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Computational precision medicine company Genialis, which leverages artificial intelligence (AI) and machine learning (ML) to model underlying disease biology, announced it raised $13 million in a Series A financing. The company will use the proceeds to fund continued development of its ResponderID computational disease modeling platform to expand its roster of clinically validated biomarker models in cancer to drive precision care.

The financing was co-led by Taiwana Capital and Debiopharm Innovation with participation from previous investors First Star Ventures, Redalpine Venture Partners, and Pikas.

“With ResponderID, we sought to disrupt the historical linear progression of drug discovery and development, rather aiming to close the loop between drug development, patient care and new drug discovery,” said Rafael Rosengarten, PhD, co-founder and CEO of Genialis. “We chose to focus initially on biomarkers that improve the efficiency of drug development, that ensure the right patient gets the right medicine, and make an impact on real people’s lives in a shorter period of time.”

The ResponderID platform along with the company’s Genialis Expressions software use AI/ML to analyze multi-omics data sets to better understand cancer biology, the molecular makeup of patients, and their likelihood of responding to targeted therapies. The Genialis website states “We are Biologists. We are also Technologists. We have combined our expertise in both biology and artificial intelligence to build a biomarker discovery platform that models underlying disease biology. Together, we are enabling the development of the next generation of cancer therapeutics, to serve patients in need.”

As company Co-founder and CTO Miha Stajdohar, PhD, noted in a press release “Genialis is leading the collision of biology and AI. Our approach is biology first, but with a deep commitment to getting the data science right. Thus, we only succeed as a team that understands both worlds. This capital brings together a global syndicate of clinical oncology and deep tech experts and will allow us to grow our in-house capabilities in multiple disciplines.”

Founded in 2015, Genialis’ ResponderID played a key role in generating 10 publications and poster presentations at industry conferences including AACR and ESMO. The machine learning platform was launched in late 2021 as a tool for clinical biomarker discovery that can be implemented for both drug and diagnostic development. At the time of its launch, the company cited a retrospective study published in February 2021 in Cancer Medicine that showed clinical trials in breast cancer, non-small cell lung cancer (NSCLC), melanoma, and colorectal cancer that used biomarkers for patient stratification were between five times and 12 times more likely to progress to the next phase of the study.

“ResponderID, Genialis’ predictive biomarker platform, enables precision medicine by identifying patients that are most likely to respond to treatments. Its use in drug development will optimize study designs and improve chances of clinical trials success, driving much-needed productivity gains for pharma R&D and accelerating the time to market for promising new drugs,” said Hamzeh Abdul-Hadi, investment director at Debiopharm Innovation Fund, who has joined the Genialis board of directors.

ResponderID can read the status of virtually any NGS-based biomarker, including bespoke and proprietary signatures, from a single assay. The assay data provides clinical and translational researchers with a comprehensive molecular portrait of patient disease phenotype to help inform decision making. The company will grow its teams in both the U.S. and at BioLab, a data science research lab at the University of Ljubljana in Slovenia, and is also pushing forward with research and development collaborations at cancer centers, hospital groups and clinical academic labs.

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