A recent graduate of Oxford Lifelong Learning’s MSc in Nanotechnology for Medicine and Health Care, Krish Ramadurai, has published a book, Machine Learning-Driven Rational Design in Nanomedicine. The book, which details a practical ML pipeline for mRNA drug delivery, was a product of Krish’s MSc dissertation project. Read on to find out about his research and his time studying on the MSc.
Tell us about the focus of your book.
The book explores how machine learning can transform the design of lipid nanoparticle (LNP) systems for mRNA therapeutics. It focuses on integrating chemoinformatics, molecular fingerprinting, and advanced machine-learning techniques to predict transfection efficiency and to accelerate the rational design of nanocarriers for oncology applications.
How did your time on the MSc contribute to its publication?
Working with my advisors, Professor Carlisle and Professor Banerjee at the Institute of Biomedical Engineering, as well as with Professor Nair at St. Catherine’s College, directly shaped the book’s development. My dissertation research formed the methodological backbone of several chapters, particularly those on supervised and semi-supervised modeling of LNP performance.
Meeting my supervisor, Professor Banerjee, was pivotal. Working closely with him allowed me to tackle real-world translational problems at the intersection of engineering and biology. The intellectual partnership we developed during the MSc naturally evolved into my DPhil work, as the MSc served as both a proving ground and a springboard, enabling us to identify deeper scientific questions and expand the scope to more ambitious modeling challenges.
For those who may be unfamiliar with the field, tell us about the real-world impact of this research.
Drug development has very high failure rates, particularly in oncology. By integrating machine learning into early-stage screening, we can reduce experimental redundancy, lower costs, and prioritize the most promising therapeutic designs. More broadly, this work contributes to a shift toward AI-native drug development workflows, in which computational modeling becomes central to preclinical decision-making.
Krish is now undertaking a DPhil at the University of Oxford alongside his MSc dissertation supervisor, Professor Banerjee.
