Quantitative Systems Pharmacology approaches for immuno‐oncology: adding virtual patients to the development paradigm

Drug development in oncology commonly exploits the tools of molecular biology to gain therapeutic benefit through reprograming of cellular responses. In immuno‐oncology (IO) the aim is to direct the patient’s own immune system to fight cancer. After remarkable successes of antibodies targeting PD1/PD‐L1 and CTLA4 receptors in targeted patient populations, the focus of further development has shifted towards combination therapies. However, the current drug‐development approach of exploiting a vast number of possible combination targets and dosing regimens has proven to be challenging and is arguably inefficient. In particular, the unprecedented number of clinical trials testing different combinations may no longer be sustainable by the population of available patients. Further development in IO requires a step change in selection and validation of candidate therapies to decrease development attrition rate and limit the number of clinical trials. Quantitative Systems Pharmacology (QSP) proposes to tackle this challenge through mechanistic modelling and simulation…

Author(s): Vijayalakshmi Chelliah, Georgia Lazarou, Sumit Bhatnagar, John P. Gibbs, Marjoleen Nijsen, Avijit Ray, Brian Stoll, R. Adam Thompson, Abhishek Gulati, Serguei Soukharev, Akihiro Yamada, Jared Weddell, Hiroyuki Sayama, Masayo Oishi, Sabine Wittemer‐Rump, Chirag Patel, Christoph Niederalt, Rolf Burghaus, Christian Scheerans, Jörg Lippert, Senthil Kabilan, Irina Kareva, Natalya Belousova, Alex Rolfe, Anup Zutshi, Marylore Chenel, Filippo Venezia, Sylvain Fouliard, Heike Oberwittler, Alix Scholer‐Dahirel, Helene Lelievre, Dean Bottino, Sabrina C. Collins, Hoa Q. Nguyen, Haiqing Wang, Tomoki Yoneyama, Andy Z.X. Zhu, Piet H. van der Graaf, Andrzej M. Kierzek

Year: 2020 年 7 月 19 日

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