Machine Learning Enables Accurate Prediction of Asparagine Deamidation Probability and Rate.

Delmar, Jared A; Wang, Jihong; Choi, Seo Woo; Martins, Jason A; Mikhail, John P

Delmar, Jared A; Wang, Jihong; Choi, Seo Woo; Martins, Jason A; Mikhail, John P.

Afiliación

Delmar JA; Analytical Sciences, Biopharmaceutical Development, AstraZeneca, One MedImmune Way, Gaithersburg, MD 20878, USA.
Wang J; Analytical Sciences, Biopharmaceutical Development, AstraZeneca, One MedImmune Way, Gaithersburg, MD 20878, USA.
Choi SW; David H. Koch School of Chemical Engineering Practice, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Martins JA; David H. Koch School of Chemical Engineering Practice, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Mikhail JP; David H. Koch School of Chemical Engineering Practice, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Mol Ther Methods Clin Dev ; 15: 264-274, 2019 Dec 13.

Article en En | MEDLINE | ID: mdl-31890727

Palabras clave

IgG; antibody; deamidation; developability; drug development; mab; machine learning; prediction; stability; therapeutic protein

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Mol Ther Methods Clin Dev Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos

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