Brixo
Skip to main content
Back to Life Sciences Agents
Genesis Therapeutics logo

Genesis Therapeutics

Genesis Therapeutics – headquartered in Burlingame, CA, with a fully integrated laboratory in San Diego – is unifying AI and biotechnology to discover novel and breakthrough treatments for patients with severe and devastating conditions. We are using a proprietary state-of-the-art generative and predictive AI platform called GEMS (Genesis Exploration of Molecular Space), to accelerate and optimize small molecule drug discovery. The GEMS platform integrates deep learning-based predictive models, molecular simulations, and molecular generative AI. GEMS accelerates hit ID through lead optimization and candidate selection by generating promising molecules for synthesis and experimental testing, and iterating this process through multiple cycles of AI-enabled discovery and optimization. We have leveraged GEMS to build an internal pipeline with multiple programs against high-value targets, including data-poor and canonically undruggable targets where GEMS is uniquely advantaged. In addition, Genesis has two AI platform collaborations across a range of therapeutic areas: Eli Lilly (signed in 2022) and Genentech (signed in 2020). Genesis has raised over $280M in funding from top technology and biotech investors, including Andreessen Horowitz, Rock Springs Capital, T. Rowe Price, Fidelity, Radical Ventures, NVentures (NVIDIA's VC arm), BlackRock, and Menlo Ventures. We are rapidly growing our team with a variety of openings on our machine learning, computational chemistry, and software teams (primarily located in the Bay Area) and our chemistry, biology, and clinical teams (primarily located in San Diego). To learn more about Genesis Therapeutics, or current employment opportunities, please visit our website.

Visit Website

Founded

2020

Location

Burlingame, California

Employees

142

Funding

$280M–$327M total; $200M Series B

Genesis Therapeutics: Company Dossier

Overview

Genesis Therapeutics is an AI-enabled biotech focused on small‑molecule drug discovery. The company builds and deploys GEMS, its in‑house molecular AI platform, to design and optimize novel compounds against difficult protein targets, advancing programs internally and through pharma collaborations. Headquarters are in Burlingame, California, with a fully integrated wet lab in San Diego. The team blends machine learning researchers, computational and medicinal chemists, and biologists, and the company partners with leading pharma organizations including Genentech, Eli Lilly, and Incyte.

  • Company site: [Genesis Therapeutics](https://genesistherapeutics.ai)
  • AI platform: [GEMS overview](https://genesistherapeutics.ai/ai-platform/)
  • Pipeline: [Internal and partnered programs](https://genesistherapeutics.ai/pipeline/)
  • News: [Partnerships and funding updates](https://genesistherapeutics.ai/news/)
  • People: [Leadership and team](https://genesistherapeutics.ai/people/)
  • What Genesis Does

  • Uses generative AI and physics‑informed ML to explore chemical space, predict protein–ligand binding, and optimize ADMET, enabling iterative design–make–test cycles.
  • Focuses on data‑poor and traditionally “undruggable” targets with structure‑aware 3D generative workflows.
  • Advances programs through discovery stages (hit ID to lead optimization and candidate selection) rather than offering a self‑serve software product.
  • Learn more: [AI platform details](https://genesistherapeutics.ai/ai-platform/) and [Pipeline overview](https://genesistherapeutics.ai/pipeline/)

    The GEMS Platform

    GEMS is a proprietary molecular AI stack integrating:

  • Diffusion models and LLMs for structure‑based generative design
  • Physics‑informed ML for accurate property and binding predictions
  • Multi‑parameter optimization for potency, selectivity, and ADMET
  • Tight integration with in‑house wet lab execution for rapid feedback loops
  • Key value propositions:

  • Accelerates hit identification and triage
  • Improves lead optimization under realistic medicinal chemistry constraints
  • Targets challenging proteins and data‑sparse scenarios
  • Explore: [GEMS platform](https://genesistherapeutics.ai/ai-platform/)

    Commercial Model

  • Business model: Internal drug discovery plus co‑discovery partnerships with pharma and biopharma
  • Access model: No public SaaS or API; no free trial
  • Collaboration model: Program‑level engagements with partners to advance assets
  • Details: [Company site](https://genesistherapeutics.ai) and [AI platform](https://genesistherapeutics.ai/ai-platform/)

    Partnerships

  • Genentech (initiated 2020)
  • Eli Lilly (announced 2022)
  • Incyte (announced via company news)
  • See updates: [News and partnerships](https://genesistherapeutics.ai/news/)

    Funding and Investors

  • Funding: Oversubscribed Series B of $200M in 2024; total raised >$280M
  • Select investors: Andreessen Horowitz (a16z), T. Rowe Price, Fidelity, BlackRock, Menlo Ventures, Radical Ventures, and NVentures (NVIDIA’s venture arm)
  • Coverage and trackers:

  • Series B coverage: [Inside Precision Medicine](https://www.insideprecisionmedicine.com/topics/ai-pioneer-genesis-tx-snags-200m-in-funding-for-drug-discovery/)
  • Investor/funding tracker: [CB Insights](https://www.cbinsights.com/company/genesis-therapeutics/financials)
  • NVIDIA strategic interest: [GEN News](https://www.genengnews.com/topics/artificial-intelligence/nvidias-venture-arm-raises-stake-in-ai-drug-discoverer-genesis-therapeutics/)
  • Who It’s For

  • Large pharma and mid‑size biopharma R&D teams seeking partnered AI-enabled small‑molecule discovery
  • Internal use by Genesis’ ML, computational chemistry, medicinal chemistry, and biology teams
  • Not intended as a standalone software product for individual researchers
  • Core Use Cases

  • Structure‑based generative design for small molecules targeting hard protein targets
  • AI‑guided hit identification and prioritization
  • Lead optimization with multi‑parameter optimization for potency, selectivity, and ADMET
  • Collaboration frameworks to advance programs to development milestones
  • Learn more: [Platform use cases](https://genesistherapeutics.ai/ai-platform/) and [News](https://genesistherapeutics.ai/news/)

    Integrations and Infrastructure

  • Stack integrates diffusion, language models, and physics‑driven ML with in‑house wet lab validation in San Diego
  • NVentures’ participation signals NVIDIA‑aligned compute strategy; specific infrastructure details are not publicly disclosed
  • References: [AI platform](https://genesistherapeutics.ai/ai-platform/), [People](https://genesistherapeutics.ai/people/), and [NVIDIA investment coverage](https://www.genengnews.com/topics/artificial-intelligence/nvidias-venture-arm-raises-stake-in-ai-drug-discoverer-genesis-therapeutics/)

    Social Proof and Sentiment

    Pros

  • Strong scientific positioning with top‑tier partnerships and investor syndicate
  • Clear narrative around combining generative models with physics‑informed ML for challenging, data‑sparse targets
  • Positive coverage around the 2024 Series B and strategic alignment with NVIDIA
  • Cons

  • No public software, API, or free trial; access is via partnerships only
  • Sparse third‑party software reviews (G2/Capterra entries under similar names are unrelated)
  • Community and coverage:

  • NVIDIA investment commentary: [GEN News](https://www.genengnews.com/topics/artificial-intelligence/nvidias-venture-arm-raises-stake-in-ai-drug-discoverer-genesis-therapeutics/) and [Reddit discussion](https://www.reddit.com/r/NVDA_Stock/comments/1gr6tcu/nvidia_invests_in_genesis_therapeutics_to_advance/)
  • General community thread: [Reddit overview](https://www.reddit.com/r/Tech_By_PV/comments/1mofnn3/genesis_therapeutics_bridging_the_gap_between_ai/)
  • Note: Unrelated listings on software review sites may cause confusion: [G2 example](https://www.g2.com/products/genesis-technologies/reviews) and [Capterra example](https://www.capterra.com/p/10015734/Genesis/)
  • Quick Facts

  • Founded: 2019
  • Headquarters: Burlingame, CA; lab in San Diego
  • Employees: ~143 (LinkedIn-reported)
  • CEO: Evan Feinberg, PhD
  • Model focus: Small‑molecule design, ADMET prediction, 3D structure‑aware generative workflows
  • How to Engage

  • Explore Genesis’ AI platform and pipeline: [Company website](https://genesistherapeutics.ai)
  • Partnership inquiries and updates: [News](https://genesistherapeutics.ai/news/) and [LinkedIn](https://www.linkedin.com/company/genesistherapeutics)
  • Additional Resources

  • Company overview: [Genesis Therapeutics](https://genesistherapeutics.ai)
  • AI platform: [GEMS](https://genesistherapeutics.ai/ai-platform/)
  • Pipeline: [Programs](https://genesistherapeutics.ai/pipeline/)
  • Funding coverage: [Inside Precision Medicine](https://www.insideprecisionmedicine.com/topics/ai-pioneer-genesis-tx-snags-200m-in-funding-for-drug-discovery/)
  • Investor tracker: [CB Insights](https://www.cbinsights.com/company/genesis-therapeutics/financials) and [LinkedIn company profile](https://www.linkedin.com/company/genesistherapeutics)
  • Related Companies

    Atomwise logo

    Atomwise

    Atomwise is a preclinical pharma company revolutionizing how drugs are discovered with AI. Atomwise has strengthened its drug discovery and development expertise by expanding its Board of Directors and creating a Scientific Advisory Board (SAB). These appointments signal a critical milestone for Atomwise as the company focuses on its own internal pipeline. We invented the use of deep learning for structure-based drug discovery, today developing a pipeline of small-molecule drug candidates advancing into preclinical studies. Our AtomNet technology has been used to unlock more undruggable targets than any other AI drug discovery platform. We are tackling over 600 unique disease targets with more than 250 partners around the world, including leading pharmaceutical, agrochemical, and emerging biotechnology companies. Atomwise has raised over $174 million from leading venture capital firms to advance our mission to make better medicines, faster. We’re at a critical time in history where our need for new kinds of medicines is greater than any time in human memory. Fortunately, we can leverage advancing technology and scientific breakthroughs to accelerate discovery. New data, new algorithms, new compute platforms lift all of us, enable our work on the hardest of problems, empower us to invent and create, and ultimately save one billion lives. Join us: www.atomwise.com/careers

    Insilico Medicine logo

    Insilico Medicine

    Insilico Medicine, a clinical stage biotech company powered by generative AI, is connecting biology, chemistry, and clinical trials analysis using next-generation AI systems. The company has developed AI platforms that utilize deep generative models, reinforcement learning, transformers, and other modern machine learning techniques for novel target discovery and the generation of novel molecular structures with desired properties. Insilico Medicine is developing breakthrough solutions to discover and develop innovative drugs for cancer, fibrosis, immunity, central nervous system diseases, infectious diseases, autoimmune diseases, and aging-related diseases.

    Insitro logo

    Insitro

    insitro is a data-driven drug discovery and development company that leverages machine learning and high-throughput biology to transform the way medicines are created to help patients. At insitro, we are rethinking the entire drug discovery process, from the perspective of machine learning, human genetics, and high-throughput, quantitative biology. Over the past five decades, we have seen the development of new medicines becoming increasingly more difficult and expensive, leaving many patients with significant unmet need. We’re embarking on a new approach to drug development – one that leverages machine learning and unique in vitro strategies for modeling disease state and designing new therapeutic interventions. We aim to eliminate key bottlenecks in traditional drug discovery, so we can help more people sooner and at a much lower cost to the patient and the healthcare industry. We believe that by harnessing the power of technology to interrogate and measure human biology, we can have a major impact on many diseases. We invest heavily in cutting edge bioengineering technologies to enable the construction of large-scale, high-quality data sets that are designed specifically to drive machine learning methods. Our first application is to use human genetics, functional genomics, and machine learning to build a new generation of in vitro human cell-derived disease models whose response to perturbation is designed to be predictive of human clinical outcomes. This cannot be done without great people. We are bringing together an outstanding team of people whose expertise spans multiple disciplines - life sciences, machine learning, human genetics, engineering, and drug discovery - and building a unique culture where people from diverse backgrounds work as a single team towards a common goal. We offer opportunities to collaborative people with expertise in life science and computational science. Join us to help bring better health to more people, faster and cheaper.