Hutchinson L G, Grimm O
Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070, Basel, Switzerland.
NPJ Digit Med. 2022 Jul 12;5(1):92. doi: 10.1038/s41746-022-00636-3.
In oncology clinical trials, on-treatment biopsy samples are taken to confirm the mode of action of new molecules, among other reasons. Yet, the time point of sample collection is typically scheduled according to 'Expert Best Guess'. We have developed an approach integrating digital pathology and mathematical modelling to provide clinical teams with quantitative information to support this decision. Using digitised biopsies from an ongoing clinical trial as the input to an agent-based mathematical model, we have quantitatively optimised and validated the model demonstrating that it accurately recapitulates observed biopsy samples. Furthermore, the validated model can be used to predict the dynamics of simulated biopsies, with applications from protocol design for phase 1-2 studies to the conception of combination therapies, to personalised healthcare.
在肿瘤学临床试验中,采集治疗期间的活检样本有多种原因,其中包括确认新分子的作用模式。然而,样本采集的时间点通常是根据“专家的最佳猜测”来安排的。我们开发了一种将数字病理学和数学建模相结合的方法,为临床团队提供定量信息以支持这一决策。通过将一项正在进行的临床试验中的数字化活检作为基于主体的数学模型的输入,我们对该模型进行了定量优化和验证,证明它能准确再现观察到的活检样本。此外,经过验证的模型可用于预测模拟活检的动态变化,其应用范围从1-2期研究的方案设计到联合疗法构想,再到个性化医疗。