Related Experiment Video
Updated: Aug 7, 2026

Modeling and Simulations of Olfactory Drug Delivery with Passive and Active Controls of Nasally Inhaled Pharmaceutical Aerosols
Published on: May 20, 2016
Comparison of neurofuzzy logic and neural networks in modelling experimental data of an immediate release tablet
Qun Shao1, Raymond C Rowe, Peter York
1Institute of Pharmaceutical Innovation, University of Bradford, Bradford, West Yorkshire, BD7 1DP, UK. q.shao@bradford.ac.uk
Abstract:
This study compares the performance of neurofuzzy logic and neural networks using two software packages (INForm and FormRules) in generating predictive models for a published database for an immediate release tablet formulation. Both approaches were successful in developing good predictive models for tablet tensile strength and drug dissolution profiles. While neural networks demonstrated a slightly superior capability in predicting unseen data, neurofuzzy logic had the added advantage of generating rule sets representing the cause-effect relationships contained in the experimental data.
Related Concept Videos
Modified-Release Drug Delivery Systems: Drug Release Characteristics
Pharmacodynamic Models: Direct Effect Model and Indirect Response Model

