Application and development trends of population pharmacokinetic techniques in virtual clinical trials_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

ZHANG Yuming ^1,2,3 , LIU Yixian ^1,2 ,  ZHENG Li ^1,2

1. Clinical Trial Center, West China Hospital, Sichuan University, Chengdu, 610041, P. R. China;
2. NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, West China Hospital, Sichuan University, Chengdu, 610041, P. R. China;
3. West China School of Medicine, West China Hospital, Sichuan University, Chengdu, 610041, P. R. China;

Corresponding author：

ZHENG Li, Email: zhengli@wchscu.cn

Keywords：

Population pharmacokinetics; virtual clinical trials; modeling and simulation

DOI：

10.7507/1007-4848.202405021

Video：

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Population pharmacokinetics is a research technique based on computer simulation and data analysis, and it has been employed to investigate the dynamic behavior of drug metabolism in different populations. This approach could address practical challenges such as prolonged clinical trial durations, high costs, and increased difficulty in traditional clinical trials. By comprehensively analyzing differences in the internal drug metabolism processes across populations with varying physiological and pathological conditions, population pharmacokinetics has emerged as an effective method to optimize drug development and clinical applications. This article provides a preliminary overview of the essence of population pharmacokinetics, its application in clinical trials, and potential future trends. We hope to serve as a reference and guidance for the application of new technologies and methods in clinical trials.

Citation： ZHANG Yuming, LIU Yixian, ZHENG Li. Application and development trends of population pharmacokinetic techniques in virtual clinical trials. Chinese Journal of Clinical Thoracic and Cardiovascular Surgery, 2024, 31(10): 1400-1406. doi: 10.7507/1007-4848.202405021 Copy

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11.	Zyryanov S, Bondareva I, Butranova O, et al. Population PK/PD modelling of meropenem in preterm newborns based on therapeutic drug monitoring data. Front Pharmacol, 2023, 14(14): 1079680.
12.	Li Y, Zhan H, Wu J, et al. Population pharmacokinetics and exposure-safety of lipophilic conjugates prodrug DP-VPA in healthy Chinese subjects for dose regime exploring. Eur J Pharm Biopharm, 2023, 188: 153-160.
13.	Klopp-Schulze L, Shaw JV, Dong JQ, et al. Applying modeling and simulations for rational dose selection of novel toll-like receptor 7/8 inhibitor enpatoran for indications of high medical need. Clin Pharmacol Ther, 2022, 112(2): 297-306.
14.	Stanczyk FZ, Archer DF, Lohmer LRL, et al. Extended regimen of a levonorgestrel/ethinyl estradiol transdermal delivery system: Predicted serum hormone levels using a population pharmacokinetic model. PLoS One, 2022, 17(12): e0279640.
15.	Marsousi N, Desmeules JA, Rudaz S, et al. Usefulness of PBPK modeling in incorporation of clinical conditions in personalized medicine. J Pharm Sci, 2017, 106(9): 2380-2391.
16.	Sewell CA, Sheehan SM, Gill MS, et al. Scientific, ethical, and legal considerations for the inclusion of pregnant people in clinical trials. Am J Obstet Gynecol, 2022, 227(6): 805-811.
17.	Quinney SK, Bonate PL. A pharmacometrician's role in enhancing medication use in pregnancy and lactation. J Pharmacokinet Pharmacodyn, 2020, 47(4): 267-269.
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20.	江泽宇, 魏璧, 许倩, 等. 孕妇药物临床试验中的伦理问题及其解决方案综述. 中国医学伦理学, 2019, 32(6): 719-723.Jiang ZY, Wei B, Xu Q, et al. Review on the ethical issues and solutions of drug clinical trials involving pregnant women. Chin J Ethic, 2019, 32(6): 719-723.
21.	Chaphekar N, Caritis S, Venkataramanan R. Model-informed dose optimization in pregnancy. J Clin Pharmacol, 2020, 60(Suppl 1): S63-S76.
22.	Wang ML, Tao YY, Sun XY, et al. Estrogen profile- and pharmacogenetics-based lamotrigine dosing regimen optimization: Recommendations for pregnant women with epilepsy. Pharmacol Res, 2021, 169: 105610.
23.	Lim SY, Pettit RS. Pharmacokinetic considerations in pediatric pharmacotherapy. Am J Health Syst Pharm, 2019, 76(19): 1472-1480.
24.	Bereda G. Pediatrics: Pharmacokinetics and dose calculation. J Pediatr Neonatal Care, 2022, 12(2): 96-102.
25.	Ghanemi K, Yan S. Ethics in pediatric clinical research. Adv Cytol Pathol, 2018, 3(1): 13-14.
26.	Anitha P, Dhar R, Krishnappa N. Clinical trials in pediatrics-review of ethics and law. Int J Basic Clin Pharmacol, 2022, 11(5): 538-538.
27.	Van der Heijden J, Freriksen J, de Hoop-Sommen M, et al. Feasibility of the pragmatic PBPK modelling approach—Towards model-informed dosing in paediatric clinical care. Arch Dis Child, 2023, 108(6): A4.3-A5.
28.	Maharaj AR, Wu H, Zimmerman KO, et al. Population pharmacokinetics of olanzapine in children. Br J Clin Pharmacol. 2021, 87(2): 542-554.
29.	Akinosoglou K, Schinas G, Almyroudi MP, et al. The impact of age on intensive care. Ageing Res Rev, 2023, 84: 101832.
30.	Liu R, Li ZY. Advances in the research of characteristics and treatment of burns in the elderly. Zhonghua Shao Shang Za Zhi, 2017, 33(9): 553-556.
31.	Ruiz-Montero P J, Castillo-Rodríguez A. Differences between body composition and physiological characteristics of active/inactive elderly women. Int J Morphol, 2018, 36(1): 262-266.
32.	Telekes A, Deme D. Principles of pharmacotherapy in the elderly. Orv Hetil, 2019, 160(23): 896-907.
33.	Butranova O, Zyryanov S. Elderly patients in randomized clinical trials: Ethical issues. Медицинская этика, 2023, 1.
34.	Usman M, Frey OR, Hempel G. Population pharmacokinetics of meropenem in elderly patients: Dosing simulations based on renal function. Eur J Clin Pharmacol, 2017, 73(3): 333-342.
35.	GBD 2017 DALYs and HALE Collaborators. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: A systematic analysis for the Global Burden of Disease Study 2017. Lancet, 2018, 392(10159): 1859-1922.
36.	Krens SD, Lassche G, Jansman FGA, et al. Dose recommendations for anticancer drugs in patients with renal or hepatic impairment. Lancet Oncol, 2019, 20(4): e200-e207.
37.	Purohit V, Huh Y, Wojciechowski J, et al. Leveraging prior healthy participant pharmacokinetic data to evaluate the impact of renal and hepatic impairment on ritlecitinib pharmacokinetics. AAPS J, 2023, 25(3): 32.
38.	Zhao Y, Yin J, Zhang L, et al. Drug-drug interaction prediction: Databases, web servers and computational models. Brief Bioinform, 2023, 25(1): bbad445.
39.	Bonate PL, Ahamadi M, Budha N, et al. Methods and strategies for assessing uncontrolled drug—Drug interactions in population pharmacokinetic analyses: Results from the International Society of Pharmacometrics (ISOP) Working Group. J Pharmacokinet Pharmacodyn, 2016, 43(2): 123-135.
40.	Kirschbrown WP, Kågedal M, Wang B, et al. Pharmacokinetic and exploratory exposure—Response analysis of pertuzumab in patients with operable HER2-positive early breast cancer in the APHINITY study. Cancer Chemother Pharmacol, 2019, 83(6): 1147-1158.
41.	Goldman JG, Marr D, Zhou L, et al. Racial differences may influence the role of cholecystokinin polymorphisms in Parkinson's disease hallucinations. Mov Disord, 2011, 26(9): 1781-1782.
42.	Li C, Wang B, Lu D, et al. Ethnic sensitivity assessment of the antibody—Drug conjugate trastuzumab emtansine (T-DM1) in patients with HER2-positive locally advanced or metastatic breast cancer. Cancer Chemother Pharmacol, 2016, 78(3): 547-558.
43.	Oda K, Saito H, Jono H. Bayesian prediction-based individualized dosing of anti-methicillin-resistant Staphylococcus aureus treatment: Recent advancements and prospects in therapeutic drug monitoring. Pharmacol Ther, 2023, 246: 108433.

1. 国家药品监督管理局. 药物临床试验质量管理规范. URL: https://www.gov.cn/zhengce/zhengceku/2020-04/28/content_5507145.htm. Accessed on 2024-05-05.National Medical Products Administration. Criterions for the quality control of clinical trial of drugs. URL: https://www.gov.cn/_zhengce/zhengceku/2020-04/28/content_5507145.htm. Accessed on 2024-05-05.
2. Desai M. Recruitment and retention of participants in clinical studies: Critical issues and challenges. Perspect Clin Res, 2020, 11(2): 51-53.
3. Pappalardo F, Russo G, Tshinanu FM, et al. In silico clinical trials: Concepts and early adoptions. Brief Bioinform, 2019, 20(5): 1699-1708.
4. 刘懿贤, 郑莉. 虚拟临床试验应用现状及趋势. 中国胸心血管外临床杂志, 2024, 31(2): 216-222.Liu YX, Zheng L. Application status and development trend of virtual clinical trials. Chin J Clin Thorac Cardiovasc Surg, 2024, 31(2): 216-222.
5. U. S. Food & Drug Administration. Population pharmacokinetics guidance for industry. URL: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/population-pharmacokinetics. Accessed on 2024-05-05.
6. 国家药品监督管理局药品审评中心. 群体药代动力学研究技术指导原则. URL: https://www.cde.org.cn/main/news/viewInfoCommon/b3e8205a4749caa0264414514cdf45ac. Accessed on 2024-05-05.National Medical Products Administration Drug Evaluation Center. Technical guidelines for population pharmacokinetic studies. URL: https://www.cde.org.cn/main/news/viewInfoCommon/b3e8205a4749caa0264414514cdf45ac. Accessed on 2024-05-05.
7. Sheiner LB, Rosenberg B, Melmon KL. Modelling of individual pharmacokinetics for computer-aided drug dosage. Comput Biomed Res, 1972, 5(5): 411-459.
8. Guidi M, Csajka C, Buclin T. Parametric approaches in population pharmacokinetics. J Clin Pharmacol, 2022, 62(2): 125-141.
9. Mould DR, Upton RN. Basic concepts in population modeling, simulation, and model-based drug development—Part 2: introduction to pharmacokinetic modeling methods. CPT Pharmacometrics Syst Pharmacol, 2013, 2(4): e38.
10. Gajjar P, Dickinson J, Dickinson H, et al. Population PK modelling as an alternative route to bioequivalence. Br J Pharmacol, 2022, 7(2): S1-S2.
11. Zyryanov S, Bondareva I, Butranova O, et al. Population PK/PD modelling of meropenem in preterm newborns based on therapeutic drug monitoring data. Front Pharmacol, 2023, 14(14): 1079680.
12. Li Y, Zhan H, Wu J, et al. Population pharmacokinetics and exposure-safety of lipophilic conjugates prodrug DP-VPA in healthy Chinese subjects for dose regime exploring. Eur J Pharm Biopharm, 2023, 188: 153-160.
13. Klopp-Schulze L, Shaw JV, Dong JQ, et al. Applying modeling and simulations for rational dose selection of novel toll-like receptor 7/8 inhibitor enpatoran for indications of high medical need. Clin Pharmacol Ther, 2022, 112(2): 297-306.
14. Stanczyk FZ, Archer DF, Lohmer LRL, et al. Extended regimen of a levonorgestrel/ethinyl estradiol transdermal delivery system: Predicted serum hormone levels using a population pharmacokinetic model. PLoS One, 2022, 17(12): e0279640.
15. Marsousi N, Desmeules JA, Rudaz S, et al. Usefulness of PBPK modeling in incorporation of clinical conditions in personalized medicine. J Pharm Sci, 2017, 106(9): 2380-2391.
16. Sewell CA, Sheehan SM, Gill MS, et al. Scientific, ethical, and legal considerations for the inclusion of pregnant people in clinical trials. Am J Obstet Gynecol, 2022, 227(6): 805-811.
17. Quinney SK, Bonate PL. A pharmacometrician's role in enhancing medication use in pregnancy and lactation. J Pharmacokinet Pharmacodyn, 2020, 47(4): 267-269.
18. Balon M, Tessier S, Damase-Michel C, et al. Adverse drug reactions in pregnant women: Do they differ from those in non-pregnant women of childbearing age? Therapie, 2022, 78(2): 165-173.
19. Diusembayeva NK, Kalieva SS, Yukhnevich Y, et al. Clinical trials of medicinal products in pregnant women (overview). Bulletin of the Karaganda University, Biology, medicine, geography Series, 2022, 106(2): 145-153.
20. 江泽宇, 魏璧, 许倩, 等. 孕妇药物临床试验中的伦理问题及其解决方案综述. 中国医学伦理学, 2019, 32(6): 719-723.Jiang ZY, Wei B, Xu Q, et al. Review on the ethical issues and solutions of drug clinical trials involving pregnant women. Chin J Ethic, 2019, 32(6): 719-723.
21. Chaphekar N, Caritis S, Venkataramanan R. Model-informed dose optimization in pregnancy. J Clin Pharmacol, 2020, 60(Suppl 1): S63-S76.
22. Wang ML, Tao YY, Sun XY, et al. Estrogen profile- and pharmacogenetics-based lamotrigine dosing regimen optimization: Recommendations for pregnant women with epilepsy. Pharmacol Res, 2021, 169: 105610.
23. Lim SY, Pettit RS. Pharmacokinetic considerations in pediatric pharmacotherapy. Am J Health Syst Pharm, 2019, 76(19): 1472-1480.
24. Bereda G. Pediatrics: Pharmacokinetics and dose calculation. J Pediatr Neonatal Care, 2022, 12(2): 96-102.
25. Ghanemi K, Yan S. Ethics in pediatric clinical research. Adv Cytol Pathol, 2018, 3(1): 13-14.
26. Anitha P, Dhar R, Krishnappa N. Clinical trials in pediatrics-review of ethics and law. Int J Basic Clin Pharmacol, 2022, 11(5): 538-538.
27. Van der Heijden J, Freriksen J, de Hoop-Sommen M, et al. Feasibility of the pragmatic PBPK modelling approach—Towards model-informed dosing in paediatric clinical care. Arch Dis Child, 2023, 108(6): A4.3-A5.
28. Maharaj AR, Wu H, Zimmerman KO, et al. Population pharmacokinetics of olanzapine in children. Br J Clin Pharmacol. 2021, 87(2): 542-554.
29. Akinosoglou K, Schinas G, Almyroudi MP, et al. The impact of age on intensive care. Ageing Res Rev, 2023, 84: 101832.
30. Liu R, Li ZY. Advances in the research of characteristics and treatment of burns in the elderly. Zhonghua Shao Shang Za Zhi, 2017, 33(9): 553-556.
31. Ruiz-Montero P J, Castillo-Rodríguez A. Differences between body composition and physiological characteristics of active/inactive elderly women. Int J Morphol, 2018, 36(1): 262-266.
32. Telekes A, Deme D. Principles of pharmacotherapy in the elderly. Orv Hetil, 2019, 160(23): 896-907.
33. Butranova O, Zyryanov S. Elderly patients in randomized clinical trials: Ethical issues. Медицинская этика, 2023, 1.
34. Usman M, Frey OR, Hempel G. Population pharmacokinetics of meropenem in elderly patients: Dosing simulations based on renal function. Eur J Clin Pharmacol, 2017, 73(3): 333-342.
35. GBD 2017 DALYs and HALE Collaborators. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: A systematic analysis for the Global Burden of Disease Study 2017. Lancet, 2018, 392(10159): 1859-1922.
36. Krens SD, Lassche G, Jansman FGA, et al. Dose recommendations for anticancer drugs in patients with renal or hepatic impairment. Lancet Oncol, 2019, 20(4): e200-e207.
37. Purohit V, Huh Y, Wojciechowski J, et al. Leveraging prior healthy participant pharmacokinetic data to evaluate the impact of renal and hepatic impairment on ritlecitinib pharmacokinetics. AAPS J, 2023, 25(3): 32.
38. Zhao Y, Yin J, Zhang L, et al. Drug-drug interaction prediction: Databases, web servers and computational models. Brief Bioinform, 2023, 25(1): bbad445.
39. Bonate PL, Ahamadi M, Budha N, et al. Methods and strategies for assessing uncontrolled drug—Drug interactions in population pharmacokinetic analyses: Results from the International Society of Pharmacometrics (ISOP) Working Group. J Pharmacokinet Pharmacodyn, 2016, 43(2): 123-135.
40. Kirschbrown WP, Kågedal M, Wang B, et al. Pharmacokinetic and exploratory exposure—Response analysis of pertuzumab in patients with operable HER2-positive early breast cancer in the APHINITY study. Cancer Chemother Pharmacol, 2019, 83(6): 1147-1158.
41. Goldman JG, Marr D, Zhou L, et al. Racial differences may influence the role of cholecystokinin polymorphisms in Parkinson's disease hallucinations. Mov Disord, 2011, 26(9): 1781-1782.
42. Li C, Wang B, Lu D, et al. Ethnic sensitivity assessment of the antibody—Drug conjugate trastuzumab emtansine (T-DM1) in patients with HER2-positive locally advanced or metastatic breast cancer. Cancer Chemother Pharmacol, 2016, 78(3): 547-558.
43. Oda K, Saito H, Jono H. Bayesian prediction-based individualized dosing of anti-methicillin-resistant Staphylococcus aureus treatment: Recent advancements and prospects in therapeutic drug monitoring. Pharmacol Ther, 2023, 246: 108433.

Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Application and development trends of population pharmacokinetic techniques in virtual clinical trials

Abstract Full text Figures/Tables Video References Cited by

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