III-080

PBPK Modeling of Repurposed HIV Drugs in Prostate Cancer and the Influence of Patient Physiology

Mariana Pereira1,2,3, Dr. Nuno Vale1,2,4

1PerMed Research Group, Center for Health Technology and Services Research (CINTESIS), 2RISE-Health, Department of Pathology, Faculty of Medicine, University of Porto, 3ICBAS—School of Medicine and Biomedical Sciences, University of Porto, 4 Laboratory of Personalized Medicine, Department of Community Medicine, Health Information and Decision (MEDCIDS), Faculty of Medicine, University of Porto

Objective: Drug repurposing is gaining attention in cancer therapy development by using safe, approved drugs, speeding up development and reducing costs [1]. Efavirenz (EFV), etravirine (ETV), and saquinavir (SAQ) are antiretroviral drugs approved for HIV treatment [2–4] and have shown potential for other diseases [5]. Our group has demonstrated their anti-cancer effects in vitro [6,7]. This study aims to develop and compare physiologically based pharmacokinetic (PBPK) models for ETV, EFV, and SAQ under conditions simulating prostate cancer. Models of healthy and cancerous prostate tissue will be created. These will be applied to different population profiles to assess the influence of age and weight on drug pharmacokinetics in prostate cancer. The primary goal of this study was to investigate whether the pharmacokinetics of EFV, ETV, and SAQ, at their standard, approved dosages, are altered when a prostate cancer compartment is introduced into the PBPK model, and whether these changes are further influenced by physiological variations such as age and body weight. Methods: Literature data and ADMET Predictor® (v11) parameters were used to build a validated ETV model in GastroPlus® (v9.8.3; Simulation Plus Inc., Lancaster, CA, USA) at 200 mg BID. A validated EFV model at 400 mg QD was already included in the software. SAQ (600 mg QD) simulations used a model from Lukacova et al. 2011 [8]. To mimic prostate cancer physiology, various “ReproOrg” tissue parameters were adjusted: volume, blood flow, leakage, partition coefficients, and fractions of neutral lipids, phospholipids, water, and acidic phospholipids—based on literature data. PEAR (Population Estimates for Age-Related Physiology) models were generated in addition to the default American male (30 years, 70 kg), including older (65 years) and heavier (95 kg) profiles, as age and obesity are prostate cancer risk factors. Results: PBPK modeling showed that age and body weight impact plasma concentrations. For EFV, maximum plasma concentrations (Cmax) ranked: 65y/70kg (1.696 µg/mL) > 30y/70kg (1.591) > 65y/95kg (1.286) > 30y/95kg (1.239). Older and lighter individuals exhibited higher EFV concentrations. Obese individuals had lower EFV levels, consistent with prior simulations [9]. Aging is also linked to reduced hepatic metabolism, especially for drugs processed by CYP2B6 and CYP3A4 [10]. ETV showed similar trends. Individuals at 70 kg had the highest Cmax (~0.328 µg/mL), regardless of age. In 95 kg models, older individuals had slightly higher Cmax (0.265 vs. 0.255). Prior studies showed ETV exposure drops ~20% in obese virtual patients [11]. For SAQ, Cmax ranked: 30y/70kg (12.498 µg/mL) > 65y/70kg (11.727) > 65y/95kg (11.546) > 30y/95kg (10.173). A higher Cmax in younger patients suggests that age may affect absorption and distribution. Clearance decreases with age, possibly explaining this trend [12]. Obesity also lowers SAQ concentrations [13]. However, AUC0-T was highest for the 65y/95kg model (60.145 µg·h/mL), versus 56.843 in the 30y/70kg model. This suggests younger individuals absorb SAQ faster (higher Cmax), but clear it faster too, while older individuals maintain levels longer [12]. Between normal and cancerous prostate models, no meaningful differences in pharmacokinetics were observed for any drug across physiologies. This suggests prostate-specific changes have minimal whole-body pharmacokinetic impact. Since these drugs are primarily metabolized hepatically and excreted via feces [2–4], prostate alterations don’t significantly influence drug disposition. Thus, age and weight should be prioritized when considering dosing for prostate cancer patients receiving repurposed antiretrovirals. Conclusions: This study highlights that prostate-specific tissue alterations do not significantly affect the pharmacokinetics of ETV, EFV, or SAQ. However, patient-specific factors, especially age and weight, play a substantial role. These should be carefully considered when repurposing these agents for prostate cancer, as elderly or obese patients may require individualized dosing to ensure efficacy and minimize toxicity.

 1. Pushpakom, S.; Iorio, F.; Eyers, P.A.; Escott, K.J.; Hopper, S.; Wells, A.; Doig, A.; Guilliams, T.; Latimer, J.; McNamee, C.; et al. Drug repurposing: progress, challenges and recommendations. Nature Reviews Drug Discovery 2019, 18, 41-58. 2. Costa, B.; Vale, N. Efavirenz: History, Development and Future. Biomolecules 2022, 13, doi:10.3390/biom13010088. 3. Etravirine. In LiverTox: Clinical and Research Information on Drug-Induced Liver Injury; National Institute of Diabetes and Digestive and Kidney Diseases: Bethesda (MD), 2012. 4. Pereira, M.; Vale, N. Saquinavir: From HIV to COVID-19 and Cancer Treatment. Biomolecules 2022, 12, 944. 5. Marima, R.; Hull, R.; Dlamini, Z.; Penny, C. Efavirenz and Lopinavir/Ritonavir Alter Cell Cycle Regulation in Lung Cancer. Front Oncol 2020, 10, 1693, doi:10.3389/fonc.2020.01693. 6. Pereira, M.; Vale, N. Exploring Darunavir, Rilpivirine and Etravirine as Potential Therapies for Bladder Cancer: Efficacy and Synergistic Effects. Biomedicines 2024, 12, 647. 7. Pereira, M.; Vale, N. Repurposing Alone and in Combination of the Antiviral Saquinavir with 5-Fluorouracil in Prostate and Lung Cancer Cells. Int J Mol Sci 2022, 23, doi:10.3390/ijms232012240. 8. Lukacova V, W.W., Bolger MB. Physiologically-Based Pharmacokinetic (PBPK) Models for Prediction of Saquinavir Effect on Midazolam Pharmacokinetics. Available online: https://www.simulations-plus.com/resource/physiologically-based-pharmacokinetic-pbpk-models-prediction-saquinavir-effect-midazolam-pharmacokinetics/ (accessed on 9. Solanke, T.; Kamau, F.; Esterhuizen, T.; Maartens, G.; Khoo, S.; Joska, J.A.; Kellermann, T.; Strijdom, H.; Decloedt, E.H. Concentrations of Efavirenz, Tenofovir, and Emtricitabine in Obesity: A Cross-Sectional Study. J Acquir Immune Defic Syndr 2022, 91, 101-108, doi:10.1097/qai.0000000000003025. 10. McLachlan, A.J.; Pont, L.G. Drug Metabolism in Older People—A Key Consideration in Achieving Optimal Outcomes With Medicines. The Journals of Gerontology: Series A 2011, 67A, 175-180, doi:10.1093/gerona/glr118. 11. Berton, M.; Bettonte, S.; Stader, F.; Decosterd, L.; Tarr, P.E.; Livio, F.; Cavassini, M.; Braun, D.L.; Kusejko, K.; Hachfeld, A.; et al. Antiretroviral Drug Exposure and Response in Obese and Morbidly Obese People With Human Immunodeficiency Virus (HIV): A Study Combining Modelling and Swiss HIV Cohort Data. Clinical Infectious Diseases 2023, 78, 98-110, doi:10.1093/cid/ciad495. 12. Vanhove, G.F.; Kastrissios, H.; Gries, J.M.; Verotta, D.; Park, K.; Collier, A.C.; Squires, K.; Sheiner, L.B.; Blaschke, T.F. Pharmacokinetics of saquinavir, zidovudine, and zalcitabine in combination therapy. Antimicrob Agents Chemother 1997, 41, 2428-2432, doi:10.1128/aac.41.11.2428. 13. Ribera, E.; Lopez, R.M.; Diaz, M.; Pou, L.; Ruiz, L.; Falcó, V.; Crespo, M.; Azuaje, C.; Ruiz, I.; Ocaña, I.; et al. Steady-state pharmacokinetics of a double-boosting regimen of saquinavir soft gel plus lopinavir plus minidose ritonavir in human immunodeficiency virus-infected adults. Antimicrob Agents Chemother 2004, 48, 4256-4262, doi:10.1128/aac.48.11.4256-4262.2004. 

Reference: PAGE 33 (2025) Abstr 11622 [www.page-meeting.org/?abstract=11622]

Poster: Drug/Disease Modelling - Oncology

PDF poster / presentation (click to open)