€3m · Pre-Seed · Healthtech · Niel, Belgium
Sightera Biosciences has closed a €3m Pre-Seed round led by Entourage, Anacura and Qbic. The financing announcement says the University of Antwerp and Antwerp University Hospital spinout will use the capital to expand its team, grow its AI-native drug-discovery platform and preclinical portfolio, advance its lead molecular-glue oncology programme towards candidate selection, and strengthen pharmaceutical and biotech partnerships.
Teaching models with patient biology
Sightera starts with patient-derived tissue rather than relying only on public chemical and biological datasets. Its platform grows treatment-resistant tissue into organoid models, uses robotic live-cell imaging to measure drug responses, and feeds those proprietary results into models that design new small molecules. The company says each programme can synthesise and test more than 400 molecules, with every experiment returning data to the next design cycle.
The commercial thesis is that clinically relevant biology can narrow the gap between a computationally promising molecule and one that works in complex disease models. Sightera has access to a local biobank and clinically annotated patient material through the Antwerp ecosystem. The University of Antwerp describes the shared infrastructure as combining patient-derived tumour organoids, automated high-throughput screening, live-cell imaging and AI-guided drug development.
Two routes to validation
Sightera plans to build its own pipeline while offering platform-discovery partnerships and out-licensing options. Its current work spans oncology and fibrosis, with the lead SIGHT001 molecular-glue programme intended to move towards preclinical candidate selection. Molecular glues are designed to recruit the cell’s own machinery to alter or remove disease-driving proteins, potentially opening targets without conventional binding pockets.
That dual model creates two tests for the new capital. Internal programmes must turn the platform’s designs into reproducible preclinical evidence, while partner projects must show that the same patient-derived loop transfers across targets and disease areas. The round funds the team, experiments and medicinal-chemistry iteration needed to produce that evidence; it does not remove the usual safety, manufacturability and clinical-development risks of a new drug candidate.
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TechBio x AI Drug Discovery: From Concept to Reality examines why proprietary biological data, wet-lab execution and pipeline strategy are becoming the differentiators for European techbio companies.


