Original paper
Application of machine learning to predict monomer retention of therapeutic proteins after long term storage
Abstract
An important aspect of initial developability assessments as well formulation development and selection of therapeutic proteins is the evaluation of data obtained under accelerated stress condition, i.e. at elevated temperatures. We propose the application of artificial neural networks (ANNs) to predict long term stability in real storage condition from accelerated stability studies and other high-throughput biophysical properties e.g. the first...
Paper Details
Title
Application of machine learning to predict monomer retention of therapeutic proteins after long term storage
Published Date
Mar 1, 2020
Volume
577
Pages
119039 - 119039
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