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Generating Three-Dimensional Molecule Structures Using Generative Artificial Intelligence Models

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Summary

USPTO published patent application US20260100254A1 titled 'Generating Three-Dimensional Molecule Structures Using Generative Artificial Intelligence Models' filed on April 15, 2025 by inventors Daniel Alexander Reidenbach and Filipp Nikitin. The application discloses methods for using transformer layers and graph neural networks in a generative AI model to generate and refine 3D molecular structures for drug discovery based on initial structure, atom type, and bond type inputs.

What changed

USPTO published patent application US20260100254A1 disclosing methods for generating three-dimensional molecular structures using generative artificial intelligence. The application describes receiving a molecular generation request with initial structure, atom type, and bond type information; generating a fused input feature via embedding representations; producing an intermediate predicted structure using transformer layers; and refining the structure using graph neural network-based layers.

For pharmaceutical companies, technology developers, and medical device manufacturers working with AI-driven drug discovery platforms, this published application indicates potential future patent claims in the computational chemistry and generative AI space. Parties developing similar 3D molecular generation technologies should monitor the prosecution of this application for claim scope and potential freedom-to-operate implications.

What to do next

  1. Monitor for patent prosecution updates

Archived snapshot

Apr 13, 2026

GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.

← USPTO Patent Applications

GENERATING THREE-DIMENSIONAL MOLECULE STRUCTURES USING GENERATIVE ARTIFICIAL INTELLIGENCE MODELS

Application US20260100254A1 Kind: A1 Apr 09, 2026

Inventors

Daniel Alexander Reidenbach, Filipp Nikitin

Abstract

In various examples, methods for generating accurate three-dimensional molecular structures using a generative artificial intelligence model include receiving a request to generate a molecular structure, the request including an initial structure, atom type information, and bond type information for the molecular structure; generating a fused input feature based on embedding representations of the initial structure, the atom type information, and the bond type information; generating an intermediate predicted molecular structure based on a transformer layer of a generative artificial intelligence model and the fused input feature; refining, using a graph neural network-based layer in the generative artificial intelligence model, the intermediate predicted molecular structure into the molecular structure; and outputting the molecular structure.

CPC Classifications

G16C 20/50 G06N 3/0475 G16C 20/30 G16C 20/70

Filing Date

2025-04-15

Application No.

19180012

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Last updated

Classification

Agency
USPTO
Published
April 9th, 2026
Instrument
Notice
Legal weight
Non-binding
Stage
Final
Change scope
Minor
Document ID
US20260100254A1

Who this affects

Applies to
Pharmaceutical companies Technology companies Medical device makers
Industry sector
3254 Pharmaceutical Manufacturing 5112 Software & Technology 3345 Medical Device Manufacturing
Activity scope
AI/ML patent filing Drug discovery technology Computational chemistry
Geographic scope
United States US

Taxonomy

Primary area
Intellectual Property
Operational domain
Legal
Topics
Artificial Intelligence Pharmaceuticals

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