Jackson Robert C
Pharmacometrics Ltd., Whittlesford, Cambridge CB22 4NZ, UK.
ISRN Pharmacol. 2012;2012:590626. doi: 10.5402/2012/590626. Epub 2012 Feb 16.
The development of pharmacodynamic (PD) biomarkers in oncology has implications for design of clinical protocols from preclinical data and for predicting clinical outcomes from early clinical data. Two classes of biomarkers have received particular attention. Phosphoproteins in biopsy samples are markers of inhibition of signalling pathways, target sites for many novel agents. Biomarkers of apoptosis in plasma can measure tumour cell killing by drugs in phase I clinical trials. The predictive power of PD biomarkers is enhanced by data modelling. With pharmacokinetic models, PD models form PK/PD models that predict the time course both of drug concentration and drug effects. If biomarkers of drug toxicity are also measured, the models can predict drug selectivity as well as efficacy. PK/PD models, in conjunction with disease models, make possible virtual clinical trials, in which multiple trial designs are assessed in silico, so the optimal trial design can be selected for experimental evaluation.
肿瘤学中药效学（PD）生物标志物的发展对基于临床前数据设计临床方案以及根据早期临床数据预测临床结果具有重要意义。两类生物标志物受到了特别关注。活检样本中的磷酸化蛋白是信号通路抑制的标志物，是许多新型药物的靶点。血浆中细胞凋亡的生物标志物可在I期临床试验中测量药物对肿瘤细胞的杀伤作用。数据建模增强了PD生物标志物的预测能力。通过药代动力学模型，PD模型形成PK/PD模型，可预测药物浓度和药物效应的时间进程。如果同时测量药物毒性的生物标志物，这些模型可以预测药物的选择性以及疗效。PK/PD模型与疾病模型相结合，使得虚拟临床试验成为可能，即在计算机上评估多种试验设计，从而可以选择最优的试验设计进行实验评估。
