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随机货架规模模型框架在冷冻干燥过程中的冻结阶段。

Stochastic shelf-scale modeling framework for the freezing stage in freeze-drying processes.

机构信息

Institute of Energy and Process Engineering, ETH Zurich, Sonneggstrasse 3, 8092 Zurich, Switzerland.

The Janssen Pharmaceutical Companies of Johnson & Johnson, Hochstrasse 201, 8200 Schaffhausen, Switzerland.

出版信息

Int J Pharm. 2022 Feb 5;613:121276. doi: 10.1016/j.ijpharm.2021.121276. Epub 2021 Nov 9.

DOI:10.1016/j.ijpharm.2021.121276
PMID:34767908
Abstract

Freezing and freeze-drying processes are commonly used to improve the stability and thus shelf life of pharmaceutical formulations. Despite strict product quality requirements, batch heterogeneity is widely observed in frozen products, thus potentially causing process failure. Such heterogeneity is the result of the stochasticity of ice nucleation and the variability in heat transfer among vials, which lead to unique freezing histories of individual vials. We present for the first time a modeling framework for large-scale freezing processes of vials on a shelf and publish an open source implementation in the form of a python package on pypi. The model is based on first principles and couples heat transfer with ice nucleation kinetics, thus enabling studies on batch heterogeneity. Ice nucleation is assumed to be an inhomogeneous Poisson process and it is simulated using a Monte Carlo approach. We applied the model to understand the individual pathways leading to batch heterogeneity. Our simulations revealed a novel mechanism how ice nucleation leads to heterogeneity based on thermal interaction among vials. We investigated the effect of various cooling protocols, namely shelf-ramped cooling, holding steps and controlled nucleation, on the nucleation and solidification behavior across the shelf. We found that under rather general conditions holding schemes lead to similar solidification times, as in the case of controlled nucleation, thus identifying a potential pathway for freezing process optimization.

摘要

冷冻和冻干工艺通常用于提高药物制剂的稳定性,从而延长其保质期。尽管对产品质量有严格的要求,但在冷冻产品中广泛观察到批次不均匀性,从而可能导致工艺失败。这种不均匀性是由于成核的随机性和小瓶之间传热的可变性导致的,这导致了各个小瓶独特的冻结历史。我们首次提出了一种在货架上大规模冷冻小瓶的建模框架,并以 python 包的形式在 pypi 上发布了一个开源实现。该模型基于第一性原理,将传热与成核动力学耦合,从而能够研究批次不均匀性。假设成核是一个不均匀的泊松过程,并使用蒙特卡罗方法进行模拟。我们应用该模型来了解导致批次不均匀性的个体途径。我们的模拟揭示了一种新的机制,即冰核化如何基于小瓶之间的热相互作用导致不均匀性。我们研究了各种冷却方案,即货架斜率冷却、保持步骤和控制成核,对货架上成核和固化行为的影响。我们发现,在相当一般的条件下,保持方案导致类似的固化时间,就像控制成核一样,从而为冷冻过程优化确定了一个潜在途径。

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