论文标题
用于细胞制造中生物传感的无校准方法
A calibration-free method for biosensing in cell manufacturing
论文作者
论文摘要
嵌合抗原受体T细胞疗法在战斗癌症中表现出创新的治疗有效性。但是，由于细胞制造中固有的患者到患者的可变性，它非常昂贵。我们在这项工作中提出了一个新颖的无校准统计框架，以有效地恢复患者到患者的变异性下的关键质量属性。具体而言，我们通过特定于患者的校准参数对此变异性进行建模，并使用多个生物传感器的读数来构建患者不变性统计量，从而减轻了校准参数的效果。提出了精心提出的优化问题和算法框架，以找到最佳的患者侵入统计统计量和模型参数。使用患者不变性统计，我们可以恢复关注的关键质量属性，这是没有校准参数的。我们证明了在不同的模拟实验中提出的无校准方法的改进。在细胞制造案例研究中，我们的方法不仅有效地恢复了可行的细胞浓度进行监测，而且还揭示了细胞制造过程的见解。
Chimeric antigen receptor T cell therapy has demonstrated innovative therapeutic effectiveness in fighting cancers; however, it is extremely expensive due to the intrinsic patient-to-patient variability in cell manufacturing. We propose in this work a novel calibration-free statistical framework to effectively recover critical quality attributes under the patient-to-patient variability. Specifically, we model this variability via a patient-specific calibration parameter, and use readings from multiple biosensors to construct a patient-invariance statistic, thereby alleviating the effect of the calibration parameter. A carefully formulated optimization problem and an algorithmic framework are presented to find the best patient-invariance statistic and the model parameters. Using the patient-invariance statistic, we can recover the critical quality attribute of interest, free from the calibration parameter. We demonstrate improvements of the proposed calibration-free method in different simulation experiments. In the cell manufacturing case study, our method not only effectively recovers viable cell concentration for monitoring, but also reveals insights for the cell manufacturing process.
