A translational minimal physiologically-based pharmacokinetic (mPBPK) model to predict preclinical and clinical PK of MEN1703 in tissues
Mira Tout (1), Faten Koraichi-Auriol (1), Elisa Borella (1), Iñaki F Trocóniz (2), Simona Blotta (1), Chiara Piana (1), Paolo Mazzei (1), Salim Bouchene (1)*
(1) Stemline Therapeutics/Menarini group, (2) Department of Pharmaceutical Technology and Chemistry, Faculty of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain. *No longer working for this company
Objectives: MEN1703 is a novel dual kinase inhibitor targeting PIM and FLT3 kinases, currently under investigation in patients with acute myeloid leukemia (AML), an aggressive malignancy characterized by an uncontrolled proliferation of abnormal myeloid progenitors in the bone marrow and blood. In-house toxicology and pharmacokinetic preclinical data showed an extensive and rapid tissue distribution of MEN1703. The characterization and the prediction of MEN1703 tissue concentration-time courses are important to better understand the exposure-efficacy and -safety relationships in humans. The objective of this study was to develop a translational minimal physiologically-based pharmacokinetic (mPBPK) model to allow predicting MEN1703 PK in selected tissues across preclinical species and humans.
Methods: PK of MEN1703 following its oral administration in three preclinical species (rats, dogs, mice) at several doses was assessed using a mPBPK model based on the integrated model of Cao and Jusko [1]. The model was fitted with NONMEM 7.3, and included blood compartment, bone marrow, liver and spleen tissue compartments, as well as a lumped tissue compartment representing the rest of the body. These tissues were selected based on the efficacy and safety profiles of the drug. System-related parameter values (blood flows and tissue volumes) were available from literature for the different species [2,3]. Tissue distribution was assumed to be perfusion-limited. For drug-related parameters, tissue-blood partition coefficients (Kp) for the included tissues were estimated with priors informed from experiments in rats and dogs and implemented with uncertainty using the PRIOR NWPRI subroutine [4]. An allometric scaling of clearances by body weight was applied across species using the standard 0.75 exponent value. The final model was validated in the clinical setting using prediction-corrected visual predictive checks (pcVPC), where model-based predictions in humans were compared to plasma concentrations from the phase I clinical study (CLI24-001) in AML patients receiving increasing oral doses of MEN1703.
Results: A total of 311 MEN1703 concentrations collected from rats (N=18), dogs (N=24), and mice (N=6) were analyzed using the described mPBPK model. The model allowed an adequate estimation of the parameters. Unbound hepatic intrinsic and non-hepatic clearances were estimated separately. High Kp values were estimated for bone marrow, liver, and spleen compartments, indicating an important tissue partitioning, consistently with the high tissue concentrations of MEN1703 measured in rats and dogs. Interindividual variability was included on Kp, hepatic intrinsic clearance, as well as on residual error. The final model allowed an appropriate prediction of PK profiles across preclinical species. Finally, pcVPC using 343 MEN1703 plasma concentrations from 48 AML patients demonstrated the adequate predictive performance of the model in the clinical setting.
Conclusions: A translational minimal PBPK model was developed to describe MEN1703 PK across three preclinical species and patients with AML. This model may be further developed into a mPBPK/PD model and used in the risk assessment setting to characterize efficacy and safety (hepatotoxicity) profiles of MEN1703. Model-based simulations of MEN1703 concentrations in blood and tissues for alternative dosing regimens would also inform dose selection in the clinical setting.
References:
[1] Cao Y, Jusko WJ. Applications of minimal physiologically-based pharmacokinetic models. J Pharmacokinet Pharmacodyn. 2012;39(6):711-723.
[2] Davies B, Morris T. Physiological parameters in laboratory animals and humans. Pharm Res. 1993;10(7):1093-1095.
[3] Brown RP, Delp MD, Lindstedt SL, Rhomberg LR, Beliles RP. Physiological parameter values for physiologically based pharmacokinetic models. Toxicol Ind Health. 1997;13(4):407-484.
[4] Langdon G, Gueorguieva I, Aarons L, Karlsson M. Linking preclinical and clinical whole-body physiologically based pharmacokinetic models with prior distributions in NONMEM. Eur J Clin Pharmacol. 2007;63(5):485-498.