Nostrum Biodiscovery
AI-powered molecular design company spun off from Barcelona's BSC and IRB, providing computational drug discovery and enzyme engineering services.
Last updated September 29, 2026
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Overview
Nostrum Biodiscovery is a Barcelona-based biotechnology company specializing in AI-powered molecular design. Founded in December 2015 as a spin-off from the Barcelona Supercomputing Center (BSC-CNS) and the Institute for Research in Biomedicine (IRB), the company combines proprietary molecular modeling software with machine learning to accelerate drug discovery and enzyme engineering. Its two main areas of focus are therapeutics — including small molecule design, targeted protein degradation, antibodies, immunologics, and nucleic acids — and bio-based chemistry, particularly enzyme engineering. The company offers customer-tailored solutions built on state-of-the-art proprietary and third-party software, using best-in-class molecular modeling for data augmentation and fine-tuning of dedicated machine-learning algorithms. Nostrum Biodiscovery serves clients in more than 12 countries and is expanding in Asia and Latin America while strengthening its presence in the US and Europe. It has a Boston office at CIC Cambridge. The company's proprietary PELE technology, a Monte-Carlo based algorithm for molecular modeling, is central to its offerings, alongside AI algorithms and the XNA-Hub platform. Nostrum Biodiscovery has achieved several milestones, including its first AI pharma project in January 2018, a Senén Vilaró award in December 2019, and a 40% CAGR over three years as of December 2024. By January 2025, 90% of its sales came from international markets. The company remains a private limited company (SL) and is recognized as an innovative SME.
History
Nostrum Biodiscovery was founded in December 2015 as a spin-off from the Barcelona Supercomputing Center (BSC-CNS) and the Institute for Research in Biomedicine (IRB), two leading Spanish research centers. The company was established to commercialize advanced molecular modeling technologies, particularly the PELE algorithm developed at BSC. In June 2016, it received NEOTEC funding from CDTi, and in July 2016, seed capital from Fundación Marcelino Botín. September 2016 saw the first internal drug discovery project, followed by the first drug discovery contract in October 2016. In January 2018, the company embarked on its first AI pharma project. By January 2019, 45% of its revenue was generated from international sales. In May 2019, the Enzyme Engineering Division was established. In June 2019, the first PCT patent was granted for a new chemical entity in the cardiovascular therapeutic area. In December 2019, Nostrum Biodiscovery received the Senén Vilaró award for the Best Innovative Startup. The company reached its breakeven point in December 2020. In December 2018, it was granted the BioExcel project under H2020-EC. By December 2024, the company had achieved a 40% compound annual growth rate over three years. In January 2025, 90% of its sales came from international markets. The company continues to expand, with a Boston office opened to strengthen its US presence, and ongoing expansion in Asia and Latin America.
Foundation of Nostrum Biodiscovery as a spin-off from BSC-CNS and IRB.
Received NEOTEC funding from CDTi.
Seed capital from Fundación Marcelino Botín.
First internal drug discovery project.
First drug discovery contract.
First AI pharma project.
BioExcel project granted under H2020-EC.
45% of revenue generated from international sales.
Enzyme Engineering Division established.
First PCT granted for an NCE in cardiovascular therapeutic area.
Products and positioning
Combines proprietary molecular modeling software with innovative AI tools to deliver highly specialized and efficient solutions for drug discovery and enzyme engineering.
PELE
Proprietary Monte-Carlo based algorithm for molecular modeling, with latest release PELE 1.9 featuring PELE Loop Closure.
XNA-Hub
In silico platform for nucleic acid design.
AI algorithms for molecular modeling
Machine learning algorithms for data augmentation and fine-tuning in molecular design.
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