BenevolentAI Patent Application, ML Identifies Biological Entities for Drug Discovery

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METHOD AND SYSTEM FOR IDENTIFYING BIOLOGICAL ENTITIES FOR DRUG DISCOVERY

Application US20260112507A1 Kind: A1 Apr 23, 2026

Assignee

BenevolentAI Technology Limited

Inventors

Dane Sterling CORNEIL, Maciej Ludwick Wiatrak, Angus Richard Greville Brayne, Vinay Prashanth SUBBIAH

Abstract

A computer-implemented method of training a machine learning model to identify biological entities for drug discovery is disclosed. The method comprises providing a training data set comprising a plurality of entity-linked text sequences, each text sequence including a mention of a biological entity, where the biological entity is linked to a corresponding biological entity identifier from a set of possible biological entity identifiers; masking the mention of the biological entity within each text sequence; encoding each masked text sequence into an input representation for a machine learning model; and training a machine learning model to predict the unique entity identifier of the masked biological entity based on the input representation. The described method is able to utilise the full breadth of the rich contextual information available in the biomedical text corpus to predict new biological targets for drug discovery and avoids the restrictions intrinsic to relationship prediction using knowledge graphs. The ability to identify more promising, biologically relevant targets in an automated manner, significantly reduces the requirement of human input and reduces the failure rate in targets that are progressed in the drug delivery pipeline.

CPC Classifications

G16H 50/70 G16B 15/30 G16B 40/20 G16H 70/40

Filing Date

2025-11-05

Application No.

19380404

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