Applying quantitative and systems pharmacology to drug development and beyond: An introduction to clinical pharmacologists

被引:0
作者
Ramasubbu, Mathan Kumar [1 ]
Paleja, Bhairav [2 ]
Srinivasann, Anand [1 ]
Maiti, Rituparna [1 ]
Kumar, Rukmini [2 ]
机构
[1] All India Inst Med Sci, Dept Pharmacol, Bhubaneswar, Odisha, India
[2] Vantage Res, Chennai, Tamil Nadu, India
关键词
Clinical pharmacologists; drug development; mathematical modeling; pharmacokinetics; pharmacokinetic-pharmacodynamic; physiology-based pharmacokinetic; quantitative and systems pharmacology; MATHEMATICAL-MODEL; DISCOVERY; CANAGLIFLOZIN; PERSPECTIVE; GLUCOSE; QSP;
D O I
10.4103/ijp.ijp_644_23
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Quantitative and systems pharmacology (QSP) is an innovative and integrative approach combining physiology and pharmacology to accelerate medical research. This review focuses on QSP's pivotal role in drug development and its broader applications, introducing clinical pharmacologists/researchers to QSP's quantitative approach and the potential to enhance their practice and decision-making. The history of QSP adoption reveals its impact in diverse areas, including glucose regulation, oncology, autoimmune disease, and HIV treatment. By considering receptor-ligand interactions of various cell types, metabolic pathways, signaling networks, and disease biomarkers simultaneously, QSP provides a holistic understanding of interactions between the human body, diseases, and drugs. Integrating knowledge across multiple time and space scales enhances versatility, enabling insights into personalized responses and general trends. QSP consolidates vast data into robust mathematical models, predicting clinical trial outcomes and optimizing dosing based on preclinical data. QSP operates under a "learn and confirm paradigm," integrating experimental findings to generate testable hypotheses and refine them through precise experimental designs. An interdisciplinary collaboration involving expertise in pharmacology, biochemistry, genetics, mathematics, and medicine is vital. QSP's utility in drug development is demonstrated through integration in various stages, predicting drug responses, optimizing dosing, and evaluating combination therapies. Challenges exist in model complexity, communication, and peer review. Standardized workflows and evaluation methods ensure reliability and transparency.
引用
收藏
页码:268 / 276
页数:9
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