Multidisciplinary Approach for Designing of Drug Delivery System: Leveraging Artificial Intelligence and Experimental Design for Enhanced Helicobacter pylori Formulation Optimization

The management of Helicobacter pylori (H. pylori) remains a complicated challenge worldwide. There is need for more effective optimised formulations with better therapeutic efficiency and less drug resistance. Rapid advancements have been achieved regarding the development of pharmaceutical formulations for the treatment of H. pylori, which demands new and improved approaches towards product optimization. This review gives an account of a combined approach of employing Design of Experiments and Artificial Intelligence techniques to enhance the optimization of pharmaceutical formulations for H. pylori treatment. The Design of Experiments concept aids in a systematic way of considering multiple variables and can optimize formulation parameters with a minimal number of experimental trials. Such techniques within Artificial Intelligence algorithms, machine learning, and predictive modelling all deal with the analysis of various complex data and allow for useful predictions, real-time optimization. Through the joint use of these two techniques, the formulation process could be revised to enable identification of important formulation factors and desired outcomes; therefore, it will speed up the development of new therapeutic solutions. This review assesses the use of the Design of Experiments and Artificial Intelligence in optimizing pharmaceutical formulations in the treatments against H. pylori. It also discusses various challenges and limitations associated with the usage of these technologies in pharmaceutical research and gives further suggestions for the future development process. The positive implementation of Design of Experiments and Artificial Intelligence promises great opportunities for H. pylori treatment, enabling drug formulation technology to improve patient compliance drastically.