Chen Emile P, Bondi Robert W, Zhang Carolyn, Price Daniel J, Ho Ming-Hsun, Armacost Kira A, DeMartino Michael P
Systems Modeling and Translational Biology, Computational Sciences, GlaxoSmithKline, Collegeville, Pennsylvania 19426, United States.
Molecular Design, Computational Sciences, GlaxoSmithKline, Collegeville, Pennsylvania 19426, United States.
J Med Chem. 2022 May 12;65(9):6926-6939. doi: 10.1021/acs.jmedchem.2c00330. Epub 2022 May 2.
Many critical decisions faced in early discovery require a thorough understanding of the dynamic behavior of pharmacological pathways following target engagement. From fundamental decisions on the optimal target to pursue and the ultimate drug product profile (combination of modality, potency, and compound properties) expected to elicit the desired clinical outcome to tactical program decisions such as what chemical series to pursue, what chemical properties require optimization, and what compounds to synthesize and progress, all demand detailed consideration of pharmacodynamics. Model-based target pharmacology assessment (mTPA) is a computational approach centered around large-scale virtual exploration of pharmacokinetic and pharmacodynamic models built early in discovery to guide these decisions. The present work summarizes several examples (use cases) from programs at GlaxoSmithKline that demonstrate the utility of mTPA throughout the drug discovery lifecycle.
早期发现阶段面临的许多关键决策都需要深入了解靶点结合后药理途径的动态行为。从关于选择最佳靶点的基本决策，到预期产生理想临床结果的最终药物产品概况（剂型、效力和化合物性质的组合），再到战术性项目决策，如选择何种化学系列、优化哪些化学性质以及合成和推进哪些化合物，所有这些都需要对药效学进行详细考量。基于模型的靶点药理学评估（mTPA）是一种计算方法，围绕在发现阶段早期构建的药代动力学和药效学模型进行大规模虚拟探索，以指导这些决策。本研究总结了葛兰素史克公司项目中的几个示例（用例），展示了mTPA在整个药物发现生命周期中的实用性。
