Protein immobilization

Technology
In development
Company

At inseit we have developed a physics-based software that allows for the design and in silico screening of protein immobilization conditions. This allows to ensure that the binding, activity and stability of the final biocatalyst is enhanced without extensive trial and error. The software has been used in R&D projects with pharma and CDMOs with excellent results, and internally, we used it to develop our own catalogue of immobilized enzymes, readily available up to Kg scale. We are now also offering early access to a selected group of partners to the software platform.


About inSEIT AG

inSEIT AG is a Swiss biotechnology company specializing in AI-driven enzyme and protein immobilization technologies. By combining proprietary bioinformatics, predictive modeling, and experimental screening, the company addresses the inefficiencies of traditional, trial-and-error immobilization workflows. Their platform enables the rational design and optimization of immobilized biocatalysts, which improves enzyme stability, reusability, and performance in harsh industrial conditions, such as varying pH, solvents, and temperatures. In addition to custom immobilization services, the company offers a catalog of pre-optimized immobilized enzymes, including lipases, ketoreductases, and transaminases, tailored for R&D and pilot-scale industrial applications.

The company's technology is critical for sectors like pharmaceuticals, food and fragrances, and chemical manufacturing, where high-selectivity and continuous flow processes are required. By facilitating enzyme reuse and process intensification, inSEIT enables more sustainable, cost-efficient, and greener chemical synthesis. Their work spans the full development cycle, from in silico design and high-throughput screening to integration into flow reactor systems. InSEIT also provides the inseit Protein Suite, a digital platform for structural characterization, providing researchers with tools for surface analysis, reactivity prediction, and molecular modeling to support protein engineering and process optimization.

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