Deep Genomics vs Insitro

Insitro has a disclosed valuation of $2.2B, while Deep Genomics's valuation is not publicly available, making a direct size comparison difficult. Insitro employs 300 people.

Insitro has raised more in total funding at $743M, compared to Deep Genomics's $180M — a gap of $563M. Combined, the two companies have completed 4 known funding rounds.

Insitro leads with an Awaira Score of 73/100, while Deep Genomics sits at 68/100. That 5-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Deep Genomics was founded by Brendan Frey in 2015. Insitro was founded by Daphne Koller in 2018. Visit each company's profile on Awaira for a full founder biography.

Deep Genomics: Deep Genomics applies deep learning to genetic medicine discovery, using AI models trained on genomic sequence data to predict the functional consequences of genetic variants, identify RNA splicing defects that underlie genetic diseases, and generate novel therapeutic candidates including antisense oligonucleotides and small molecules that correct disease-causing genetic variants. The Toronto company was founded by Brendan Frey, a University of Toronto machine learning professor who collaborated with Geoffrey Hinton on deep learning research.\n\nThe company raised approximately $180 million in venture funding from investors including True Ventures, AlleyCorp, and GV (Google Ventures). Deep Genomics has built an AI drug discovery platform called the AI Workbench that integrates genomic data, disease biology, and AI prediction across the therapeutic discovery pipeline, and has entered a strategic alliance with Agenus to develop cancer treatments using its AI-designed oligonucleotide candidates.\n\nDeep Genomics competes in the AI genetic medicine space against Recursion Pharmaceuticals, Insitro, Exscientia, and gene therapy companies building computational biology capabilities. Its specific focus on RNA biology and oligonucleotide therapeutics, which represent a growing class of approved genetic medicines, differentiates it from platforms focused on small molecule drug discovery or cell therapy. The Toronto University of Toronto AI ecosystem, including connections to the Vector Institute and the Hinton research lineage, provides research credibility and talent access that distinguishes Canadian AI drug discovery from international competitors. Insitro: Insitro is an AI-driven drug discovery company founded in 2018 that applies machine learning to accelerate pharmaceutical development. The company combines computational biology, artificial intelligence, and wet-lab experimentation to identify and validate drug targets more efficiently than traditional methods. Insitro's platform uses proprietary algorithms to analyze complex biological data, predict drug efficacy and safety profiles, and optimize candidate selection across therapeutic areas including metabolic disease, oncology, and immunology. The company has raised $743 million across multiple funding rounds, achieving a valuation of $2.2 billion as of its Series C stage. This positions Insitro among well-capitalized AI healthcare startups addressing the structural inefficiencies in drug discovery. The company partners with pharmaceutical institutions to apply its technology to their pipelines, utilizing both internal discovery programs and collaborations. Insitro's competitive approach differs from pure software platforms by integrating experimental validation, reducing the translation gap between computational predictions and real-world drug performance. The company operates in a crowded but expanding market of AI drug discovery platforms competing against both established pharma AI initiatives and other venture-backed startups. Its growth trajectory reflects investor confidence in AI-enabled drug discovery models, though clinical validation remains ongoing for internally developed candidates. Insitro uniquely combines machine learning with integrated wet-lab capabilities rather than operating as pure software, bridging computational predictions to experimental validation.

Deep Genomics got there first, launching in 2015 — that's 3 years of extra runway. Insitro didn't arrive until 2018. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Deep Genomics has about 100-500 employees; Insitro has about 300. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both Deep Genomics and Insitro compete in AI Healthcare, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.