PII-127 - MODELING AND SIMULATION TO EXPLORE MECHANISMS OF PHARMACOKINETIC DRUG-DRUG INTERACTIONS OF ABEMACICLIB AND OLAPARIB IN PATIENTS WITH RECURRENT PLATINUM-RESISTANT OVARIAN CANCER

J. Na¹, K. Hill¹, N. Abbott¹, A. Hendrickson², L. Duska³, J. Hays⁴, G. Shapiro⁵, K. Moore⁶, M. Phelps¹; ¹The Ohio State University, ²Mayo foundation for medical education and research, ³University of Virginia, ⁴The ohio state university comprehensive cancer center, ⁵Dana-Farber Cancer Institute, ⁶Stephenson Cancer Center at the University of Oklahoma.

Background: Abemaciclib, a selective inhibitor of cyclin-dependent kinases 4 and 6, and olaparib, a poly (ADP-ribose) polymerase (PARP) enzyme inhibitor, are used for cancer treatment. Given the potential overlapping transport and metabolism pathways for these two agents, along with early toxicity observed with this combination in patients with recurrent platinum-resistant ovarian cancer, we integrated pharmacokinetic (PK) sampling to assess drug interactions (NCT04633239).

Methods: Plasma samples were collected when 200 or 250 mg of olaparib was administered alone BID starting cycle 1, day 1 for 7 days and then when administered in combination with 50 mg of abemaciclib BID, from cycle 1, day 8 through day 28. Mixed-effects population PK models were developed for olaparib and abemaciclib plus three active abemaciclib metabolites, M2, M18, and M20. The models were also constructed to enable evaluation of potential mechanisms for DDI via relevant transporter proteins, cytochrome P450 (CYP) enzymes, and time-dependent CYP inhibition.

Results: Thus far, a total of 240 plasma concentrations of abemaciclib and metabolites, and 124 plasma concentrations of olaparib were measured in samples from six enrolled patients. Compared to historical data, exposures of both abemaciclib and olaparib are significantly elevated when abemaciclib is started on cycle 1 day 8, lasting through day 15. By day 28, when both agents are at steady state, olaparib exposure returns to historical levels while abemaciclib exposure remains high. Olaparib is known to exhibit time-dependent PK, though we observe time-varying behavior for both olaparib and abemaciclib during the time course evaluated. Use of published population PK models enable good fitting of the data and estimations of PK parameters for both parent drugs, despite the limited number of patients thus far.

Conclusion: The developed population PK models adequately described the observed plasma concentrations of abemaciclib and olaparib in patients with recurrent platinum-resistant ovarian cancer. Cycle 1 PK behavior can be explained by empirical time-varying functions, though underlying mechanisms that can explain the observed data are still unclear. Transporter and CYP-mediated mechanisms are being explored within the model while patients accrue, and the dataset expands.