Sightera Biosciences closes €3M pre-seed to expand its patient-derived AI drug discovery platform

The funding will expand Sightera's AI-driven drug discovery platform, advance its lead oncology programme towards candidate selection, and strengthen partnerships with pharmaceutical companies. Biotech Sightera Biosciences closes €3M pre-seed to expand its patient-derived AI drug discovery platform The funding will expand Sightera's AI-driven drug discovery platform, advance its lead oncology programme towards candidate selection, and strengthen partnerships with pharmaceutical companies. Tamara Djurickovic 1 hour ago Share Share Send email Copy link Sightera Biosciences , a Belgian techbio company using generative AI to develop novel small-molecule therapies, has raised €3 million in a pre-seed funding round led by Entourage, Anacura and QBIC.

A spin-off from the University of Antwerp and Antwerp University Hospital (UZA), Sightera is developing an AI-native drug discovery platform focused on oncology and fibrosis. Unlike many AI drug discovery companies that rely on public or generic datasets, Sightera trains its models using proprietary data generated from patient-derived biological samples collected from individuals with advanced, therapy-resistant disease. These samples are used to create preclinical models, including organoids, that closely replicate human disease biology and generate large-scale drug-response datasets.

The proprietary datasets underpin Sightera's AI platform, enabling it to design small molecules based on biological responses observed in patient-derived systems rather than chemical properties alone. By placing human disease biology at the centre of the discovery process, the company aims to improve the likelihood that AI-designed drug candidates will translate successfully into clinical development. The funding will support the expansion of Sightera's AI-powered drug discovery platform, accelerate the development of its preclinical pipeline and advance its lead molecular glue oncology programme towards preclinical candidate selection.