Abstract
Background and Objective
Abiraterone is a first-in-class inhibitor of cytochrome P450 17A1 (CYP17A1), and its pharmacokinetic (PK) profile is susceptible to intrinsic and extrinsic variabilities. Potential associations between abiraterone concentrations and pharmacodynamic consequences in prostate cancer may demand further dosage optimization to balance therapeutic outcomes. Consequently, we aim to develop a physiologically based pharmacokinetic (PBPK) model for abiraterone via a middle-out approach to prospectively interrogate the untested, albeit clinically relevant, scenarios.
Methods
To characterize in vivo hydrolysis of prodrug abiraterone acetate (AA) and supersaturation of abiraterone, in vitro aqueous solubility data, biorelevant measurements, and supersaturation and precipitation parameters were utilized for mechanistic absorption simulation. CYP3A4-mediated N-oxidation and sulfotransferase 2A1-catalyzed sulfation of abiraterone were subsequently quantified in human liver subcellular systems. Iterative PBPK model refinement involved evaluation of potential organic anion transporting polypeptide (OATP)-mediated abiraterone uptake in transfected cells in the absence and presence of albumin.
Results
The developed PBPK model recapitulated the duodenal concentration–time profile of both AA and abiraterone after simulated AA administration. Our findings established abiraterone as a substrate of hepatic OATP1B3 to recapitulate its unbound metabolic intrinsic clearance. Further consideration of a transporter-induced protein-binding shift established accurate translational scaling factors and extrapolated the sinusoidal uptake process. Subsequent simulations effectively predicted the PK of abiraterone upon single and multiple dosing.
Conclusion
Our systematic development of the abiraterone PBPK model has demonstrated its application for the prospective interrogation of the individual or combined influences of potential interindividual variabilities influencing the systemic exposure of abiraterone.
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Acknowledgements
The authors thank Dr Bruno Stieger (Division of Clinical Pharmacology and Toxicology, University Hospital, Zurich, Switzerland) for the kind donation of both wild type and human OATP1B1/1B3/2B1-transfected Chinese hamster ovary cell lines.
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Funding
This work was supported by the Singapore Ministry of Education Tier 1 Academic Research Funding (grant R-148-000-249-114) and the National University of Singapore (NUS) President’s Graduate Fellowship (PGF) to E.J.Y.C and the National University of Singapore, Department of Pharmacy, final year project funding provided to Z.W.N, T.J.Y and E.Z.B.C.
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All authors participated in research design, performed data analysis, and wrote or contributed to the writing of the manuscript. Cheong, Ng, Chin, and Wang conducted the experiments. All authors read and approved the final manuscript.
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The data that support the findings of this study are available from the corresponding author upon reasonable request. Some data may not be made available because of privacy or ethical restrictions.
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40262_2023_1266_MOESM1_ESM.tif
Figure S1. Schematic presentation of the interplay between supersaturation and precipitation of abiraterone in intestinal fluids. Region A: The dissolved concentration of abiraterone is permitted to rise above equilibrium solubility until the critical supersaturation concentration (CSC) is attained. Region B: Above the CSC, there exists a metastable time window of supersaturated concentrations. Region C: Supersaturated abiraterone will precipitate as a function of time following a first-order kinetic process governed by the precipitation rate constant (PRC). Precipitation continues until dissolved concentration is equal to equilibrium solubility (TIF 101 kb)
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Figure S2. Determination of the intrinsic solubility of abiraterone via a saturation shake flask experiment. Measurements after 14 and 24 h of incubation indicated that the difference in mean intrinsic solubility of abiraterone was not statistically significant, p>0.05. Hence, taking the average of 12 measurements, the intrinsic solubility of abiraterone was calculated to be 0.0058 mg/mL (TIF 592 kb)
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Figure S3. Examining how the magnitude of the secondary precipitation rate constant (sPRC) will affect (a) the simulated duodenal concentration-time profile of abiraterone and (b) the simulated plasma Cmax (TIF 562 kb)
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Figure S4. Comparing the impact of utilizing a perfusion-limited liver model versus a permeability-limited liver model on the simulated plasma (solid lines) and liver (dashed lines) concentration-time profiles of abiraterone. Open symbols represent the observed clinical plasma concentration-time profile following a single 250 mg dose of abiraterone acetate administered under fasted conditions (TIF 982 kb)
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Figure S5. Time-dependent uptake of (a) testosterone 5 μM and (b) abiraterone 2.5 μM in OATP1B3-expressing CHO cells. Linearity of OATP1B3-mediated testosterone and abiraterone uptake was demonstrated between 1 to 2 min and 0.5 to 1 min respectively. Each point represents the mean ± SD of triplicate determinations. (TIF 553 kb)
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Figure S6. Evaluating the source and quality of drug-dependent parameters utilized to parameterize the absorption models of abiraterone acetate and abiraterone. (a) Depletion profile of abiraterone acetate in fasted state human intestinal fluid, fasted state simulated intestinal fluid supplemented with pancreatin (10 mg/mL) and fed state human intestinal fluid after the addition of 1 µM of abiraterone acetate to the media. Simulated (solid line) plasma drug concentration-time profiles of abiraterone in the fed state following (b) a single 250 mg dose of AA as reported by Geboers et al (TIF 642 kb)
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Figure S7. Comparison between the simulated geometric mean (solid and dashed lines) and observed PK profiles (open symbols) of abiraterone in healthy controls versus moderately hepatic impaired subjects following single dose administration of 1000 mg AA (TIF 629 kb)
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Cheong, E.J.Y., Chin, S.Y., Ng, Z.W. et al. Unraveling Complexities in the Absorption and Disposition Kinetics of Abiraterone via Iterative PBPK Model Development and Refinement. Clin Pharmacokinet 62, 1243–1261 (2023). https://doi.org/10.1007/s40262-023-01266-y
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DOI: https://doi.org/10.1007/s40262-023-01266-y