Asia-Inclusive Clinical Research and Development Enabled by Translational Science and Quantitative Clinical Pharmacology: Toward a Culture That Challenges the Status Quo

被引:12
作者
Venkatakrishnan, Karthik [1 ,4 ]
Gupta, Neeraj [1 ]
Smith, Patrick F. [2 ]
Lin, Tiffany [2 ]
Lineberry, Neil [1 ]
Ishida, Tatiana [1 ]
Wang, Lin [3 ]
Rogge, Mark [1 ,5 ]
机构
[1] Takeda Dev Ctr Amer Inc, Lexington, MA 02421 USA
[2] Certara Inc, Princeton, NJ USA
[3] Takeda Dev Ctr Asia, Shanghai, Peoples R China
[4] EMD Serono Res & Dev Inst Inc, Billerica, MA 01821 USA
[5] Univ Florida, Ctr Pharmacometr & Syst Pharmacol, Orlando, FL USA
关键词
KINASE INHIBITOR ALISERTIB; CYTOCHROME-P450; ENZYMES; INVESTIGATIONAL AURORA; PHARMACOKINETIC MODEL; PHASE-I; CANCER; DRUG; CHINESE; POPULATIONS; CLEARANCE;
D O I
10.1002/cpt.2591
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Access lag to innovative therapies in Asian populations continues to present a challenge to global health. Recent progressive changes in the global regulatory landscape, including newer guidelines, are enabling simultaneous global drug development and near-simultaneous global drug registration. The International Conference on Harmonization (ICH) E17 guideline outlines general principles for the design and analysis of multiregional clinical trials (MRCTs). We posit that translational research and quantitative clinical pharmacology tools are core enablers for Asia-inclusive global drug development aligned with ICH E17 principles. Assessment of ethnic sensitivity should be initiated early in the development lifecycle to inform the need for, and extent of, Asian phase I ethno-bridging data. Relevant ethno-bridging data may be generated as standalone Asian phase I trials, as part of Western First-In-Human trials, or under accelerated development settings as a lead-in phase in an MRCT. Quantitative understanding of human clearance mechanisms and pharmacogenetic factors is vital to forecasting ethnic sensitivity in drug exposure using physiologically-based pharmacokinetic models. Stratification factors to control heterogeneity in MRCTs can be identified by reverse translational research incorporating pharmacometric disease models and model-based meta-analyses. Because epidemiological variations can extend to the molecular level, quantitative systems pharmacology models may be useful in forecasting how molecular variation in therapeutic targets or pathway proteins across populations might impact treatment outcomes. Through prospective evaluation of conservation in drug- and disease-related intrinsic and extrinsic factors, a pooled East Asian region can be implemented in Asia-inclusive MRCTs to maximize efficiency in substantiating evidence of benefit-risk for the region at-large with a Totality of Evidence approach.
引用
收藏
页码:298 / 309
页数:12
相关论文
共 91 条
[1]   Mapping Human Genetic Diversity in Asia [J].
Abdulla, Mahmood Ameen ;
Ahmed, Ikhlak ;
Assawamakin, Anunchai ;
Bhak, Jong ;
Brahmachari, Samir K. ;
Calacal, Gayvelline C. ;
Chaurasia, Amit ;
Chen, Chien-Hsiun ;
Chen, Jieming ;
Chen, Yuan-Tsong ;
Chu, Jiayou ;
Cutiongco-de la Paz, Eva Maria C. ;
De Ungria, Maria Corazon A. ;
Delfin, Frederick C. ;
Edo, Juli ;
Fuchareon, Suthat ;
Ghang, Ho ;
Gojobori, Takashi ;
Han, Junsong ;
Ho, Sheng-Feng ;
Hoh, Boon Peng ;
Huang, Wei ;
Inoko, Hidetoshi ;
Jha, Pankaj ;
Jinam, Timothy A. ;
Jin, Li ;
Jung, Jongsun ;
Kangwanpong, Daoroong ;
Kampuansai, Jatupol ;
Kennedy, Giulia C. ;
Khurana, Preeti ;
Kim, Hyung-Lae ;
Kim, Kwangjoong ;
Kim, Sangsoo ;
Kim, Woo-Yeon ;
Kimm, Kuchan ;
Kimura, Ryosuke ;
Koike, Tomohiro ;
Kulawonganunchai, Supasak ;
Kumar, Vikrant ;
Lai, Poh San ;
Lee, Jong-Young ;
Lee, Sunghoon ;
Liu, Edison T. ;
Majumder, Partha P. ;
Mandapati, Kiran Kumar ;
Marzuki, Sangkot ;
Mitchell, Wayne ;
Mukerji, Mitali ;
Naritomi, Kenji .
SCIENCE, 2009, 326 (5959) :1541-1545
[2]   Liquid Biopsy Enables Quantification of the Abundance and Interindividual Variability of Hepatic Enzymes and Transporters [J].
Achour, Brahim ;
Al-Majdoub, Zubida M. ;
Grybos-Gajniak, Agnieszka ;
Lea, Kristi ;
Kilford, Peter ;
Zhang, Mian ;
Knight, David ;
Barber, Jill ;
Schageman, Jeoffrey ;
Rostami-Hodjegan, Amin .
CLINICAL PHARMACOLOGY & THERAPEUTICS, 2021, 109 (01) :222-232
[3]   Physiologically-based pharmacokinetic model predictions of inter-ethnic differences in imatinib pharmacokinetics and dosing regimens [J].
Adiwidjaja, Jeffry ;
Gross, Annette S. ;
Boddy, Alan, V ;
McLachlan, Andrew J. .
BRITISH JOURNAL OF CLINICAL PHARMACOLOGY, 2022, 88 (04) :1735-1750
[4]   Pivotal Considerations for Optimal Deployment of Healthy Volunteers in Oncology Drug Development [J].
Ahmed, Mariam A. ;
Patel, Chirag ;
Drezner, Nicole ;
Helms, Whitney ;
Tan, Weiwei ;
Stypinski, Daria .
CTS-CLINICAL AND TRANSLATIONAL SCIENCE, 2020, 13 (01) :31-40
[5]   Points to Consider for Implementation of the ICH E17 Guideline: Learning from Past Multiregional Clinical Trials in Japan [J].
Asano, Kunihito ;
Aoi, Yoko ;
Kamada, Shuji ;
Uyama, Yoshiaki ;
Tohkin, Masahiro .
CLINICAL PHARMACOLOGY & THERAPEUTICS, 2021, 109 (06) :1555-1563
[6]   TAK-264 (MLN0264) in Previously Treated Asian Patients with Advanced Gastrointestinal Carcinoma Expressing Guanylyl Cyclase C: Results from an Open-Label, Non-randomized Phase 1 Study [J].
Bang, Yung-Jue ;
Takano, Toshimi ;
Lin, Chia-Chi ;
Fasanmade, Adedigbo ;
Yang, Huyuan ;
Danaee, Hadi ;
Asato, Takayuki ;
Kalebic, Thea ;
Wang, Hui ;
Doi, Toshihiko .
CANCER RESEARCH AND TREATMENT, 2018, 50 (02) :398-404
[7]   Differences in Cytochrome P450-Mediated Pharmacokinetics Between Chinese and Caucasian Populations Predicted by Mechanistic Physiologically Based Pharmacokinetic Modelling [J].
Barter, Zoe E. ;
Tucker, Geoffrey T. ;
Rowland-Yeo, Karen .
CLINICAL PHARMACOKINETICS, 2013, 52 (12) :1085-1100
[8]   Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients [J].
Baruch, Erez N. ;
Youngster, Ilan ;
Ben-Betzalel, Guy ;
Ortenberg, Rona ;
Lahat, Adi ;
Katz, Lior ;
Adler, Katerina ;
Dick-Necula, Daniela ;
Raskin, Stephen ;
Bloch, Naamah ;
Rotin, Daniil ;
Anafi, Liat ;
Avivi, Camila ;
Melnichenko, Jenny ;
Steinberg-Silman, Yael ;
Mamtani, Ronac ;
Harati, Hagit ;
Asher, Nethanel ;
Shapira-Frommer, Ronnie ;
Brosh-Nissimov, Tal ;
Eshet, Yael ;
Ben-Simon, Shira ;
Ziv, Oren ;
Khan, Md Abdul Wadud ;
Amit, Moran ;
Ajami, Nadim J. ;
Barshack, Iris ;
Schachter, Jacob ;
Wargo, Jennifer A. ;
Koren, Omry ;
Markel, Gal ;
Boursi, Ben .
SCIENCE, 2021, 371 (6529) :602-+
[9]  
Center for Drug Evaluation and Research, 2013, APPL NUMB 205123ORIG
[10]   Quantitative Systems Pharmacology Approaches for Immuno-Oncology: Adding Virtual Patients to the Development Paradigm [J].
Chelliah, Vijayalakshmi ;
Lazarou, Georgia ;
Bhatnagar, Sumit ;
Gibbs, John P. ;
Nijsen, Marjoleen ;
Ray, Avijit ;
Stoll, Brian ;
Thompson, R. Adam ;
Gulati, Abhishek ;
Soukharev, Serguei ;
Yamada, Akihiro ;
Weddell, Jared ;
Sayama, Hiroyuki ;
Oishi, Masayo ;
Wittemer-Rump, Sabine ;
Patel, Chirag ;
Niederalt, Christoph ;
Burghaus, Rolf ;
Scheerans, Christian ;
Lippert, Joerg ;
Kabilan, Senthil ;
Kareva, Irina ;
Belousova, Natalya ;
Rolfe, Alex ;
Zutshi, Anup ;
Chenel, Marylore ;
Venezia, Filippo ;
Fouliard, Sylvain ;
Oberwittler, Heike ;
Scholer-Dahirel, Alix ;
Lelievre, Helene ;
Bottino, Dean ;
Collins, Sabrina C. ;
Nguyen, Hoa Q. ;
Wang, Haiqing ;
Yoneyama, Tomoki ;
Zhu, Andy Z. X. ;
van der Graaf, Piet H. ;
Kierzek, Andrzej M. .
CLINICAL PHARMACOLOGY & THERAPEUTICS, 2021, 109 (03) :605-618