The digitization of biological research is generating larger amounts of data than ever. However, it is more and more difficult to handle these data to extract new insights using the human brain alone. Despite the increasing amount of data, only 10% of drugs that enter clinical trials are approved due to the high complexity of biological systems. Furthermore, after approval, drug manufacturing requires strong production and regulatory constraints and production costs are estimated to reach up to 30% of drug market.
At Gencovery, we are convinced of the need of collaborative virtual platforms to allow biology experts to sustainably leverage their data and knowledge using AI and digital organisms in their R&D and drug bioproduction pipelines.
Digital organisms are digital twins of living organisms. They are mathematical models designed to mimic the functional capabilities of living organisms (bacteria, viruses, fungi, plants, animals, …) and experiments. They allow to benefit the power of modern computational infrastructures and methods to build tomorrow’s life science. We successfully assessed the technology in research proof-of-concepts and projects. We are therefore bringing it to industry using our collaborative virtual platform for computer-aided biology.
Our mission is to provide cutting-edge software based on digital organisms for biotechnology and pharmaceutical industry in order to improve people’s lives.
We are focused today on the development of AI software for accelerating cell engineering and optimizing bioprocesses using digital twins
By 2025, our computer-aided biology platform is broadly adopted in drug bioproduction and is also used for personalized medicine.
We are developing AI-based software for computer-aided biology to allow biotechnology and pharmaceutical companies to improve drug development, reduce biomanufacturing costs and innovate faster using digital organisms.
Our job is to develop AI-based software for the modeling of complex living systems.
We have strong expertise in Software engineering, Applied mathematics, Systems biology, Bioinformatics, Data science and Omics science. To succeed in the digitalization of R&D in biotechnology and pharmaceutical industry, we are convinced of the need of innovative tools for continuous and sustainable integration of biological knowledge and data. We are therefore designing our platform for that!
