Central to both iDESIGN (intelligent design of compound libraries for drug discovery) and RADICALZ (enzyme discovery using diverse chemical/biological libraries).
ANALYTICON DISCOVERY GMBH
German SME providing compound libraries and enzyme discovery services using microfluidics, metagenomics, and machine learning for pharma and green biotech.
Their core work
Analyticon Discovery is a Potsdam-based SME specializing in compound library design and biochemical discovery services. They develop and supply diverse chemical compound collections used as starting points in drug discovery and enzyme engineering. Their work spans from health-oriented compound screening (C. elegans models, intelligent library design) to industrial enzyme discovery using microfluidics and machine learning. In practice, they sit at the intersection of chemistry, biology, and data science — providing the molecular building blocks and screening tools that larger research teams need.
What they specialise in
RADICALZ project focuses on rapid discovery of enzymes for consumer products using protein engineering and metagenomics.
RADICALZ explicitly lists microfluidics as a core technology for high-throughput enzyme screening.
RADICALZ applies machine learning to accelerate enzyme and compound identification from large biological datasets.
Ageing with elegans project used C. elegans models to validate health and disease factors, likely involving compound screening.
How they've shifted over time
Analyticon Discovery started in H2020 with health-focused work — validating biological models for ageing and disease (2015), then moved into smarter drug discovery library design (2018). By 2021, they shifted decisively toward industrial biotechnology: enzyme discovery for consumer products using microfluidics, metagenomics, and machine learning. The trajectory shows a clear move from pharma-adjacent compound supply toward greener, bio-based industrial applications powered by computational methods.
Analyticon is pivoting from traditional pharmaceutical compound libraries toward machine-learning-driven enzyme discovery for sustainable consumer products — a direction aligned with the EU's green industrial push.
How they like to work
Analyticon participates exclusively as a partner, never as coordinator, which is typical for a specialist SME contributing specific technical capabilities to larger consortia. With 34 unique partners across 16 countries in just 3 projects, they consistently join large, multinational consortia rather than small bilateral collaborations. This suggests they are comfortable operating within complex project structures and are sought out for their specialized compound/screening expertise rather than driving research agendas.
Despite only 3 projects, Analyticon has built a broad network of 34 partners across 16 countries, indicating participation in large-scale EU consortia with wide geographic spread. No single country dominance is apparent — their partnerships are truly pan-European.
What sets them apart
Analyticon occupies a niche that few SMEs cover: they bridge chemistry and biology by providing intelligently designed compound and enzyme libraries, now enhanced with machine learning and microfluidic screening. For consortium builders, they offer a rare combination — a commercial entity with hands-on molecular discovery capabilities that can supply both the compounds and the high-throughput screening infrastructure. Their shift toward green biotech makes them particularly relevant for sustainability-focused projects needing enzyme or bioprocess expertise.
Highlights from their portfolio
- RADICALZTheir most technically ambitious project, combining microfluidics, metagenomics, ML, and protein engineering for green enzyme discovery — signals their strategic direction.
- iDESIGNDirectly aligned with their core business of compound library design, using intelligent/data-driven methods to improve drug discovery starting points.
- Ageing with elegansTheir largest single grant (EUR 533,531) and earliest H2020 project, establishing their presence in biological model validation.