Role of AI in Alternative Proteins

AI advancements have propelled the alternative protein field forward, revolutionising how researchers design, optimise, and scale up recombinant protein production, plant-based protein production, and cultivated meat production processes.

Design, Optimise, and Scale Recombinant Protein Production

Central to the shift to alternative proteins is recombinant protein production, a biotechnological process that harnesses the power of microorganisms to produce proteins with diverse applications.

• Protein engineering and design: AI algorithms analyse complex protein structures, predict functionalities, and modify genetic sequences to optimise properties — resulting in proteins with improved nutritional profiles, enhanced functionalities, and reduced allergenicity.
• Discovery of the right strain: AI-driven high-throughput screening expedites the identification of the most promising microbial strains capable of producing target proteins.
• Reducing trial & error: AI-powered predictive analytics enable researchers to anticipate the behaviour of biological systems, saving valuable time and resources.

While AlphaFold itself is not directly involved in producing alternative proteins, its accurate predictions of protein structures can revolutionise the field of protein engineering and design.

Cultivated Meat: Efficiency, Scalability, Cost

• Cell-line identification & development: AI algorithms aid in selecting and engineering the most productive and stable cell lines for meat production and can predict sensory profile and taste based on cell lines and cultivation conditions.
• Bioprocess optimisation: AI-driven automation and data analytics monitor and control nutrient supply, temperature, and pH levels in bioreactors.
• Nutrient and media optimisation: AI optimises cell-culture media by predicting the ideal combination of nutrients and growth factors required for efficient cell growth, reducing reliance on costly and scarce ingredients.

We don't think, as investors and entrepreneurs, we should be obsessed with AI. Instead, we should be obsessed with the end outcome we want to achieve in alternative proteins — mimicking animal-derived meats, seafood, and dairy in a kinder, cleaner, and healthier way. AI is an enabler. We are not going to put money in a company because it is 'AI', but rather because it is leveraging AI to help scale biomanufacturing and overall product formulation, making it more cost-effective and efficient.