Through the program, David aims to leverage advanced machine learning technologies to accelerate the development of precision medicine and drug discovery. His research will integrate real-world data, including various omics data and electronic health records, to develop personalized disease risk and treatment response prediction models. These models will not only help in formulating personalized treatment strategies that optimize outcomes and minimize adverse effects but will also propose cost-reduction methods by applying these models to the time-consuming and expensive clinical trial phases, enabling rapid and accurate selection of eligible patients.
David expressed his honor in being selected for the program, stating, "I am thrilled to have the opportunity to collaborate with emerging researchers in Sweden on significant societal issues such as climate change, precision medicine, and innovative energy solutions. The guidance and support from experienced mentors will undoubtedly enhance my research capabilities. I am committed to utilizing the knowledge and experience gained from this program to achieve better research outcomes and contribute to both academia and society."