Deep learning for in vitro prediction of pharmaceutical formulations
Abstract
Current pharmaceutical formulation development still strongly relies on the traditional trial-and-error approach by individual experiences of pharmaceutical scientists, which is laborious, time-consuming and costly. Recently, deep learning has been widely applied in many challenging domains because of its important capability of automatic feature extraction. The aim of this research is to use deep learning to predict pharmaceutical formulations....
Paper Details
Title
Deep learning for in vitro prediction of pharmaceutical formulations
Published Date
Sep 6, 2018
Journal
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