Noetik, an AI-driven drug discovery firm focused on immuno-oncology, has successfully closed a $14 million seed financing round. Leading the investment is DCVC, with participation from Zetta Venture Partners, 11.2 Capital, Catalio Capital Management, Epic Ventures, Intermountain Ventures, North South Ventures, Chau Khuong, CJNV BioVentures, Enveda Founder and CEO, Viswa Colluru, Hummingbird Nomads Fund, and Recursion CEO & CFO, Chris Gibson and Michael Secora.
Transforming Cancer Therapeutics with AI
Noetik employs machine learning and proprietary human data to develop precision therapeutics in immuno-oncology. The company’s groundbreaking multimodal tissue profiling platform combines self-supervised learning and spatial biology to address critical issues in cancer immunology. In just under a year of operation, Noetik has accumulated extensive human data, including genomics, transcriptomics, and proteomics, enabling the creation of foundational models for cell and tissue biology.
Fueling Data Generation and Machine Learning Advancements
This new funding will bolster Noetik’s internal data generation efforts and the advancement of transformer-based machine learning methods. The company aims to expedite target and therapeutics discovery using this data. Additionally, the funds will be allocated to expand Noetik’s team, focusing on machine learning, computational biology, and cancer immunology.
A Commitment to Advancing Cancer Therapeutics
Dr. Ron Alfa, CEO & Co-Founder of Noetik, emphasizes the company’s dedication to improving cancer therapeutics through advanced computational tools. Noetik seeks to discover more effective cancer treatments with a higher likelihood of clinical success.
“We are here to make cancer drugs. Our commitment to patients is to discover better cancer therapeutics that have a higher probability of clinical success, using the most advanced computational tools.”Dr. Ron Alfa, CEO & Co-Founder of Noetik
AI’s Role in Revolutionizing Drug Discovery
James Hardiman, General Partner at DCVC, underscores the potential for AI to transform drug discovery by enhancing the prediction of clinical success in oncology therapies. Machine learning enables Noetik to unravel the intricate circuitry of tumor biology, paving the way for precision oncology advancements.
“Technology will have the greatest impact on therapeutics by enabling better prediction of clinical success of new oncology therapies. The biggest bottleneck is clinical failure, with an ever-growing discovery funnel. Using machine learning, Noetik can discover the circuit diagram of tumor biology to unlock the next generation of precision oncology for end-to-end therapeutics discovery,” said James Hardiman, General Partner, DCVC.
Redefining AI’s Role in Drug Development
Dylan Reid, Partner at Zetta Venture Partners, highlights the shift from supervised learning to self-supervision in AI drug discovery. This change allows AI to learn directly from data, revolutionizing the role of AI in drug development. Noetik aims to apply these principles to oncology to develop next-generation precision therapies.
Building an Exceptional Team for Impactful Science
Noetik’s founding team includes experts such as Dr. Lacey Padron, CTO, who previously served as VP Informatics at the Parker Institute for Cancer Immunotherapy. Padron’s extensive experience in multiomic data analysis and biomarker discovery bolsters Noetik’s mission to bridge biology and machine learning.
“We founded Noetik not only to conduct impactful science, but to bring together some of the most talented people in the industry to build the ML-enabled therapeutics company of the future. One of the most challenging aspects of bringing together biology and machine learning is building exceptional interdisciplinary teams,” said Jacob Rinaldi, Ph.D., CSO & Co-Founder, Noetik. “We’re recruiting a world-class, deeply technical team that have built in this space and are passionate to work on solving hard problems to make an impact for patients.”
Noetik secures $14 million in seed funding led by DCVC to advance its AI-driven drug discovery platform in immuno-oncology. The funding will support data generation efforts, machine learning advancements, and team expansion, aiming to accelerate target and therapeutics discovery while improving cancer treatment outcomes.
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