AI-accelerated therapeutic antibody development: practical insights DOI Creative Commons
Luca Santuari,

Marianne Bachmann Salvy,

Ioannis Xénarios

и другие.

Frontiers in Drug Discovery, Год журнала: 2024, Номер 4

Опубликована: Сен. 3, 2024

Antibodies represent the largest class of biotherapeutics thanks to their high target specificity, binding affinity and versatility. Recent breakthroughs in Artificial Intelligence (AI) have enabled information-rich silico representations antibodies, accurate prediction antibody structure from sequence, generation novel antibodies tailored specific characteristics optimize for developability properties. Here we summarize state-of-the-art methods analysis. This valuable resource will serve as a reference application AI analysis sequencing datasets.

Язык: Английский

Reading the repertoire: Progress in adaptive immune receptor analysis using machine learning DOI Creative Commons

Timothy J O'Donnell,

Chakravarthi Kanduri, Giulio Isacchini

и другие.

Cell Systems, Год журнала: 2024, Номер 15(12), С. 1168 - 1189

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

2

AI-accelerated therapeutic antibody development: practical insights DOI Creative Commons
Luca Santuari,

Marianne Bachmann Salvy,

Ioannis Xénarios

и другие.

Frontiers in Drug Discovery, Год журнала: 2024, Номер 4

Опубликована: Сен. 3, 2024

Antibodies represent the largest class of biotherapeutics thanks to their high target specificity, binding affinity and versatility. Recent breakthroughs in Artificial Intelligence (AI) have enabled information-rich silico representations antibodies, accurate prediction antibody structure from sequence, generation novel antibodies tailored specific characteristics optimize for developability properties. Here we summarize state-of-the-art methods analysis. This valuable resource will serve as a reference application AI analysis sequencing datasets.

Язык: Английский

Процитировано

0