DE_Interact
PROJECT DESCRIPTION Determination of compatibility between drug and excipient is crucial step during any pharmaceutical formulation development. Presently only experiment based techniques are available to determine proabable incompatibility. This project is about development of artificial neural network (ANN) based model for prediction of incompatibility. This will save significant time and dependancy over costly tests like DSC and FTIR. This formal prediction allows formulators to choose excipient wisely.
DRUG EXCIPIENT INTERACTION PREDICTION BY ARTIFICIAL NEURAL NETWORK
Accuracy of Training Data: 0.9834 Accuracy of Validating Data: 0.9096
Total Data: 2300+
Developed by: Dr Swayamprakash Patel Asst. Professor Ramanbhai Patel College of Pharmacy Charotar University of Science and Technolgoy (CHARUSAT) CONTACT: swayamprakash.patel@gmail.com | swayamprakashpatel.ph@Charusat.ac.in
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