Invention Grant
- Patent Title: Systems and methods for artificial intelligence-guided biomolecule design and assessment
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Application No.: US17886751Application Date: 2022-08-12
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Publication No.: US11869629B2Publication Date: 2024-01-09
- Inventor: Joshua Laniado , Julien Jorda , Matthias Maria Alessandro Malago , Thibault Marie Duplay , Mohamed El Hibouri , Lisa Juliette Madeleine Barel
- Applicant: Pythia Labs, INc.
- Applicant Address: US CA Culver City
- Assignee: Pythia Labs, Inc.
- Current Assignee: Pythia Labs, Inc.
- Current Assignee Address: US CA Los Angeles
- Agency: Choate, Hall & Stewart LLP
- Agent William R. Haulbrook; Ronen Adato
- Main IPC: G16B15/20
- IPC: G16B15/20 ; G16B35/00 ; G16B15/30 ; G16B40/20

Abstract:
Described herein are systems and methods for designing and testing custom biologic molecules in silico which are useful, for example, for the treatment, prevention, and diagnosis of disease. In particular, in certain embodiments, the biomolecule engineering technologies described herein employ artificial intelligence (AI) software modules to accurately predict performance of candidate biomolecules and/or portions thereof with respect to particular design criteria. In certain embodiments, the AI-powered modules described herein determine performance scores with respect to design criteria such as binding to a particular target. AI-computed performance scores may, for example, be used as objective functions for computer implemented optimization routines that efficiently search a landscape of potential protein backbone orientations and binding interface amino-acid sequences. By virtue of their modular design, AI-powered scoring modules can be used separately, or in combination, such as in a pipeline approach where different structural features of a custom biologic are optimized in succession.
Public/Granted literature
- US20230022022A1 SYSTEMS AND METHODS FOR ARTIFICIAL INTELLIGENCE-GUIDED BIOMOLECULE DESIGN AND ASSESSMENT Public/Granted day:2023-01-26
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