AIgnostics, a spin-off of Charité - Universitätsmedizin Berlin developing novel digital pathology solutions with "Explainable AI" for pharmaceutical research and diagnostics, announces an oversubscribed Series A funding round of €14 million. Well-known names from the investor scene are on board: Wellington Partners led the round as a new investor. Other existing investors include the Boehringer Ingelheim Venture Fund (BIVF), the VC Fonds Technologie managed by IBB Ventures, the High-Tech Gründerfonds (HTGF) and - a new addition - the CARMA Fund initiated by Ascenion.
While pathologists excel at qualitatively interpreting individual tissue samples, in-depth analysis of large data sets requires the use of Artificial Intelligence (AI). Recognizing this, AIgnostics is focused on developing AI models for detailed analysis of tissue samples and associated metadata for its blue-chip customers in the pharmaceutical and biotechnology industries. AIgnostics' AI models go far beyond current off-the-shelf solutions and established approaches. Its models cover key tissue staining technologies, including hematoxylin-eosin (H&E), immunohistochemistry (IHC), and multiplex immunofluorescence (mIF). Their use is expected to accelerate preclinical and translational research by improving understanding of disease biology and mechanisms of action. They can also identify novel biomarkers and clues to the efficacy of innovative drug candidates that are difficult to detect using conventional microscopy methods.
Dr. Rainer Strohmenger, Managing Partner at Wellington Partners, commented: "We are deeply impressed by AIgnostics' team and technology. Wellington is pleased to join the group of existing investors as a new lead investor and to support a leading German AI provider in its expansion phase. Even more so than our previous portfolio company Definiens, we see potential in AIgnostics to make the use of pathology by the pharmaceutical industry and CROs in the drug development process much more efficient to significantly improve the treatment of patients with difficult-to-treat diseases, including cancer."
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