Creative Enzymes, a global enzyme technology service provider, has launched an AI-integrated biocatalysis platform designed to address the growing bottleneck in enzyme catalyst development for biomanufacturing. The platform combines computational enzyme engineering with hands-on process development, delivering AI-driven biocatalysis solutions that are both predictable in silico and practical at industrial scale.
The platform targets a significant gap in the industry: the lag between identifying application opportunities for biocatalysis and having suitable enzymes available. Traditional development methods cannot keep pace with the speed required for iterative product development. According to Creative Enzymes, AI brings critical value on three fronts: predicting enzyme candidates for specific reactions, designing enzymes constrained by process parameters rather than biological factors, and leveraging molecular features to anticipate process performance in advance.
Beyond speed, the AI approach reduces R&D costs by minimizing the need to test numerous biocatalyst variants. It also lowers the risk of process failure by identifying suitable catalysts earlier in development and opens routes to molecules previously inaccessible to enzymatic conversion, creating new product opportunities.
The platform is organized into three service modules. The first, AI-Driven Biocatalysis Solutions, offers an end-to-end workflow from target reaction analysis to scale-up characterization. It includes computational screening against sequence databases and proprietary libraries, process optimization across parameters like temperature, pH, and substrate loading, and scale-up evaluation covering expression yield and operational half-life. For moderately complex targets, this reduces the design-build-test-learn cycle from the conventional 12–24 months to just 8–12 months.
The second module, AI-Driven Industrial Biocatalysis, focuses on bridging lab-scale performance and commercial production. It addresses substrate concentration optimization, cofactor regeneration, product inhibition management, immobilization, formulation development, integration of process analytical technology for real-time quality assurance, and delivery of complete technology transfer packages including SOPs and regulatory documentation.
The third module, AI-Driven Green Biocatalysis, provides sustainability-focused solutions. Enzymatic reactions typically occur in aqueous media at room temperature, minimizing organic solvent use and emissions. Mild conditions reduce heating and cooling requirements, and enzymatic selectivity minimizes byproduct formation, simplifying purification and reducing waste. AI-guided development amplifies these advantages by identifying inherently more efficient enzymes.
In a recent case study, Creative Enzymes applied the platform to transaminase engineering. Researchers developed a 6D protein engineering framework combining interaction energy, solvent effects, and 1.39 million structural fragments to predict beneficial mutations. Five AI-selected transaminase variants, each with nine mutations, exhibited high solubility and catalytic stability at 7-liter fermentation scale. The engineered enzymes convert prochiral ketones to sitagliptin, achieving enantiomeric purity exceeding 99% and conversion rates up to 89% during scale-up.
Pharmaceuticals are currently the biggest adopters of AI biocatalysis, particularly for asymmetric synthesis of chiral intermediates and replacing hazardous reagents. Agrochemicals and food industries are also adopting the technology—the former to fine-tune toxicology profiles, the latter for cleaner labels through enzymatic modification. Fine chemicals and personal care sectors are beginning to explore high-value conversions and more sustainable processes.
