A review on the modernization of pharmaceutical development and manufacturing – Trends, perspectives, and the role of mathematical modeling

• Published in: International journal of pharmaceutics Vol. 620; p. 121715
• Main Authors: Destro, Francesco, Barolo, Massimiliano
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 25.05.2022
• Subjects: Industrial digitalization; Industry 4.0; Pharmaceutical development; Pharmaceutical industry; Pharmaceutical manufacturing; Quality-by-control; Quality-by-design; Quality-by-control; Pharmaceutical development; Quality-by-design; Pharmaceutical manufacturing; Industrial digitalization; Industry 4.0; Pharmaceutical industry
• ISSN: 0378-5173; 1873-3476
• DOI: 10.1016/j.ijpharm.2022.121715

[Display omitted] Recently, the pharmaceutical industry has been facing several challenges associated to the use of outdated development and manufacturing technologies.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.