Pharmacometrics Modelling-Based Dose-Finding and Synthetic Control Arms Established Using Longitudinal Analyses - Numerical analysis - Mathematical sc

肿瘤学领域的进步正在迅速改变许多癌症患者的预期寿命。治疗干预措施正在逐步转变，从对大量人群给予细胞毒药物的短暂间歇周期，直到病情恶化或死亡，到在较小人群中终生慢性治疗靶向和/或免疫调节分子的组合。这些进展在肿瘤药物开发中提出了几个挑战，将在本项目中解决：1.基于药物计量学的超过最大耐受量(MTD)的剂量发现，平衡长期有效性和安全性，是否为肿瘤临床药物开发提供了一种可行和成本效益高的方法？使用基于系统建模、估计和优化的方法，将探索肿瘤学药物开发中的几种剂量发现策略。这将基于虚拟发展计划，但环境将反映目前在肿瘤学中看到的情况。传统的MTD范例将与更广泛的剂量范围、更长期的疗效和安全性评估进行比较，决策将基于纵向分析。这将与成本分析相结合，以评估可行性和附加值。2.能否利用对历史临床试验数据和真实世界数据集的纵向分析来为I/II期试验建立合成对照装置，以提高肿瘤临床药物开发的效率并将成本降至最低？几个内部AZ数据集和外部数据库将被确定并用于纵向建模，将药物暴露、生物标记物、遗传学和其他信息与相关临床试验结果联系起来。这些努力将与正在进行的发展项目保持一致，重点将放在应用现有的建模和统计方法、促进决策和防止消极的关键试验。

Advancements in the field of oncology are rapidly changing the life expectancy of patients across many cancers. Therapeutic interventions are gradually shifting, from short intermittent cycles of cytotoxic drugs administered to large populations until progression or death, to the life-long chronic treatment of combinations of targeted and/or immunomodulating molecules in smaller populations. These advances raise several challenges in oncology drug development that will be tackled in this project: 1. Do pharmacometrics based dose findings beyond the Maximum Tolerated Dose (MTD), balancing longer-term efficacy and safety, provide a feasible and cost-effective approach to clinical drug development in oncology? Using a systems modelling estimation and optimisation based approach several dose-finding strategies in oncology drug development will be explored. This will be based on virtual development programmes, but the settings will reflect what is currently seen across oncology. The traditional MTD-paradigm will be compared with more extensive dose-ranging, longer-term efficacy and safety evaluations, with decision-making based on the longitudinal analysis. This will be tied in with an analysis of costs to evaluate the feasibility and added value. 2. Can longitudinal analyses of historical clinical trial data and real-world datasets be leveraged to establish synthetic control arms for phase I/II trials to increase efficiency and minimise costs in oncology clinical drug development? Several internal AZ datasets and external databases will be identified and used for longitudinal modelling, linking drug exposure, biomarkers, genetics and other information to relevant clinical trial outcomes. These efforts will be aligned with ongoing development projects and the focus will be on the application of existing modelling and statistical approaches, facilitation decision-making, and preventing negative pivotal trials.