Yongrui Xiao
About
My research project
Robotic and digital system for topical formulation designwe propose to develop a disruptively new technology that builds upon equipment miniaturisation based on microfluidics, and AI-enabled smart optimisation method, for automated and high-throughput formulation design for skin products. The need for high-throughput experimentation in skin permeation has been well recognised. The initial approach, due to Mitrogotri and co-workers [7], was to use electrical conductivity as a surrogate measure to reduce time, though this surrogate can be poor prediction of the actual permeation profile. Microfluidic devices have seen emerging applications in areas such as biosensors [8]; this concept is recently shown to have potential to miniaturise skin permeation tests [9], though its scale-up for automated high-throughput experimentation has not been explored. For the first time, we will engineer a microfluidic platform equipped with AI algorithms for automatic iterations between experimentation and optimisation, with >100 times gain in throughout expected.
This PhD project will benefit from the critical mass at the University of Surrey in skin research, led by Professor Tao Chen with further four academics involved (>10 PhD & postdoctoral researchers), as well as Dr Dimitrios Tsaoulidis (early career lecturer)’s expertise in microfluid. The proposed research is interdisciplinary in nature, aligning with the University’s strategic research theme ‘Lifelong Health’ and contributing to the ‘AI Institute’ in terms of an important healthcare application.
Supervisors
we propose to develop a disruptively new technology that builds upon equipment miniaturisation based on microfluidics, and AI-enabled smart optimisation method, for automated and high-throughput formulation design for skin products. The need for high-throughput experimentation in skin permeation has been well recognised. The initial approach, due to Mitrogotri and co-workers [7], was to use electrical conductivity as a surrogate measure to reduce time, though this surrogate can be poor prediction of the actual permeation profile. Microfluidic devices have seen emerging applications in areas such as biosensors [8]; this concept is recently shown to have potential to miniaturise skin permeation tests [9], though its scale-up for automated high-throughput experimentation has not been explored. For the first time, we will engineer a microfluidic platform equipped with AI algorithms for automatic iterations between experimentation and optimisation, with >100 times gain in throughout expected.
This PhD project will benefit from the critical mass at the University of Surrey in skin research, led by Professor Tao Chen with further four academics involved (>10 PhD & postdoctoral researchers), as well as Dr Dimitrios Tsaoulidis (early career lecturer)’s expertise in microfluid. The proposed research is interdisciplinary in nature, aligning with the University’s strategic research theme ‘Lifelong Health’ and contributing to the ‘AI Institute’ in terms of an important healthcare application.