Downstream Process Development and Engineering, Merck & Co., Inc., Kenilworth, NJ, USA.
Downstream Process Development and Engineering, Merck & Co., Inc., Kenilworth, NJ, USA.
J Chromatogr A. 2019 May 24;1593:54-62. doi: 10.1016/j.chroma.2019.01.063. Epub 2019 Jan 24.
Chromatography is a cornerstone of biologics downstream purification processes, and there is an ever increasing demand for improved speed and efficiency in process development. Scale-down models are used in process development to optimize operating conditions and study process robustness while expending as little time and material as possible. The advent of automated liquid handling systems and miniature columns has taken the efficiency of process development to another level by allowing up to eight column runs in parallel with column volumes under 1 ml. As expected, results between these miniature columns and typical lab/manufacturing scale columns can deviate due to scale dependent and/or configuration dependent differences. Regulatory guidelines do not require an exact match in scale-down and large scale data, but do require that small scale models account for scale effects, be representative of the commercial process, and be scientifically justified. Therefore, it is important to gain insight into what causes differences between scales and account for them during development. Mechanistic models can be used to understand the physics of the process (fluid flow, mass transfer, etc.) as a function of scale, and provide explanation for deviations that may be observed. We have used mechanistic modeling to study the factors leading to differences in pool sizes observed between scales, and to make predictions on lab scale pool sizes from miniature column data. Results indicate that changes in mass transfer parameters, specifically axial dispersion, between scales leads to the observed differences in pool size. Additionally, we have studied the effect of system differences between automated liquid handling systems and conventional preparative chromatography systems on elution pool volume. This work provides new insight into the fundamental differences observed between scales and overcomes the challenge of enabling the use of miniature column chromatography as a scale-down model for process characterization.
色谱法是生物制品下游纯化过程的基石，人们对提高工艺开发速度和效率的需求不断增加。在工艺开发中使用缩小规模模型来优化操作条件并研究工艺稳健性，同时尽可能少地消耗时间和材料。自动化液体处理系统和微型柱的出现通过允许在 1ml 以下的柱体积中同时进行多达 8 次柱运行，将工艺开发的效率提高到了另一个水平。可以预期，由于依赖于比例和/或配置的差异，这些微型柱与典型的实验室/生产规模柱之间的结果可能会有所不同。监管指南不要求缩小规模和大规模数据完全匹配，但要求小型模型考虑到规模效应，代表商业工艺，并具有科学依据。因此，了解导致不同规模之间差异的原因并在开发过程中加以考虑非常重要。机理模型可用于研究工艺的物理特性（流体流动、质量传递等）随比例的变化，并对可能观察到的偏差提供解释。我们已经使用机理建模来研究导致不同规模之间观察到的池大小差异的因素，并根据微型柱数据对实验室规模的池大小进行预测。结果表明，比例之间传质参数（特别是轴向扩散）的变化导致了观察到的池大小差异。此外，我们还研究了自动化液体处理系统和传统制备性色谱系统之间的系统差异对洗脱池体积的影响。这项工作提供了对不同规模之间观察到的基本差异的新见解，并克服了使用微型柱色谱作为工艺特性的缩小规模模型的挑战。
