Abstract：
Therapeutic cancer vaccines are novel immuno-therapeutics, aiming to improve clinical outcomes with other immunotherapies. However, obstacles to their successful clinical development remain, which model-informed drug development approaches may address. UV1 is a telomerase based therapeutic cancer vaccine candidate being investigated in phase I clinical trials for multiple indications. We developed a mechanism-based model structure, using a nonlinear mixed-effects modeling techniques, based on longitudinal tumor sizes (sum of the longest diameters, SLD), UV1-specific immunological assessment (stimulation index, SI) and overall survival (OS) data obtained from a UV1 phase I trial including non-small cell lung cancer (NSCLC) patients and a phase I/IIa trial including malignant melanoma (MM) patients. The final structure comprised a mechanistic tumor growth dynamics (TGD) model, a model describing the probability of observing a UV1-specific immune response (SI ≥ 3) and a time-to-event model for OS. The mechanistic TGD model accounted for the interplay between the vaccine peptides, immune system and tumor. The model-predicted UV1-specific effector CD4+ T cells induced tumor shrinkage with half-lives of 103 and 154 days in NSCLC and MM patients, respectively. The probability of observing a UV1-specific immune response was mainly driven by the model-predicted UV1-specific effector and memory CD4+ T cells. A high baseline SLD and a high relative increase from nadir were identified as main predictors for a reduced OS in NSCLC and MM patients, respectively. Our model predictions highlighted that additional maintenance doses, i.e. UV1 administration for longer periods, may result in more sustained tumor size shrinkage.
摘要：
治疗性癌症疫苗是新型的免疫疗法，旨在改善其他免疫疗法的临床结果。然而,他们成功的临床发展的障碍仍然存在，哪些模型知情药物开发方法可以解决。UV1是一种基于端粒酶的治疗性癌症候选疫苗，正在I期临床试验中针对多种适应症进行研究。我们开发了一种基于机制的模型结构，使用非线性混合效果建模技术，基于纵向肿瘤大小(最长直径的总和，SLD),UV1特异性免疫评估(刺激指数，SI）和从包括非小细胞肺癌（NSCLC）患者的UV1I期试验和包括恶性黑色素瘤（MM）患者的I/IIa期试验获得的总生存期（OS）数据。最终结构包括机械性肿瘤生长动力学（TGD）模型，描述观察到UV1特异性免疫应答(SI≥3)的概率的模型和OS的事件发生时间模型.机制TGD模型解释了疫苗肽之间的相互作用，免疫系统和肿瘤。模型预测的UV1特异性效应CD4+T细胞在NSCLC和MM患者中诱导肿瘤缩小，半衰期为103和154天，分别。观察到UV1特异性免疫应答的概率主要由模型预测的UV1特异性效应子和记忆CD4+T细胞驱动。高基线SLD和相对于最低点的高相对增加被确定为NSCLC和MM患者OS降低的主要预测因子。分别。我们的模型预测强调了额外的维持剂量，即UV1管理时间较长，可能导致更持续的肿瘤大小缩小。
