Richter-Helm BioLogics GmbH & Co. KG, Suhrenkamp 59, 22335 Hamburg, Germany.
Research Division Biochemical Engineering, Institute of Chemical Environmental and Bioscience Engineering, Vienna University of Technology, Vienna, Austria.
Drug Discov Today Technol. 2020 Dec;38:9-24. doi: 10.1016/j.ddtec.2021.04.001. Epub 2021 Apr 24.
Current trends in the biopharmaceutical market such as the diversification of therapies as well as the increasing time-to-market pressure will trigger the rethinking of bioprocess development and production approaches. Thereby, the importance of development time and manufacturing costs will increase, especially for microbial production. In the present review, we investigate three technological approaches which, to our opinion, will play a key role in the future of biopharmaceutical production. The first cornerstone of process development is the generation and effective utilization of platform knowledge. Building processes on well understood microbial and technological platforms allows to accelerate early-stage bioprocess development and to better condense this knowledge into multi-purpose technologies and applicable mathematical models. Second, the application of verified scale down systems and in silico models for process design and characterization will reduce the required number of large scale batches before dossier submission. Third, the broader availability of mathematical process models and the improvement of process analytical technologies will increase the applicability and acceptance of advanced control and process automation in the manufacturing scale. This will reduce process failure rates and subsequently cost of goods. Along these three aspects we give an overview of recently developed key tools and their potential integration into bioprocess development strategies.
当前生物制药市场的趋势，如治疗方法的多样化以及上市时间压力的增加，将促使人们重新思考生物工艺开发和生产方法。因此，开发时间和制造成本的重要性将会增加，特别是对于微生物生产而言。在本综述中，我们研究了三种技术方法，我们认为这三种方法将在未来的生物制药生产中发挥关键作用。工艺开发的第一个基石是平台知识的产生和有效利用。在充分了解的微生物和技术平台上构建工艺，可以加速早期生物工艺的开发，并将更多的知识浓缩到多用途技术和适用的数学模型中。其次，验证的缩小规模系统和计算模型在工艺设计和特性描述中的应用将减少提交档案前大型批次所需的数量。第三，更广泛地应用数学过程模型和改进过程分析技术将提高先进控制和生产自动化在制造规模上的适用性和可接受性。这将降低工艺故障率，从而降低产品成本。沿着这三个方面，我们概述了最近开发的关键工具及其在生物工艺开发策略中的潜在集成。
