Capgemini has introduced a patent-pending generative AI-driven methodology for protein engineering, leveraging a specialized protein large language model (pLLM) to predict the most effective protein variants. This breakthrough significantly reduces the data required to design protein sequences by over 99%, accelerating research and development (R&D) in healthcare, agriculture, and environmental science.
By minimizing experimentation needs, Capgemini’s approach helps lower biosolution development costs, unlocking business cases that were previously unfeasible. This advancement is expected to drive scientific breakthroughs and fuel the global bioeconomy.
Tackling the Data Bottleneck in Engineering Biology
Engineering biology is poised to disrupt industries, with 50% of business leaders anticipating transformation within the next five years. However, data constraints remain a key challenge. Capgemini’s methodology enables scientific innovation even in data-limited environments, positioning the company as a leader in AI-driven bioengineering solutions.
Developed at Cambridge Consultants AI-driven biotechnology lab, this methodology has already been applied to critical use cases, demonstrating step-change innovation.
Applications and Breakthroughs
60% Boost in Plastic Degradation Efficiency
- AI-enhanced cutinase enzyme improved PET plastic breakdown by 60%, offering an innovative, cost-effective solution for plastic waste management.
- This advancement supports sustainability goals by enhancing enzymatic plastic degradation, reducing waste-processing costs.
Drastic Reduction in Experimental Testing
- AI-driven predictions cut down experimentation requirements for Green Fluorescent Protein (GFP) enhancement from thousands of tests to just 43 data points.
- Achieved 7x brightness improvement over natural jellyfish GFP, unlocking potential in drug discovery, diagnostics, and bioengineering.
Industry Insights on Capgemini’s Innovation
Roshan Gya, CEO of Capgemini Invent, emphasized:
“Our generative AI-driven approach is a game-changer, helping clients accelerate their bio-journey while solving global challenges. This methodology is faster, more cost-effective, and opens doors to innovative bio-based solutions.”
Prof. Stephen Wallace, University of Edinburgh, highlighted:
“Capgemini’s AI-driven approach transforms bioengineering timelines by drastically reducing data requirements. This breakthrough paves the way for more sustainable and scalable industrial processes.”
The Future of AI in Biotechnology
Capgemini’s bespoke AI-driven biotechnology lab in the UK integrates expertise across biology, chemistry, generative AI, digital twins, and sustainability. With over 10 years of pioneering AI and bioengineering research, this initiative positions Capgemini at the forefront of engineering biology and industrial biotech innovation.
