As precision medicine becomes more nuanced and complex, biopharmaceutical companies are increasingly turning to AI to enhance the utility, performance, and scalability of computational pathology analyses for drug development and diagnostics. In parallel, machine learning technologies are rapidly evolving, producing AI models with record accuracy and robustness, opening new avenues for biopharmaceutical research and diagnostics.
„At its core, Aignostics is a world-class machine learning company,“ said Julian Zachmann from ATHOS. „The field is advancing so quickly that, in order to succeed, AI companies need to avoid flashy distractions, stay laser focused on the highest-quality science, and relentlessly innovate. Aignostics is doing just that and bringing a level of transparency and rigor to its biopharmaceutical clients that we think is truly unique.“
„We know that digital pathology, paired with the vast capabilities of AI, has immense potential to impact diagnosis and treatment for patients. Mayo Clinic is actively charting the new frontier of predictive and personalized care,“ shared Jim Rogers, CEO of Mayo Clinic Digital Pathology.
„With this new round of funding, we’re turning our most popular algorithms into products that will help usher in an era of truly generalizable AI for computational pathology.“
The new funding will strengthen Aignostics’ offerings for target ID, translational research, and companion diagnostics (CDx), and support several strategic initiatives, including:
- Launch of scaled „plug-and-play“ products for a range of indications and tasks, including tumor microenvironment and biomarker profiling.
- Continued expansion into the US with additional headcount and support for US partners.
- Collaborative development of foundation models and biopharma product offerings with Mayo Clinic.
„2024 has been a pivotal year for us that has included a major strategic collaboration with Bayer and the launch of our first foundation model, RudolfV,“ said Viktor Matyas, CEO and Co-Founder of Aignostics. „With RudolfV, we’ve gained the ability to quickly develop cost-efficient algorithms that generalize to the real-world. Now with this new round of funding, we’re turning our most popular algorithms into products that will help usher in an era of truly generalizable AI for computational pathology.“
