UCD spinout Nuritas will mark the commercial release of a sports nutrition product formulated in part by its peptide discovery platform next year.

Nuritas, an Ireland-based peptide discovery platform developer spun out from a University College Dublin (UCD) accelerator program, has closed a €16.8m ($20m) series A round led by VC firm Cultivian Sandbox Ventures, the Irish Times reported today.

Nuritas has developed an automated platform for discovering peptides, molecules found within food that can tackle certain health conditions. The technology uses artificial intelligence (AI) and DNA analysis to match potential peptides with specific health conditions.

The funding will allow Nuritas to target business growth in the US, where it hopes its platform could help fight diabetes. Chemicals corporate BASF will release an anti-inflammatory sports nutrition product based on a Nuritas discovery in the US next year.

Nuritas was founded by Nora Khaldi, the company’s chief scientific officer who has a PhD in bioinformatics and molecular evolution. It has now raised $30m in funding altogether.

The business was spun out in 2014 after graduating from UCD’s three-month Venture Launch Accelerator Programme, receiving $165,000 in funding later the same year from NDRC, an Ireland-based digital accelerator firm founded by five universities including UCD.

New Protein Capital, which is now part of VisVires New Protein, backed Nuritas’ $3.2m seed round alongside unspecified private investors in 2015, before state-owned enterprise support agency Enterprise Ireland backed Nuritas’ $2.3m round in 2016.

New Protein Capital also invested in the 2016 round, along with Acdeng Property and angel investor Marc Benioff through his firm Efficient Capacity. 

Angel investors Bono and the Edge, two band members of U2, have been named as early Nutritas investors along with Ali Partovi.

Emmet Browne, chief executive of Nuritas, said: “Bioactive peptides are known to play a role in managing diabetes and many other areas, but the current methods of identifying those that may work is time-consuming, inefficient and expensive.

“Our AI platform has already disrupted this antiquated process by targeting, predicting and unlocking peptides that can positively impact conditions like pre-diabetes, while reducing the cost and time needed to find them.”