Cancer treatments are being revolutionised by advances in the drug discovery process. In this MSc in Computer-Aided Drug Discovery for Cancer Therapeutics, you will learn foundational concepts in medicinal and computational chemistry, and how it is implemented in drug discovery and optimisation.
You will gain an understanding of how oncogenic pathways can be exploited to generate anti-cancer therapeutics, and how genomic approaches and bioinformatic resources and tools are used in the process of anticancer drug development. You will be introduced to computational methods ranging from chemical informatics through force-field-based simulation to quantum mechanical methods. The latest tools for modelling pharmacokinetics and pharmacodynamics, and AImachine learning methods, will also be presented.
You will have an opportunity to work with world-class researchers with industrial and academic drug discovery experience, including the inventors of two approved cancer medicines, to undertake a collaborative research project that will allow you to bring together and apply the methods and ideas that you have learned about throughout your course.
You will enhance your multidisciplinarity and teamwork, equipping you with the prerequisite skills for career development and further research in any aspect of drug discovery. You'll apply your learning to problem-solving in drug discovery via workshops and group work, deploying cheminformaticsstructure-based in silico design tools, training and applying machine learning models, and conducting data analysis with Jupyter notebooks.
This course is perfect for students with a background in medicinal chemistry, pharmacology, pharmacy, pharmaceutical sciences, biochemistry, chemistry or biochemical or chemical engineering.
You will benefit from immersion in the biomedical research environment at The University of Manchester, which covers the whole drug discovery journey. You will also be taught by members of the Centre for Applied Pharmacokinetics Research. Pharmacy at Manchester was ranked among the top 3 of its unit of assessment in the most recent Research Assessment Framework in 2021.