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Genialis Raises $13M to Build Clinical Biomarkers that Predict Patient Response 

by Syed Hamza Sohail 03/29/2023 Leave a Comment

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What You Should Know:

  • Genialis, a computational precision medicine company unraveling complex biology to find new ways to address disease, today announced it raised more than $13 million in Series A financing to transform the way diseases are diagnosed and treatment decisions are made.
  • Taiwania Capital and Debiopharm Innovation Fund co-led the round, with participation from previous investors First Star Ventures, Redalpine Venture Partners, and Pikas. Other new investors include P5 Health Ventures and several Angels. Ita Lu of Taiwania and Hamzeh Abdul-Hadi of Debiopharm will join Genialis’ Board of Directors. 

AI/ML-enabled Platform With a Biology-First Approach

Genialis is developing next-generation patient classifiers using machine learning and high-throughput omics data to capture underlying disease biology and predict how patients will likely respond to targeted therapies. The company will use the funds from the Series A to expand its proprietary ResponderID(™) platform and build out its comprehensive collection of clinically validated biomarker models to provide pinpoint diagnoses for virtually every cancer patient. To date, Genialis has used ResponderID in collaboration with biopharma to analyze clinical trial data and inform future trial designs for numerous investigational drugs. Genialis also supports the commercialization of next-gen biomarker assays with several leading diagnostic firms.

“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,” says Rafael Rosengarten, Ph.D., 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.”

ResponderID is a machine learning platform for clinical and translational research, built from years of experience working with partners across the industry and advanced internal R&D. ResponderID yields new biomarkers for drug development and discovery programs, as well as diagnostic tests. ResponderID can read the status of virtually any NGS-based biomarker, including bespoke and proprietary signatures, from a single assay. The resulting output provides clinical and translational researchers with a comprehensive molecular portrait of patient disease phenotype enabling the most informed decision-making possible.

“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. 

Last year, ten publications and poster presentations at major scientific conferences featured results generated with ResponderID, including AACR, ESMO, and SITC. Genialis also co-authored a paper in the Journal of Clinical Oncologydescribing OncXerna’s navicixizumab ph1b trial, including retrospective analysis with the Xerna TME Panel. 

“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,” said Miha Stajdohar, Ph.D., co-founder and CTO of Genialis. “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.”Genialis is growing its teams in both the U.S. and Slovenia across business, operations, life science, and data science functions and expanding its advisory boards. The company is also investing in R&D collaborations with several leading cancer centers, hospital groups, and clinical academic labs. 

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Tagged With: AI, Biomarkers, cancer, Clinical Trial, Clinical Trials, Drug Discovery, Health Ventures, Machine Learning, Oncology, Partners, Patient Care, Pharma, Precision Medicine, Translational Research

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