Research Journal of Science and Technology

Yatri R. Shah ¹, Parimal M. Prajapati ², Ravi N. Patel ³, Urvi Y. Patel ³, Dhrubo Jyoti Sen ³

Affiliations
1 Shukla Institute of Pharmaceutical Education & Research, Gujarat Technological University, Behind Marketing Yard, Nr. Lalpari Lake, Amargadh (Bhichari), Rajkot, Gujarat, IN
2 I. K. Patel College of Pharmaceutical Education and Research, Samarth Campus, Opp. Sabar Dairy, Himmatnagar-383001, Sabarkantha, Gujarat, IN
3 Department of Pharmaceutical Chemistry, Shri Sarvajanik Pharmacy College, Hemchandracharya North Gujarat University, Arvind Baug, Mehsana-384001, Gujarat, IN

Abstract

Caco-2 cells are most commonly used not as individual cells, but as a confluent monolayer on a cell culture insert filter (e.g., Transwell). When cultured in this format, the cells differentiate to form a polarized epithelial cell monolayer that provides a physical and biochemical barrier to the passage of ions and small molecules. The Caco-2 monolayer is widely used across the pharmaceutical industry as an in-vitro model of the human small intestinal mucosa to predict the absorption of orally administered drugs. The correlation between the in vitro apparent permeability (P¬app) across Caco-2 monolayers and the in-vivo fraction absorbed (fa) is well established.

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Parimal M. Prajapati ¹, Yatri R. Shah ², Dhrubo Jyoti Sen ³

Affiliations
1 I. K. Patel College of Pharmaceutical Education and Research, Samarth Campus, Opp. Sabar Dairy, Himmatnagar-383001, Sabarkantha, Gujarat, IN
2 Shree H. N. Shukla Institute of Pharmaceutical Education and Research, Behind Marketing Yard, Nr. Lalpari Lake, Amargadh (Bhichari), Rajkot, Gujarat, IN
3 Department of Pharmaceutical Chemistry, Shri Sarvajanik Pharmacy College, Hemchandracharya North Gujarat University, Arvind Baug, Mehsana-384001, Gujarat, IN

Abstract

Autonet, that represents a self training neural network. Results from the neural network are presented visually in order to rapid and easy convey to the medicinal chemist the important features derived by the neural network. The Autonet approach addresses this through the visual display of the hidden unit weights and thus rapidly conveys useful and informative results to the user. QSAR (Quantitative Structure-Activity Relationships) studies rely heavily upon statistics to derive mathematical models which relate the biological activity of a series of compounds to one or more properties of the molecules. The application of neural networks as a substitute for discriminant analysis. Neural networks in QSAR in a manner similar to multiple regression analysis. Comparative study of neural networks and regression analysis using a set of dihydrofolate reductase inhibitors. Their results indicated neural networks were superior to regression analysis in providing accurate predictions.

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