Rob ter Heine
Radboud University Medical Center, Nijmegen
Objectives: Everolimus is a drug from the class of mTOR-inhibitors. There is increasing concern over the need for dose reductions due to severe toxicity [1]. Everolimus pharmacokinetics and pharmacodynamics are influenced by hematocrit (HT), as everolimus extensively accumulates in erythrocytes [2]. The extent to which HT affects everolimus plasma exposure and thereby mTOR inhibition is unknown. The aim of our study was to investigate the everolimus pharmacokinetics and pharmacodynamics and the influence of HT on these parameters in cancer patients.
Methods: A semi-physiological population pharmacokinetic (PK) model for everolimus that accounted for everolimus erythrocyte accumulation and incorporated a physiological model for first-pass metabolism, as described previously [3] was developed in NONMEM. By implementing a pharmacodynamic (PD) model, describing the relationship between unbound plasma concentrations and inhibition of S6K1 (a downstream mTOR effector) [4], we investigated the impact HT on the predicted PK and PD.
Results: PK curves in whole blood from 73 cancer patients were available. HT ranged from 25% to 49.7%. Oral absorption was described with 4 transit compartments and a mean absorption time (MAT) of 0.544 h (RSE 6.4%). The apparent volume of distribution of the central and peripheral compartment were respectively estimated to be 207 (RSE 5.0%)and 485 L (RSE 4.2%), with an inter-compartmental clearance of 72.1 L/h (RSE 3.2%). The intrinsic clearance was estimated to be 198 L/h (RSE 4.3%). The inter-individual variability in MAT, intrinsic clearance and volume of distribution of the central compartment were estimated to be 62.0% (RSE 23.5%), 38.9% (RSE 24.8%) and 36.1% (RSE 63.4%), respectively. A decrease in HT of 45% to 20% resulted in a reduction in whole blood exposure of approximately 50%, but everolimus plasma pharmacokinetics and mTOR inhibition were not affected. The predicted mTOR (S6K1) inhibition was at a plateau level in the approved dose of 10 mg once daily.
Conclusions: A semi-physiological population PK model accounting for erythrocyte accumulation was developed for everolimus in cancer patients. HT influenced whole blood PK, but not plasma PK or PD. Therefore, in studies investigating the relation between everolimus PK and PD, whole blood concentrations should always be corrected for HT. Since predicted mTOR inhibition was at a plateau level, dose reductions may only have a limited impact on mTOR inhibition. This encourages further prospective studies to reduce everolimus toxicity without loss of efficacy.
References:
[1] Baselga J, Campone M, Piccart M, Burris HA, 3rd, Rugo HS, Sahmoud T, et al. Everolimus in postmenopausal hormone-receptor-positive advanced breast cancer. The New England journal of medicine. 2012;366(6):520-9.
[2] http://www.accessdata.fda.gov/drugsatfda_docs/nda/2009/022334s000_ClinPharmR.pdf
[3] Gordi T, Xie R, Huong NV, Huong DX, Karlsson MO, Ashton M. A semiphysiological pharmacokinetic model for artemisinin in healthy subjects incorporating autoinduction of metabolism and saturable first-pass hepatic extraction. British journal of clinical pharmacology. 2005;59(2):189-98.
[4] Tanaka C, O’Reilly T, Kovarik JM, Shand N, Hazell K, Judson I, et al. Identifying optimal biologic doses of everolimus (RAD001) in patients with cancer based on the modeling of preclinical and clinical pharmacokinetic and pharmacodynamic data. J Clin Oncol. 2008;26(10):1596-602.
Reference: PAGE 25 (2016) Abstr 3693 [www.page-meeting.org/?abstract=3693]
Poster: Drug/Disease modeling - Oncology