Creative Enzymes, a global enzyme technology service provider, has launched an AI-integrated platform that takes a systematic approach to accelerating enzyme catalyst development. By merging computational enzyme engineering with hands-on process development know-how, the platform delivers AI-Driven Biocatalysis Solutions that are predictable in silico and practical at industrial scale.
While biocatalysis is an established manufacturing process, a significant gap remains between identifying application opportunities and having suitable enzymes available. Traditional development approaches cannot meet the speed requirements of iterative product development. AI brings critical value by predicting enzyme candidates best suited for a given reaction, designing enzymes constrained by process parameters, and leveraging molecular features to anticipate process performance in advance.
The platform's capabilities are delivered through three specialized service modules tailored to different stages of biocatalyst development. The first module provides an end-to-end AI-driven solution for biocatalyst discovery and engineering, spanning from target reaction analysis to scale-up characterization. It encompasses computational screening, process optimization across key parameters, and scale-up evaluation. For moderately complex targets, this reduces the design-build-test-learn cycle from 12–24 months to just 8–12 months.
The second module focuses on AI-Driven Industrial Biocatalysis, addressing the journey from reaction engineering to full-scale implementation. It includes substrate concentration optimization, cofactor regeneration, immobilization, process analytical technology integration, and delivery of complete technology transfer packages. The objective is a fundamentally improved industrial workflow built around the catalytic process.
The third module, AI-Driven Green Biocatalysis, provides sustainability-focused solutions that align with corporate environmental goals. Enzymatic reactions minimize organic solvent use, reduce heating and cooling requirements, and minimize byproduct formation. AI-guided development amplifies these advantages by identifying inherently more efficient enzymes, reducing the environmental footprint of both development and production.
The platform's capabilities have been demonstrated through a recent AI-driven case study in transaminase engineering. Researchers developed a 6D protein engineering framework that combines interaction energy, solvent effects, and 1.39 million structural fragments to predict beneficial mutations. Five transaminase variants selected by AI exhibited high solubility and catalytic stability at 7-liter fermentation scale, converting prochiral ketones to sitagliptin with enantiomeric purity exceeding 99% and conversion rates up to 89%.
Pharma is where AI biocatalysis is making the biggest impact currently, with asymmetric synthesis of chiral intermediates and replacement of hazardous reagents already underway. Agrochemicals and food industries are also adopting the technology to fine-tune toxicology profiles and deliver cleaner labels. Fine chemicals and personal care sectors are beginning to explore high-value conversions and milder, more sustainable processes.
