028: Drug-Drug Interactions of Lirafugratinib

Statement of Purpose, Innovation or Hypothesis: Lirafugratinib is being developed by Relay Therapeutics as an orally available, potent, and highly selective inhibitor of FGFR2, for the treatment of FGFR2-driven cancers. In vitro data indicated that lirafugratinib is a substrate of CYP3A4, CYP2J2, BCRP and P-gp. In vitro data also suggested lirafugratinib at the recommended dose of 70 mg QD may inhibit CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, P-gp, BCRP, OATP1B, and MATEs. Based on these in vitro results, an integrated approach of a clinical drug-drug interaction (DDI) study and physiologically based pharmacokinetic (PBPK) modeling and simulations were used to assess the DDI potentials of lirafugratinib to inform its dosing with concomitant medications in cancer patients.

Description of Methods & Materials: An open-label, 2-period, fixed sequence, crossover study with single oral dose of 20 mg lirafugratinib with and without itraconazole (strong CYP3A4 inhibitor) was conducted in healthy adult participants. A combination of in vitro data and clinical PK data following single and multiple dosing of 70 mg QD lirafugratinib in cancer patients were used to develop the PBPK model using Simcyp^® v21 simulator. PK obtained from the lirafugratinib/itraconazole clinical DDI study and patient study (additional doses of 20 – 100 mg QD or BID) were used to verify the PBPK model. The verified PBPK model was then used to simulate DDI potentials of lirafgratinib.

Data & Results: Sixteen healthy participants were enrolled and completed the lirafugratinib clinical DDI study with itraconazole. Itraconazole increased lirafugratinib C_max and AUC_0-inf by 1.26- and 2.00-fold, respectively. A PBPK model of lirafugratinib was developed and captured sufficiently the observed concentration-time data in cancer patients. Simulated AUC_0-inf and C_max geometric mean ratios (GMRs) of lirafugratinib with and without itraconazole agreed with the clinical data (1.13- and 2.04-fold increase for C_max and AUC_0-inf, respectively). Prospective victim DDI simulations from the PBPK model indicated no clinically relevant DDIs between lirafugratinib and the weak CYP3A4 inhibitor cimetidine (Table 1). The moderate CYP3A4 inhibitor erythromycin was predicted to increase lirafugratinib exposure (AUC) by 1.66-fold. Simulations with the moderate (efavirenz) and strong (rifampicin) CYP3A4 inducers predicted moderate decrease in lirafugratinib AUC (57 – 75%). No clinically relevant DDIs were predicted between lirafugratinib and substrates of various CYP enzymes. Similarly, with the exception of rosuvastatin (BCRP), no clinically relevant DDIs were predicted between lirafugratinib and substrates of transporters including P-gp (digoxin), OATP1B (rosuvastatin) and MATEs (metformin). A weak to moderate DDI was predicted between lirafugratinib and rosuvastatin (BCRP). PBPK sensitivity analyses indicated that simultaneous inhibition of CYP3A4 and P-gp is not expected to exacerbate DDI potentials of lirafugratinib compared with CYP3A4 inhibition alone, thus modulations of P-gp activities are unlikely to affect lirafugratinib exposures significantly.

Interpretation, Conclusion or Significance: DDIs of lirafugratinib were assessed using an integrated approach to inform its clinical dosing with concomitant medications in cancer patients.

Disclosures: XL, RS, FRa, KYJ, FRi, and JS declare employment with and ownership interest in Relay Therapeutics. HH declares employment with Certara UK, Simcyp Division, of which Relay Therapeutics is a PBPK consultancy client.

Citations/References: n/a

Additional Information/Authors: n/a