Insilico Biotechnology is a market-leading company providing predictive solutions for the Bioeconomy. An interdisciplinary team of experts offers mechanistic models, customized software, and a high performance computing platform for the simulation of living cells.
Based on our expertise in reconstructing genome-based network models, we use data from our customer‘s bioprocess to generate a model that represents the customer‘s host organism. Using this model we simulate how cells behave in a bioprocess to identify the best conditions. Our simulations significantly reduce the experimental effort required during upstream bioprocess development:
Automated time-resolved process analysis in manufacturing
Media optimization in process development
Clone analysis and clone selection in cell line development
Metabolic network simulations for metabolic engineering
Customers benefit from our technology either as a service or by licensing our software solutions. To promote knowledge transfer, we provide expert training, consulting, and software customization. For world-leading pharma and biotech companies Insilico‘s technology lowers time, risk and costs of process development.
(Stuttgart) - Insilico Biotechnology AG has announced that Prof. Dr.-Ing. René Schenkendorf has complemented its Scientific Advisory Board. With this further expansion of the…
Insilico Biotechnology AG participates in Inno4vac, a European new public-private partnership to innovate vaccine development
(Stuttgart) - The Innovative Medicines Initiative 2 (IMI2) Joint Undertaking mobilised more than € 33 million to support Inno4vac, an innovative public-private partnership to…
(Stuttgart) - Insilico Biotechnology AG announces that Professor John Bagterp Jørgensen is joining its Scientific Advisory Board to enrich the scientific capabilities of the…
Insilico Announces the Release of “Insilico Advisor” for Model Predictive Monitoring of Cell Culture Processes
(Stuttgart) - Insilico Biotechnology AG announces the release of its new product, the Insilico Advisor to improve efficiency of biologics manufacturing.