Development and Machine Learning-based Drug Release Prediction of Age-appropriate Combined Therapy

This project is proposed to develop age-appropriate (geriatric/paediatric) combined therapy with poorly water soluble drug(s) using advanced manufacturing methods, i.e. microwave-induced in situ amorphization of mini-tablets and/or hot melt (co-) extrusion with appropriate down-stream processes and a combination of novel analytical techniques and to further explore the drug release profiles with a final view to establishing a robust prediction platform based on Machine Learning (ML). 

Applicants should have a 1st or 2.1 honours degree (or equivalent) in a relevant subject. Relevant subjects include Pharmacy, Pharmaceutical Sciences, Biochemistry, Biological/Biomedical Sciences, Chemistry, Engineering, or a closely related discipline. Students who have a 2.2 honours degree and a Master’s degree may also be considered, but the School reserves the right to shortlist for interview only those applicants who have demonstrated high academic attainment to date.

Training will be provided on the following:

•     In situ microwave amorphization Mini-tablet compression

•    Thermal analysis (DSC & TGA)

•   Imaging techniques (SEM & AFM)

•   Spectroscopic techniques

Expected Impact Activities include

•       Promising manufacture technique(s) to be selected for formulating challenging FDCs with different structures/properties.

•       Most functional excipient/mix to be identified among all studied.

•       A better understanding on the relationship between formulation composition, processing method and associated parameters and performance of both the intermediate and final products.

•       An innovative dosage form to be recommended for further clinical studies.

•       A robust drug release prediction tool to be established based on machine learning.