A review of algorithmic approaches for cell culture media optimization

• Published in: Frontiers in bioengineering and biotechnology Vol. 11; p. 1195294
• Main Authors: Zhou, Tianxun, Reji, Rinta, Kairon, Ryanjit Singh, Chiam, Keng Hwee
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 11.05.2023
• Subjects: Bioengineering and Biotechnology; culture media optimization; design of experiements; fermentation optimization; media optimization algorithm; metaheuistics; surrogate model; benchmark comparison; surrogate model; culture media optimization; design of experiements; media optimization algorithm; metaheuistics; fermentation optimization
• ISSN: 2296-4185; 2296-4185
• DOI: 10.3389/fbioe.2023.1195294

Cell culture media composition and culture conditions play a crucial role in product yield, quality and cost of production. Culture media optimization is the technique of improving media composition and culture conditions to achieve desired product outcomes. To achieve this, there have been many algorithmic methods proposed and used for culture media optimization in the literature. To help readers evaluate and decide on a method that best suits their specific application, we carried out a systematic review of the different methods from an algorithmic perspective that classifies, explains and compares the available methods. We also examine the trends and new developments in the area. This review provides recommendations to researchers regarding the suitable media optimization algorithm for their applications and we hope to also promote the development of new cell culture media optimization methods that are better suited to existing and upcoming challenges in this biotechnology field, which will be essential for more efficient production of various cell culture products.