药学学报, 2021, 56(3): 734-742
引用本文:
郑冠濠, 王琛瑀, 焦正. 模型引导下免疫检查点抑制剂的研发[J]. 药学学报, 2021, 56(3): 734-742.
ZHENG Guan-hao, WANG Chen-yu, JIAO Zheng. Model-informed drug development for immune checkpoint inhibitors[J]. Acta Pharmaceutica Sinica, 2021, 56(3): 734-742.

模型引导下免疫检查点抑制剂的研发
郑冠濠1,2, 王琛瑀2, 焦正2
1. 南方医科大学深圳医院, 广东 深圳 518000;
2. 上海市胸科医院, 上海交通大学附属胸科医院, 上海 200030
摘要:
免疫检查点抑制剂作为一种新型的抗肿瘤治疗药物,因其对多种肿瘤卓越的疗效及良好的安全性得到广泛认可。基于定量药理学的发展应运而生的模型引导的药物研发(model-informed drug development,MIDD),能加速新药临床试验的进程,提高新药研究过程中决策的正确率,尤其是针对研发难度较大而需求甚广的免疫检查点抑制剂类新药。本文主要以帕博利珠单抗为例,阐述MIDD方法在免疫检查点抑制剂研发过程中的具体应用,包括研发早期有效给药方案的拟定,研发晚期评估临床疗效和验证给药方案的可行性,再至上市后给药方案的再评估及变更,为MIDD指导抗肿瘤新药的研发提供参考。
关键词:    模型引导的药物研发      建模      模拟      定量药理学      免疫检查点抑制剂      帕博利珠单抗     
Model-informed drug development for immune checkpoint inhibitors
ZHENG Guan-hao1,2, WANG Chen-yu2, JIAO Zheng2
1. Shenzhen Hospital, Southern Medical University, Shenzhen 518000, China;
2. Shanghai Chest Hospital, Shanghai JiaoTong University, Shanghai 200030, China
Abstract:
With a deepening understanding of cancer treatment, immune checkpoint inhibitors are recognized widely as a novel fundamental remedy for various malignancies with effectiveness and safety. With the development of pharmacometrics, model-informed drug development (MIDD) has emerged to accelerate the process of clinical research for new drugs and improve the accuracy of decision-making in new drug research, especially for immune checkpoint inhibitors. As a typical illustration, the research development of pembrolizumab is presented in this review to highlight the application of MIDD, which may provide a reference for the development of other new antitumor drugs.
Key words:    model-informed drug development    modeling    simulation    pharmacometrics    immune checkpoint inhibitor    pembrolizumab   
收稿日期: 2020-10-13
DOI: 10.16438/j.0513-4870.2020-1610
基金项目: 吴阶平医学基金会临床科研专项资助基金(320.6750.2020-10-103).
通讯作者: 焦正,Tel:13611881161,E-mail:jiaozhen@online.sh.cn
Email: jiaozhen@online.sh.cn
相关功能
PDF(964KB) Free
打印本文
0
作者相关文章
郑冠濠  在本刊中的所有文章
王琛瑀  在本刊中的所有文章
焦正  在本刊中的所有文章

参考文献:
[1] Li B, Chan HL, Chen P. Immune checkpoint inhibitors:basics and challenges[J]. Curr Med Chem, 2019, 26:3009-3025.
[2] Jardim DL, Gagliato DDM, Giles FJ, et al. Analysis of drug development paradigms for immune checkpoint inhibitors[J]. Clin Cancer Res, 2018, 24:1785-1794.
[3] Marshall SF, Burghaus R, Cosson V, et al. Good practices in model-informed drug discovery and development:practice, application, and documentation[J]. CPT Pharmacometrics Syst Pharmacol, 2016, 5:93-122.
[4] Vaddepally RK, Kharel P, Pandey R, et al. Review of indications of FDA-approved immune checkpoint inhibitors per NCCN guidelines with the level of evidence[J]. Cancers (Basel), 2020, 12:738.
[5] Akinleye A, Rasool Z. Immune checkpoint inhibitors of PD-L1 as cancer therapeutics[J]. J Hematol Oncol, 2019, 12:92.
[6] Madden K, Kasler MK. Immune checkpoint inhibitors in lung cancer and melanoma[J]. Semin Oncol Nurs, 2019, 35:150932.
[7] Seront E, Catala G, Dermine A, et al. Immune checkpoint inhibitors as a real hope in advanced urothelial carcinoma[J]. Future Sci OA, 2018, 4:FSO341.
[8] Watson GA, Doi J, Hansen AR, et al. Novel strategies in immune checkpoint inhibitor drug development:how far are we from the paradigm shift?[J]. Br J Clin Pharmacol, 2020, 86:1753-1768.
[9] Gill J, Cetnar JP, Prasad V. A timeline of immune checkpoint inhibitor aporovals in small cell lung cancer[J]. Trends Cancer, 2020, 6:736-738.
[10] Ochoa De Olza M, Oliva M, Hierro C, et al. Early-drug development in the era of immuno-oncology:are we ready to face the challenges?[J]. Ann Oncol, 2018, 29:1727-1740.
[11] Marshall S, Madabushi R, Manolis E, et al. Model-informed drug discovery and development:current industry good practice and regulatory expectations and future perspectives[J]. CPT Pharmacometrics Syst Pharmacol, 2019, 8:87-96.
[12] Dunyak J, Mitchell P, Hamren B, et al. Integrating dose estimation into a decision-making framework for model-based drug development[J]. Pharm Stat, 2018, 17:155-168.
[13] Clancy CE, An G, Cannon WR, et al. Multiscale modeling in the clinic:drug design and development[J]. Ann Biomed Eng, 2016, 44:2591-2610.
[14] Bellanti F, Della Pasqua O. Modelling and simulation as research tools in paediatric drug development[J]. Eur J Clin Pharmacol, 2011, 67:75-86.
[15] Aarons L, Karlsson MO, Mentre F, et al. Role of modelling and simulation in phase I drug development[J]. Eur J Pharm Sci, 2001, 13:115-122.
[16] Chen WJ, Zhou TY, Lu W. Population pharmacokinetics and its application in new drug research[J]. Acta Pharm Sin (药学学报), 2017, 52:371-377.
[17] Barrett JS, Fossler MJ, Cadieu KD, et al. Pharmacometrics:a multidisciplinary field to facilitate critical thinking in drug development and translational research settings[J]. J Clin Pharmacol, 2008, 48:632-649.
[18] Sheiner LB. Computer-aided long-term anticoagulation therapy[J]. Comput Biomed Res, 1969, 2:507-518.
[19] Jelliffe RW, Buell J, Kalaba R, et al. A computer program for digitalis dosage regimens[J]. Math Biosci, 1970, 9:179-193.
[20] Sheiner LB. Learning versus confirming in clinical drug development[J]. Clin Pharmacol Ther, 1997, 61:275-291.
[21] Center for Drug Evaluation, NMPA. Guidelines for model-informed drug development (No.59,2020)[EB/OL]. 2020-12-31[2021-03-09]. http://www.cde.org.cn/attachmentout.do?mothed=list&id=be346add0358a356.
[22] Liu DY, Li L, Li LJ, et al. The value and general consideration of pharmacometric study in new drug development[J]. Chin J Clin Pharmacol Ther (中国临床药理学与治疗学), 2018, 23:961-973.
[23] Li J, Yang JB, Wang YZ. Applications of model-informed drug development (MIDD) on new drug research and development[J]. Chin J Clin Pharmacol Ther (中国临床药理学与治疗学), 2020, 25:1-8.
[24] Wolchok JD, Neyns B, Linette G, et al. Ipilimumab monotherapy in patients with pretreated advanced melanoma:a randomised, double-blind, multicentre, phase 2, dose-ranging study[J]. Lancet Oncol, 2010, 11:155-164.
[25] Agrawal S, Feng Y, Roy A, et al. Nivolumab dose selection:challenges, opportunities, and lessons learned for cancer immunotherapy[J]. J Immunother Cancer, 2016, 4:72.
[26] Lindauer A, Valiathan CR, Mehta K, et al. Translational pharmacokinetic/pharmacodynamic modeling of tumor growth inhibition supports dose-range selection of the anti-PD-1 antibody pembrolizumab[J]. CPT Pharmacometrics Syst Pharmacol, 2017, 6:11-20.
[27] Elassaiss-Schaap J, Rossenu S, Lindauer A, et al. Using model-based "learn and confirm" to reveal the pharmacokinetics-pharmacodynamics relationship of pembrolizumab in the KEYNOTE-001 trial[J]. CPT Pharmacometrics Syst Pharmacol, 2017, 6:21-28.
[28] Heery CR, GHOS Coyne, Marte JL, et al. Pharmacokinetic profile and receptor occupancy of avelumab (MSB0010718C), an anti-PD-L1 monoclonal antibody, in a phase I, open-label, dose escalation trial in patients with advanced solid tumors[J]. J Clin Oncol, 2015, 33:3055.
[29] Jin C, Zheng Y, Jin X, et al. Exposure-efficacy and safety analysis of durvalumab in patients with urothelial carcinoma (UC) and other solid tumors[J]. J Clin Oncol, 2017, 35:2568.
[30] Baverel PG, Dubois VFS, Jin CY, et al. Population pharmacokinetics of durvalumab in cancer patients and association with longitudinal biomarkers of disease status[J]. Clin Pharmacol Ther, 2018, 103:631-642.
[31] Feng Y, Masson E, Dai D, et al. Model-based clinical pharmacology profiling of ipilimumab in patients with advanced melanoma[J]. Br J Clin Pharmacol, 2014, 78:106-117.
[32] Bajaj G, Wang X, Agrawal S, et al. Model-based population pharmacokinetic analysis of nivolumab in patients with solid tumors[J]. CPT Pharmacometrics Syst Pharmacol, 2017, 6:58-66.
[33] Ahamadi M, Freshwater T, Prohn M, et al. Model-based characterization of the pharmacokinetics of pembrolizumab:a humanized anti-PD-1 monoclonal antibody in advanced solid tumors[J]. CPT Pharmacometrics Syst Pharmacol, 2017, 6:49-57.
[34] Chatterjee MS, Elassaiss-Schaap J, Lindauer A, et al. Population pharmacokinetic/pharmacodynamic modeling of tumor size dynamics in pembrolizumab-treated advanced melanoma[J]. CPT Pharmacometrics Syst Pharmacol, 2017, 6:29-39.
[35] Stroh M, Winter H, Marchand M, et al. Clinical pharmacokinetics and pharmacodynamics of atezolizumab in metastatic urothelial carcinoma[J]. Clin Pharmacol Ther, 2017, 102:305-312.
[36] Shemesh CS, Chanu P, Jamsen K, et al. Population pharmacokinetics, exposure-safety, and immunogenicity of atezolizumab in pediatric and young adult patients with cancer[J]. J Immunother Cancer, 2019, 7:314.
[37] Wilkins J, Brockhaus B, Wang S, et al. Population pharmacokinetic analysis of avelumab in different cancer types[J]. J Pharmacokinet Pharmacodyn, 2017, 44:1-143.
[38] Ogasawara K, Newhall K, Maxwell SE, et al. Population pharmacokinetics of an anti-PD-L1 antibody, durvalumab in patients with hematologic malignancies[J]. Clin Pharmacokinet, 2020, 59:217-227.
[39] de Greef R, Elassaiss-Schaap J, Chatterjee M, et al. Pembrolizumab:role of modeling and simulation in bringing a novel immunotherapy to patients with melanoma[J]. CPT Pharmacometrics Syst Pharmacol, 2017, 6:5-7.
[40] Li J, Yan F, Yang JB, et al. Application of model-informed drug development approach in dose opti-mization:insights from the modification of nivolumab dosage regimen[J]. Chin J Clin Pharmacol Ther (中国临床药理学与治疗学), 2020, 25:408-412.
[41] Freshwater T, Kondic A, Ahamadi M, et al. Evaluation of dosing strategy for pembrolizumab for oncology indications[J]. J Immunother Cancer, 2017, 5:43.
[42] Hall E, Zhang J, Kim EJ, et al. Economics of alternative dosing strategies for pembrolizumab and nivolumab at a single academic cancer center[J]. Cancer Med, 2020, 9:2106-2112.
[43] Lala M, Li TR, De Alwis DP, et al. A six-weekly dosing schedule for pembrolizumab in patients with cancer based on evaluation using modelling and simulation[J]. Eur J Cancer, 2020, 131:68-75.
[44] Morrissey KM, Marchand M, Patel H, et al. Alternative dosing regimens for atezolizumab:an example of model-informed drug development in the postmarketing setting[J]. Cancer Chemother Pharmacol, 2019, 84:1257-1267.
[45] Novakovic AM, Wilkins JJ, Dai H, et al. Changing body weight-based dosing to a flat dose for avelumab in metastatic merkel cell and advanced urothelial carcinoma[J]. Clin Pharmacol Ther, 2020, 107:588-596.
[46] Baverel P, Dubois V, Jin C, et al. Population pharmacokinetics of durvalumab and fixed dosing regimens in patients with advanced solid tumors[J]. J Clin Oncol, 2017, 35:2566.
[47] Patnaik A, Kang SP, Rasco D, et al. Phase I study of pembrolizumab (MK-3475; anti-PD-1 monoclonal antibody) in patients with advanced solid tumors[J]. Clin Cancer Res, 2015, 21:4286-4293.
[48] US Food and Drug Administration. Label of KEYTRUDA® (pembrolizumab) injection[EB/OL]. 2020-06-17[2020-10-07]. https://www.accessdata.fda.gov/drugsatfda_docs/label/2020/125514s071s090lbl.pdf.
[49] Kang SP, Gergich K, Lubiniecki GM, et al. Pembrolizumab KEYNOTE-001:an adaptive study leading to accelerated approval for two indications and a companion diagnostic[J]. Ann Oncol, 2017, 28:1388-1398.
[50] Thu Oanh D, Ogunniyi A, Barbee MS, et al. Pembrolizumab for the treatment of PD-L1 positive advanced or metastatic non-small cell lung cancer[J]. Expert Rev Anticancer Ther, 2016, 16:13-20.
[51] Keizer RJ, Huitema ADR, Schellens JHM, et al. Clinical pharmacokinetics of therapeutic monoclonal antibodies[J]. Clin Pharmacokinet, 2010, 49:493-507.
[52] Mould DR, Green B. Pharmacokinetics and pharmacodynamics of monoclonal antibodies concepts and lessons for drug development[J]. BioDrugs, 2010, 24:23-39.
[53] Garg A, Balthasar JP. Physiologically-based pharmacokinetic (PBPK) model to predict IgG tissue kinetics in wild-type and FcRn-knockout mice[J]. J Pharmacokinet Pharmacodyn, 2007, 34:687-709.
[54] Renner A, Burotto M, Rojas C. Immune checkpoint inhibitor dosing:can we go lower without compromising clinical efficacy?[J]. J Glob Oncol, 2019, 5:1-5.
[55] JJMA Hendrikx, JBaG Haanen, Voest EE, et al. Fixed dosing of monoclonal antibodies in oncology[J]. Oncologist, 2017, 22:1212-1221.
[56] US Food and Drug Administration. FDA approves new dosing regimen for pembrolizumab[EB/OL]. 2020-04-29[2020-10-07]. https://www.fda.gov/drugs/drug-approvals-and-databases/fda-approves-new-dosing-regimen-pembrolizumab.