GENERALIZED ARTIFICIAL NEURAL NETWORK MODELLING AND ITS APPLICATION IN PERFORMANCE PREDICTION OF SUSTAINED RELEASE MONOLITHIC TABLETS
AbstractArtificial Intelligence is the simulation of human intelligence. From delivering simple groceries to doorsteps to solving the toughest task in scientists’ lab, it is surrounding human life in all the means. So how can the Pharma industry be untouched in the case of AI?! Artificial Neural Network (ANN) is a type of AI used to solve non-linear problems and predict the output for given input parameters from the training values. In this research work, such generalized ANN is developed to predict drug release from the sustained-release monolithic tablet. It is trained by the backpropagation method under supervised learning. This developed model is evaluated on the basis of RMSE, similarity and dissimilarity factors and can predict the output with the best achieved average error ~0.0095 and R2 0.9953. Such ANNs can be the best combination of experience and intelligence, which can eliminate tedious lab works that can be cost-effective and time-effective.
Article Information
40
6530-6539
767 KB
348
English
IJPSR
Tulsi H. Vyas * and Girish N. Patel
Department of Pharmaceutics, Shree S. K. Patel College of Pharmaceutical Education & Research, Ganpat University, Ganpat Vidyanagar, Mehsana-Gozaria Highway, Mehsana, Gujarat, India.
tulsiupadhyay90@gmail.com
25 January 2021
05 May 2021
28 May 2021
10.13040/IJPSR.0975-8232.12(12).6530-39
01 December 2021
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