil 2.0 was leveraged to retrieve reports related to Rucaparib from FDA database between Q4/2003-Q2/2024 through retrospective case/non case study. All the data pertaining to the patients who received Rucaparib were collected to identify the signals. Disproportionality analysis was carried out based on Reporting Odds Ratio (ROR), Chi Squared Value (χ2), Proportional Reporting Ratio (PRR) and Drug Event (DE). Further, to identify the target underlying the signals of Rucaparib, STITCH drug-protein interaction tool was utilized, while MalaCards and Reactome databases exposed the pathways. Finally, molecular docking was performed using Schrodinger Maestro 2024-1 to study the molecular interaction between Rucaparib and the identified target associated with the signal.

Results: Out of 142 ADEs, 5 were considered as positive for signal using the criteria χ2 >4, PRR >2, ROR >2, and DE ≥ 3 for which the confidence interval was 95%. Through disproportionality analysis, decreased Glomerular Filtration Rate (GFR) was identified as one of the signals wherein, the number of DE was found to be 13. Further, STITCH tool revealed the interactions of Rucaparib with proteins to explore the mechanism of the shortlisted signal. Tankyrase (TNKS) protein was found to be associated with focal segmental glomerulosclerosis which has clinical features of decreased GFR, as evinced through Human Disease Database – MalaCards. To computationally corroborate the above findings, molecular docking revealed favorable binding affinities (glide score: -6.058 kcal/mol) between Rucaparib and TNKS (PDB ID: 4KRS).

Conclusions: The identified signal for Rucaparib, which links decreased GFR with focal segmental glomerulosclerosis underpins the need for cautious prescribing along with renal function monitoring. Extensive epidemiological studies in larger cohorts are required to further validate this signal.