Destro Francesco, Barolo Massimiliano
CAPE-Lab - Computer-Aided Process Engineering Laboratory, Department of Industrial Engineering, University of Padova, via Marzolo 9, 35131 Padova PD, Italy.
CAPE-Lab - Computer-Aided Process Engineering Laboratory, Department of Industrial Engineering, University of Padova, via Marzolo 9, 35131 Padova PD, Italy.
Int J Pharm. 2022 May 25;620:121715. doi: 10.1016/j.ijpharm.2022.121715. Epub 2022 Mar 31.
Recently, the pharmaceutical industry has been facing several challenges associated to the use of outdated development and manufacturing technologies. The return on investment on research and development has been shrinking, and, at the same time, an alarming number of shortages and recalls for quality concerns has been registered. The pharmaceutical industry has been responding to these issues through a technological modernization of development and manufacturing, under the support of initiatives and activities such as quality-by-design (QbD), process analytical technology, and pharmaceutical emerging technology. In this review, we analyze this modernization trend, with emphasis on the role that mathematical modeling plays within it. We begin by outlining the main socio-economic trends of the pharmaceutical industry, and by highlighting the life-cycle stages of a pharmaceutical product in which technological modernization can help both achieve consistently high product quality and increase return on investment. Then, we review the historical evolution of the pharmaceutical regulatory framework, and we discuss the current state of implementation and future trends of QbD. The pharmaceutical emerging technology is reviewed afterwards, and a discussion on the evolution of QbD into the more effective quality-by-control (QbC) paradigm is presented. Further, we illustrate how mathematical modeling can support the implementation of QbD and QbC across all stages of the pharmaceutical life-cycle. In this respect, we review academic and industrial applications demonstrating the impact of mathematical modeling on three key activities within pharmaceutical development and manufacturing, namely design space description, process monitoring, and active process control. Finally, we discuss some future research opportunities on the use of mathematical modeling in industrial pharmaceutical environments.
最近,制药行业一直面临着与使用过时的研发和制造技术相关的若干挑战。研发投资回报率一直在下降,与此同时,因质量问题导致的短缺和召回数量惊人。在质量源于设计(QbD)、过程分析技术和制药新兴技术等倡议和活动的支持下,制药行业一直在通过研发和制造的技术现代化来应对这些问题。在本综述中,我们分析了这一现代化趋势,重点关注数学建模在其中所起的作用。我们首先概述制药行业的主要社会经济趋势,并强调制药产品生命周期中技术现代化有助于实现始终如一的高产品质量和提高投资回报率的阶段。然后,我们回顾制药监管框架的历史演变,并讨论QbD的当前实施状况和未来趋势。随后对制药新兴技术进行综述,并讨论QbD向更有效的质量源于控制(QbC)范式的演变。此外,我们阐述了数学建模如何在制药生命周期的各个阶段支持QbD和QbC的实施。在这方面,我们回顾了学术和工业应用,展示了数学建模对制药研发和制造中的三项关键活动,即设计空间描述、过程监测和主动过程控制的影响。最后,我们讨论了在工业制药环境中使用数学建模的一些未来研究机会。