A fresh start for Molecular Health: technology core becomes start-up Lucera
A fresh start for Molecular Health: technology core becomes start-up Lucera
Publish Date: 2026-06-02 03:52:00
Source Domain: european-biotechnology.com
The aim of the restart in Heidelberg is to develop the technology built up over many years for data-driven decision support in drug development in a more focused, leaner way, and closer to the market.
For the German biotech scene, the transaction is both a look back and a look ahead. Molecular Health was once one of the early hopefuls in precision medicine. The company was already focusing on linking biomedical data at a time when terms such as knowledge graph or artificial intelligence were still far from standard industry vocabulary. Commercial execution, however, proved challenging. Like many pioneers in data-driven medicine, the company had to adapt its strategy several times to changing market conditions.
Data-driven pharma decisions
Lucera will now carry forward the part of the company that has established itself as a viable business model in recent years. According to the company, it has already served more than 20 pharma, biotech and investment clients worldwide. Around 25 employees are moving from Molecular Health to the new company at launch.
At the top are two executives who have been familiar with the technology for years: former Molecular Health founder and long-time industry investor Friedrich von Bohlen as CEO, and Stephan Brock as CTO. Lucera is being financed by a consortium of institutional and private investors.
At the centre remains the Dataome knowledge platform, which the company says has been developed over more than 15 years. The database integrates information from hundreds of public and proprietary sources and connects it through a semantic knowledge graph. Unlike many generative AI systems, the platform is intended not only to deliver predictions, but also to explain them biologically and trace them back to the underlying evidence.
Curated data are the real asset
The approach addresses a problem that has become larger, rather than smaller, with the rise of AI in drug development: while ever more data and models are available, the…
