Development of a drug-drug interaction screening tool for oncology clinical trial enrollment.

Abstract

315 Background: Screening drug-drug interactions (DDI) for subjects enrolling in oncology clinical trials is critical to ensuring patient safety and the validity of clinical trial data. We previously reported that DDI screening is not uniformly conducted when screening patients for enrollment into SWOG clinical trials and found that at the University of Michigan Rogel Cancer Center up to 24.2% of subjects enrolled in National Clinical Trial Network (NCTN) trials had a DDI. Screening tools aid in DDI reduction in clinical practice, but none have been created for clinical trial enrollment. Our objective was to develop a clinical trial specific DDI screening tool based on features requested by the end-users of the tool at U-M. Methods: Semi-structured and informal interviews were conducted with all data managers who enroll patients into NCTN clinical trials at the U-M cancer center. Data managers were asked about their current workflow and desired features of a DDI screening tool. Responses were combined and reviewed for feasibility. Desired features were conveyed to PEPID, LLC (Phoenix, AZ) for tool development. Results: Four data managers were interviewed. Protocol-guided screening was a key workflow feature, which was completed by gathering DDI information primarily from the exclusion criteria and drug information sections of each respective protocol, Google, CredibleMeds, and the Indiana University P450 Drug Interaction Table. Consequently, a critical feature was the display of drug characteristics with wording that aligned with that in the protocol including transporter and CYP450 substrates, inhibitors, or inducers and QT prolongation potential. Additional desirable features included separate entry of study and concomitant drugs, filtering to display only DDI with study drugs, and PDF export of results. PEPID developed a prototype tool including these desired attributes for a prospective implementation pilot study. Conclusions: A first generation clinical trial specific DDI screening tool was developed based on end-user feedback. We are designing a prospective study to determine whether implementation of this tool can reduce DDI, enhance patient safety, and ensure validity of clinical trial data.