论文标题
随机模拟不确定性分析以加速柔性生物制造过程开发
Stochastic Simulation Uncertainty Analysis to Accelerate Flexible Biomanufacturing Process Development
论文作者
论文摘要
在生物制药制造中的关键挑战和需求的推动下，我们提出了一个通用的元模型辅助随机模拟不确定性分析框架，以加速使用模块化设计的模拟模型的开发，以用于灵活生产过程。过程观察通常非常有限。因此，在系统性能估计中同时存在模拟和模型不确定性。在生物制药制造中，模型不确定性通常会主导。所提出的框架可以通过使用元模型辅助的自举方法来产生置信区间，该置信区间可以解释模拟和模型不确定性。此外，利用方差分解来估计每个模型不确定性来源的相对贡献以及模拟不确定性。该信息可用于改善系统平均性能估计。渐近分析为我们的方法提供了理论支持，而经验研究表明它具有良好的有限样本性能。
Motivated by critical challenges and needs from biopharmaceuticals manufacturing, we propose a general metamodel-assisted stochastic simulation uncertainty analysis framework to accelerate the development of a simulation model with modular design for flexible production processes. There are often very limited process observations. Thus, there exist both simulation and model uncertainties in the system performance estimates. In biopharmaceutical manufacturing, model uncertainty often dominates. The proposed framework can produce a confidence interval that accounts for simulation and model uncertainties by using a metamodel-assisted bootstrapping approach. Furthermore, a variance decomposition is utilized to estimate the relative contributions from each source of model uncertainty, as well as simulation uncertainty. This information can be used to improve the system mean performance estimation. Asymptotic analysis provides theoretical support for our approach, while the empirical study demonstrates that it has good finite-sample performance.
