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Dongyang Zheng

Project: Intelligent optimisation of inline purification – delivering automated product profiling for pharma

Supervisors: Anna Slater, Prudence Wong, Adam Clayton (Univ. Leeds), Richard Bourne (Univ. Leeds)

Industry Partner: Astra Zeneca

What inspired you to pursue this project and join the DAMC CDT?

I have a strong background in pharmaceutical chemistry and chromatography, developed through both academic and industrial experience in China. As a research assistant at the Chinese Academy of Sciences (CAS), I gained exposure to autonomous experimental equipment and contributed to the development of an autonomous membrane separation platform. This aroused my interest in interdisciplinary and autonomous research. I then gained two years of industrial experience as a chromatography engineer at ThermoFisher and Danaher, where I worked with companies and research institutes engaged in AI4Sci-related research. These experiences deepened my understanding of AI in scientific discovery and process development.

This motivated me to pursue an MSc in Digital Chemistry at the University of Liverpool, where I have developed skills in AI, computation, robotics, and automation. The PhD project in data-driven pharmaceutical purification closely aligns with both my background and experience. I am particularly motivated by its potential to enable autonomous purification method development and to contribute to in the pharmaceutical industry.

What is your research project about, and what impact do you hope it will have?

My PhD research aims to develop a data-driven and closed-loop framework for purification method development and optimization. Traditional purification development in the pharmaceutical industry is highly dependent on scientists’ experience and is often time-consuming. My PhD project aims to address three challenges: (1) identifying the most critical variables affecting chromatographic separation, including discrete variables such as pH and column selection, and continuous variables such as temperature, flow rate, and elution time; (2) designing effective elution method for complex multi-component mixtures, where separation is particularly challenging; and (3) developing suitable optimization algorithms for purification. In collaboration with AstraZeneca, the long-term goal is to simplify and optimize purification method development in the pharmaceutical industry and integrate it into a synthesis–purification–analysis platform.

What has been the most exciting or rewarding part of your PhD journey so far and how does your project benefit from being part of an interdisciplinary CDT?  

The most rewarding part of my PhD journey so far has been developing an interdisciplinary way of thinking. The CDT’s training, such as computation and data science, helps me to think about research problems from new perspectives. Events such as winter schools and industrial seminars have also expanded my professional network. Working with a multidisciplinary supervisory team and industrial partners makes it easier for me to connect my research to real-world challenges.