Research & Projects
We work at the interface of computation and the life sciences, creating methods, algorithms, and software to understand how biomolecules interact and function.
Every research line walks hand in hand with engineering: many of our projects produce open tools and databases used by the scientific community worldwide.
Strategic focus
Seven applied research fronts connecting artificial intelligence, biotechnology, and data science to challenges in health, industry, and sustainability.
Cutting the time and cost of discovering new treatments for chronic inflammatory diseases and viral infections (such as COVID-19, HIV, and Yellow Fever) through artificial intelligence. The line brings intelligence to compound screening, enabling the rapid repurposing of already approved drugs for new health emergencies.
Meeting the global demand for clean energy and a green economy. The ultimate goal is to make second-generation biofuels viable and cheaper by developing enzymes able to degrade plant biomass with maximum efficiency at industrial scale.
Meeting the pharmaceutical industry's strong demand for immunobiologicals and peptide-based therapies, a highly profitable market thanks to their low toxicity and extreme target precision. The final delivery focuses on the design of competitive inhibitors and highly effective vaccines.
Creating tailor-made, highly stable biomolecules for industry. The line delivers predictive answers about which genetic modifications will let an enzyme withstand the harsh conditions — temperature swings, high inhibitor concentrations — required on biotechnology and food production lines.
Extracting value from large volumes of molecular data (Big Data) to uncover new active compounds and unexplored targets. Rather than the mathematics behind it, the focus here is the lab's ability to find needles in the haystack, accelerating innovation and decision-making in research and development (R&D).
Minimizing bench failures and sharply reducing costs and the use of laboratory animals. The delivery is a realistic simulation of how a new drug or therapy will behave in the human body (interaction and stability over time), making sure only the most promising compounds advance to expensive clinical trials.
Providing agile databases, specialized platforms (SaaS - Software as a Service), and digital literacy. The line answers the market's need to modernize access to biological information and to train life-science professionals for the new era of data science and technological innovation.