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CADABRE

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Computational design of synthetic antibody repertoires for accelerated therapeut...

Computational design of synthetic antibody repertoires for accelerated therapeutic discovery Synthetic human antibody repertoires are an important source of therapeutics; however, antibodies often exhibit undesirable developability liabilities, such as low stability, solubility, and polyreactivity, that limit their potent... ver más

31/07/2029

WEIZMANN

3M€

Presupuesto del proyecto: 3M€

Líder del proyecto

WEIZMANN INSTITUTE OF SCIENCE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-08-01

ERC-2023-ADG: ERC ADVANCED GRANTS Scope:Objectives

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Duración del proyecto: 59 meses Fecha Inicio: 2024-08-01
Fecha Fin: 2029-07-31

Líder del proyecto

WEIZMANN INSTITUTE OF SCIENCE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 3M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Synthetic human antibody repertoires are an important source of therapeutics; however, antibodies often exhibit undesirable developability liabilities, such as low stability, solubility, and polyreactivity, that limit their potential as drug candidates. CADABRE will design next-generation repertoires comprising billions of diverse human antibodies that exhibit excellent developability properties, with the following aims:1. Repertoire design: We will use our newly developed combinatorial Rosetta atomistic design paradigm to select human germline genes and design H3 multipoint mutants. These will combine into billions of diverse, low-energy, and foldable full-length antibody variable domains for expression in a phage-displayed repertoire. The repertoires will comprise hundreds of possible germline gene combinations, increasing the structural diversity relative to existing repertoires and the odds of obtaining diverse antibodies toward any antigen.2. Learning developability principles: High-throughput screening will identify heat-stable antibodies that are not polyreactive. Data from deep sequencing will be used to train an AI-based predictor of these properties that will be used to improve the repertoire and rank antibody candidates. We will iterate repertoire design, screening, and learning until we converge on a repertoire that exhibits excellent properties.3. Verifying relevance to therapeutic discovery: We will select antibodies that target antigens that represent relevant drug targets, verifying that the antibodies exhibit high stability, affinity, and developability.CADABRE combines the strengths of our protein-design methods (generating stable antibodies) and phage-display screening (unbiased binder selection). It will deepen our understanding of the biophysical underpinnings of antibody developability, develop new methods for ranking drug candidates, and generate new repertoires that will accelerate the discovery of life-saving therapeutic antibodies.

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