Disintegration And Dissolution Of Solid Oral Dose Forms In The Fed Stomach : Novel Insights Using MRI Imaging In Humans
Lead Research Organisation:
University of Nottingham
Department Name: Sch of Molecular Medical Sciences
Abstract
Significant gaps remain in our basic knowledge of solid oral dosage form behaviour in the fed state. MRI imaging has the potential to provide new information on spatial and temporal processes occurring in the stomach. This iCASE collaboration between GSK and gastrointestinal imaging and specialists at the University of Nottingham addresses some of these key basic issues, with the potential to lead to better in-vitro and in-silico (modelling) tools for oral product development, and ultimately enhance our ability to tailor drug release in the fed state.
The student will optimise and exploit the ability of MRI imaging to detect and characterise the behaviour of dosage forms in the fed stomach by:
1) Identification and design of suitable test disintegrating formulations.
2) Optimisation of MRI techniques and image analysis for the evaluation of dosage form disintegration. In-vitro assessment will perform a key part of this work.
3) Evaluation of MRI techniques in human volunteers with carefully selected test formulations and test meals
The student will benefit from a world-leading research environment, a unique multi-disciplinary approach with clear translational applications, and tailored training opportunities including training in image data processing, biomedical imaging, machine learning and artificial intelligence
The student will optimise and exploit the ability of MRI imaging to detect and characterise the behaviour of dosage forms in the fed stomach by:
1) Identification and design of suitable test disintegrating formulations.
2) Optimisation of MRI techniques and image analysis for the evaluation of dosage form disintegration. In-vitro assessment will perform a key part of this work.
3) Evaluation of MRI techniques in human volunteers with carefully selected test formulations and test meals
The student will benefit from a world-leading research environment, a unique multi-disciplinary approach with clear translational applications, and tailored training opportunities including training in image data processing, biomedical imaging, machine learning and artificial intelligence
People |
ORCID iD |
Luca Marciani (Primary Supervisor) | |
Tejal Akbar (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/X524967/1 | 01/10/2022 | 30/09/2027 | |||
2753934 | Studentship | EP/X524967/1 | 01/10/2022 | 30/09/2026 | Tejal Akbar |