Novartis Pharma AG, Basel, Switzerland.
Eur J Cancer. 2010 Jan;46(1):21-32. doi: 10.1016/j.ejca.2009.10.011.
Physiologically based modelling of pharmacodynamics/toxicodynamics requires an a priori knowledge on the underlying mechanisms causing toxicity or causing the disease. In the context of cancer, the objective of the expert meeting was to discuss the molecular understanding of the disease, modelling approaches used so far to describe the process, preclinical models of cancer treatment and to evaluate modelling approaches developed based on improved knowledge. Molecular events in cancerogenesis can be detected using 'omics' technology, a tool applied in experimental carcinogenesis, but also for diagnostics and prognosis. The molecular understanding forms the basis for new drugs, for example targeting protein kinases specifically expressed in cancer. At present, empirical preclinical models of tumour growth are in great use as the development of physiological models is cost and resource intensive. Although a major challenge in PKPD modelling in oncology patients is the complexity of the system, based in part on preclinical models, successful models have been constructed describing the mechanism of action and providing a tool to establish levels of biomarker associated with efficacy and assisting in defining biologically effective dose range selection for first dose in man. To follow the concentration in the tumour compartment enables to link kinetics and dynamics. In order to obtain a reliable model of tumour growth dynamics and drug effects, specific aspects of the modelling of the concentration-effect relationship in cancer treatment that need to be accounted for include: the physiological/circadian rhythms of the cell cycle; the treatment with combinations and the need to optimally choose appropriate combinations of the multiple agents to study; and the schedule dependence of the response in the clinical situation.
生理药效/toxicodynamic 建模需要对导致毒性或导致疾病的潜在机制有先验知识。在癌症方面，专家会议的目的是讨论对该疾病的分子理解、迄今为止用于描述该过程的建模方法、癌症治疗的临床前模型，并评估基于改进知识而开发的建模方法。可以使用“组学”技术检测癌症发生中的分子事件，这是一种应用于实验性致癌作用的工具，也可用于诊断和预后。分子理解是开发新药的基础，例如针对特异性表达于癌症中的蛋白激酶的药物。目前，肿瘤生长的经验性临床前模型被广泛应用，因为生理模型的开发既耗费成本又耗费资源。尽管肿瘤患者 PKPD 建模的一个主要挑战是系统的复杂性，部分基于临床前模型，但已经构建了成功的模型来描述作用机制，并提供了一种工具来确定与疗效相关的生物标志物水平，并有助于定义首个人体剂量的生物学有效剂量范围选择。跟踪肿瘤部位的浓度可以将动力学和动态学联系起来。为了获得肿瘤生长动力学和药物作用的可靠模型，需要考虑癌症治疗中浓度-效应关系建模的特定方面，包括：细胞周期的生理/昼夜节律；联合治疗以及需要优化选择多种药物的适当组合进行研究；以及临床情况下反应的方案依赖性。
