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AI and Data for Cancer Therapeutics

Winter 2026Founded 20254 peopleSan Francisco, CA, USA
AI insightcan contain mistakes
Cancer Drug Discovery DataTransactionalPharma companies and AI labsLow competition
Moat
Patient-derived, single-cell datasets with drug-effect screening are unique and difficult to replicate.
Key risk
Competitive datasets may emerge from larger pharma; regulatory/IP challenges in data licensing.
Why now
AI-driven drug discovery is accelerating and labs are willing to license specialized datasets.
Competitors
Tempus AI, Recursion Pharmaceuticals data licensing

About

Creating the largest patient-derived cancer single-cell dataset for licensing to pharmaceutical and AI companies. These datasets are unique as they screen the effects of various drugs and genetic medicines under the control of our DNA switches.

Founders · 2

Yash Rathod
Yash RathodFounder
UIUC

CEO @ Origin | Computer Science @ UIUC, Computer Vision and Reinforcement Learning Research, First Prize 2022 OpenCV AI Research Competition.

Malhar Bhide
Malhar BhideFounder
UIUC

CTO @ Origin | Prev: Computer Science @ UIUC, ML Research @ Wadhwani AI, Automorphic (YC S23). Published disease modeling research done in high school in Nature Scientific Reports.

Launch

Launched on Y Combinator · Feb 2026
View launch post ↗

AI designed regulatory DNA sequences to program gene expression patterns

Origin announces Axis, an AI model that designs regulatory DNA sequences to activate therapeutic genes in target disease cell-states, aiming to make cell and gene therapies safer and more effective. They are building a large proprietary dataset of synthetic regulatory elements and claim Axis outperforms Google DeepMind’s AlphaGenome in predictive benchmarks.

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