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Genesis Therapeutics

What Genesis Therapeutics does

Genesis Molecular AI (formerly Genesis Therapeutics) develops molecular AI for small-molecule drug discovery. The company’s core platform, GEMS (Genesis Exploration of Molecular Space), is positioned as an “agentic end-to-end” workflow that integrates foundation models, generative and predictive methods, and physics-based computation so chemists can generate candidate molecules, predict protein–ligand structures and molecular properties, and decide what to synthesize next. Genesis says its foundation-model approach emphasizes molecule–protein structure prediction (Pearl) and downstream potency/selectivity and ADME prediction, and it describes using a drug design “flywheel” in which partnered and internal wet-lab feedback helps improve models and tooling over time.

News

Company record

Jun 10, 2026 · Reporting · Genesis Molecular AIGenesis Model Distillation

Genesis published a technical blog post describing DeCAF (Denoiser Cofolding All-atom Flowmap) and DeCAF-Pearl, presenting it as a flow-map distillation approach for fast all-atom cofolding and reporting throughput and speedup implications for screening and synthetic-data generation.

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Jun 03, 2026 · Reporting · Genesis Molecular AIZero-shot Pearl System Surpasses All Cofolding Models on OpenBind

Genesis published a blog post describing results from evaluating the Pearl system on the OpenBind Consortium benchmark, including reported success-rate figures for zero-shot protein–ligand cofolding settings and discussion of inference-time scaling and physics/AI-based pose ranking as part of the Pearl system.

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May 20, 2026 · Official · Genesis Molecular AI (press release on Genesis site)Incyte and Genesis Molecular AI Expand Collaboration

Incyte and Genesis announced an expanded collaboration to accelerate discovery of novel small molecules for Incyte-selected collaboration targets. Genesis said it will receive $120M upfront consideration (including $80M cash and $40M purchase of equity), plus research funding and milestone/royalty eligibility, with the expanded agreement adding at least five new collaboration targets.

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Oct 28, 2025 · Official · Genesis Molecular AI (press/release page)Introducing Pearl: The Next Generation Foundation Model for Drug Discovery

Genesis published a release describing Pearl as a generative 3D foundation model for biomolecular structure prediction, including claims about benchmark and real-world pipeline utility (including reported improvements relative to AlphaFold 3).

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Nov 13, 2024 · Official · Business WireGenesis Therapeutics Announces New Equity Investment and Collaboration with NVIDIA to Optimize Key Computational Methods for AI-powered Drug Discovery

Genesis announced an additional equity investment from NVentures and a collaboration with NVIDIA to optimize computational methods for GEMS, describing work to improve efficiency for neural network architectures relevant to drug discovery.

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Sep 10, 2024 · Official · Gilead press roomGilead and Genesis Therapeutics Announce Strategic Collaboration to Discover and Develop Novel Therapies

Gilead and Genesis announced a strategic collaboration to discover and develop novel therapies; Genesis’ partners/pipeline page describes this as a 2024 collaboration to deploy GEMS against multiple targets and references upfront consideration tied to three initial targets.

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Still resolving: Newsroom · Official X

What it builds

GEMS (Genesis Exploration of Molecular Space)

Genesis positions GEMS as its AI operating system for drug discovery, integrating foundation models, agents, and exploratory tooling for candidate generation, protein–ligand structure prediction, property/ADME prediction, and chemist-in-the-loop decisioning across the design cycle.

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Pearl (Placing Every Atom in the Right Location)

Pearl is presented as Genesis’ generative 3D foundation model for protein–ligand structure prediction, described as being deployed as part of GEMS to enable structure prediction and downstream utility in drug discovery workflows.

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DeCAF (Denoiser Cofolding All-atom Flowmap framework)

Genesis describes DeCAF as a distillation approach for faster all-atom cofolding, presented as a flow-map model (DeCAF-Pearl) to reduce inference steps while retaining structure-prediction performance for throughput-critical screening and synthetic-data generation.

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Milestones & partnerships