Overview
In this project, you'll explore how intelligent robotic systems can be designed and deployed for dissolution testing using a modular, human-robot collaborative approach.
About this opportunity
The future of small-molecule pharmaceuticals, driven by advancements like generative AI for novel molecule and material design, still critically depends on high-quality data from physical experiments to verify model-based projections. Some aspects of this verification are very process intensive, such as Long Term Stability Testing (LTSS). In this process, analytical data from multiple storage conditions, multiple packaging systems and multiple batches needs to be generated, in a regulated fashion, over an extended period (for example, up to three years of data needs to be generated). One of the tests that’s carried out on all solid dosage forms in LTSS is dissolution. This process is still very much manual and laborious as it doesn’t lend itself well to automation due to the heterogeneity in the process when using different materials and formulations.
During this project, we’ll start by addressing the robotics challenges related to preparing, dispensing and placing the dosage form into the test media, and removing it safely and in a timely manner at the end of the test, ready for the next test. Subsequently, we’ll integrate statistical frameworks with robust uncertainty estimates, such as conformal predictors, enabling the robot to autonomously determine its next action or request human intervention based on its confidence level. This approach aims not only to accelerate dissolution testing through innovative robotic systems but also to establish reliable, uncertainty-aware methodologies, fostering trust in AI-driven robots for pharmaceuticals.
This project offers a unique opportunity for you to:
- Develop intelligent robotic systems capable of adapting to the complexities of heterogeneous materials and formulations in dissolution testing
- Establish a reliable process in a safety-critical setting by developing a statistical framework with robust uncertainty estimates
- Deploy and validate the robotics system in real-world labs at the University of Liverpool and in collaboration with our industrial partner, Bristol Myers Squibb (BMS)
- Collaborate with external partners in our collaborative network of ongoing multidisciplinary projects.
You’ll work across the research groups of Dr Gabriella Pizzuto (Computer Science) and Dr Anthony Bradley (Chemistry) and contribute towards cutting-edge robotics research in AI-driven robotic scientists at the University of Liverpool, focused on their deployment in real-world applications. You’ll also have the opportunity to collaborate with external partners on our ongoing multidisciplinary projects.
This project is offered under the University of Liverpool EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry along with other studentships for applicants from backgrounds spanning the physical and computer sciences to start in October 2025. Students will develop core expertise in robotic, digital, chemical and physical thinking, which they’ll apply in their domain-specific research in materials design, discovery and processing. By working with each other and benefiting from a tailored training programme, students will become both leaders and fully participating team players, aware of the best practices in inclusive and diverse R&D environments.
Who is this opportunity for?
This project is open to UK and international applicants. Candidates will have, or be due to obtain, a master’s degree or equivalent related to Physical Science, Engineering or Computational Science, or an international equivalent. Exceptional candidates with a First Class undergraduate degree or international equivalent in an appropriate field will also be considered. The minimum English Language requirements for international candidates is IELTS 6.5 overall (with no band below 5.5) or equivalent. Find out more about English language requirements.
We want all our staff and students to feel that Liverpool is an inclusive and welcoming environment that actively celebrates and encourages diversity. We’re committed to working with students to make all reasonable project adaptations including supporting those with caring responsibilities, disabilities or other personal circumstances.