--- title: Genesis Therapeutics slug: genesis-therapeutics-a9d37 url: /detay/genesis-therapeutics-a9d37 type: article language: English entity: primary: Genesis Therapeutics type: article categories: - name: Science And Technology slug: bilim url: /kategori/bilim - name: Engineering slug: muhendislik url: /kategori/muhendislik - name: Technology And Innovation slug: teknoloji url: /kategori/teknoloji tags: - Genesis Therapeutics author: Ömer Said Aydın created_at: 2025-10-25T21:29:27.010987+03:00 updated_at: 2025-11-06T16:56:40.944650+03:00 image: https://cdn.t3pedia.org/media/uploads/2025/10/25/nhUdXHsjThI2urohl3sOtvfibNT3wlcN.webp --- # Genesis Therapeutics ## KURE Information Cards ![5lF1HhlFygm6RQ4CJbIXLKf9VDzael13.webp](https://cdn.t3pedia.org/media/uploads/2025/10/25/7Jupfq7IVCk23Ob2oz6IFnSzf4ng9ABF.webp) *Genesis Therapeutics* | Field | Value | |-------|-------| | Website(s) | https://www.genesistherapeutics.ai | | Founded(Text) | 2019 | | Headquarters | Burlingame, California, USA | ## Article Content [Genesis Therapeutics](/en/detay/genesis-therapeutics-6ea46/llms.txt) is a biotechnology and artificial intelligence (AI) company headquartered in Burlingame, California, with a fully integrated wet laboratory in San Diego. The company combines advanced generative and predictive AI models with biotechnology to discover novel small-molecule therapeutics for severe and treatment-resistant diseases. Its proprietary [GEMS](/en/detay/genesis-therapeutics-35033/llms.txt) (Genesis Exploration of Molecular Space) platform accelerates and optimizes drug discovery through [deep learning](/en/detay/digital-health-and-artificial-intelligence-applica/llms.txt), molecular simulation, and physics-based modeling. ### **GEMS Platform** GEMS is a multi-layered AI system that unifies deep learning–based predictive models, molecular simulations, and [generative AI](/en/detay/generative-adversarial-network-gan-a862c/llms.txt) for molecular design. It performs iterative generation and evaluation of molecular structures from design to candidate selection. Key components include: - **Molecular language models** for de novo molecule generation. - **Diffusion models** for protein–ligand structure prediction. - **Physics-informed machine learning** for potency and selectivity estimation. - This approach enables drug design against **“undruggable” biological targets**, expanding therapeutic reach in previously inaccessible domains. ### **Research and Technology Domains** Genesis operates at the intersection of **machine learning, physics, and chemistry**, developing next-generation **foundation models** capable of understanding the “language” of molecules. Core research areas include: - **Generative diffusion models** for high-precision 3D molecular structure creation. - **Science-oriented large language models (LLMs)** for molecule and reaction understanding. - **Reinforcement learning** for guided, multi-objective molecule optimization. - **Multimodal learning** integrating diverse data types (3D structures, bioassay data) for pharmacokinetic and toxicity prediction. - **Geometric and 3D deep learning** leveraging physical symmetries through equivariant neural networks. Genesis applies GEMS to internal programs in **oncology** and **immunology**, targeting diseases with limited data or historically intractable biology. ### **Partnerships and Collaborations** The company has formed **multi-target discovery partnerships** with: - **Genentech** (2020) - **Eli Lilly** (2022) - **Gilead Sciences** (2024) - **Incyte** (2025) These collaborations include upfront payments totaling over USD 65 million and joint research pipelines focusing on small-molecule innovation. ### **Funding and Investors** Genesis has raised over USD 300 million from leading technology and biotech investors, including Andreessen Horowitz, T. Rowe Price, Rock Springs Capital, Fidelity, BlackRock, Radical Ventures, Menlo Ventures, and NVentures (NVIDIA’s venture arm). The 2024 partnership with NVIDIA enhanced the development of computational methods and equivariant neural architectures. ### **Intellectual Property and Scientific Contributions** Genesis holds several patents in AI-driven drug discovery, including: - *Computational platform for molecule generation* (US12159693B2) - *Chemical computation graphs* (US12230367B2) - *Generative ML based on text-based molecular queries* (US12288600B2) Company researchers have presented at ICML, the Stanford AI+Biomedicine Seminar, and MIT Tech Talk, contributing to the advancement of generative modeling and AI-driven small-molecule discovery. ### **Organization and Leadership** Genesis Therapeutics operates across **Burlingame (headquarters)**, **San Diego (wet lab)**, and **New York City (technical center)**, with part of its workforce remote. The leadership team includes: - **Evan Feinberg, PhD** – Chief Executive Officer & Co-Founder - **Will McCarthy** – Chief Operating Officer - **Shifeng Pan, PhD** – Chief Scientific Officer Its scientific and technical teams feature experts formerly from OpenAI, [DeepMind](/en/detay/deep-genomics-4153a/llms.txt), Meta, and Google, reflecting the company’s interdisciplinary culture at the frontier of AI and biomedicine. ## Academic Sources and References 1. Genesis Therapeutics. “About.” LinkedIn. Accessed October 23, 2025. https://www.linkedin.com/company/genesistherapeutics/.Genesis Therapeutics. “AI Platform.” Official Website. Accessed October 23, 2025. https://genesistherapeutics.ai/ai-platform/.Genesis Therapeutics. “Home.” Official Website. Accessed October 23, 2025. https://genesistherapeutics.ai/.Genesis Therapeutics. “People.” Official Website. Accessed October 23, 2025. https://genesistherapeutics.ai/people/.Genesis Therapeutics. “Pipeline.” Official Website. Accessed October 23, 2025. https://genesistherapeutics.ai/pipeline/.Genesis Therapeutics. “Research.” Official Websi