Simeoni Monica, De Nicolao Giuseppe, Magni Paolo, Rocchetti Maurizio, Poggesi Italo
Drug Discov Today Technol. 2013 Sep;10(3):e365-72. doi: 10.1016/j.ddtec.2012.07.004.
Xenograft models are commonly used in oncology drug development. Although there are discussions about their ability to generate meaningful data for the translation from animal to humans, it appears that better data quality and better design of the preclinical experiments, together with appropriate data analysis approaches could make these data more informative for clinical development. An approach based on mathematical modeling is necessary to derive experiment-independent parameters which can be linked with clinically relevant endpoints. Moreover, the inclusion of biomarkers as predictors of efficacy is a key step towards a more general mechanism-based strategy.
异种移植模型常用于肿瘤学药物开发。尽管对于其能否生成从动物到人类转化的有意义数据存在讨论,但似乎更好的数据质量、更好的临床前实验设计以及适当的数据分析方法可以使这些数据对临床开发更具参考价值。基于数学建模的方法对于推导与临床相关终点相关的、不依赖于实验的参数是必要的。此外,纳入生物标志物作为疗效预测指标是迈向更通用的基于机制策略的关键一步。