The main aim of this research project is to use dataset available in the UK Biobank to analyze important factors affecting drug (antidiabetic drug for T2DM, beta-lactam antibiotics for sepsis) efficacy. By integrating the different types of data, such as genetic, proteomics, digital imaging, and clinical, we hope to gain a better understanding of the underlying factors that contribute to the development and prognosis of T2DM and sepsis. To quantitatively describe the relationship between factors, pharmacokinetics or pharmacodynamics and clinical outcomes. For example, there is a racial difference between !-cell function and insulin sensitivity, which are common index of glucose metabolism. But we have no idea about quantitative model racial difference of antidiabetic drug target. We hope to connect the molecular phenotypes to clinical and disease phenotypes to identify underlying biomarkers and therapeutic targets.
Our research project will last for three years, with the first year dedicated to data acquisition, preprocessing, and cleaning. The second year will focus on data analysis, model development, validation, and interpretation, while the third year will be for writing and publishing our results. Our project’s public health impact is significant, as it has the potential to personalize treatment risk assessment and improve drug effect, leading to improved therapeutic strategies and reduced healthcare costs of T2DM and sepsis.
