Using AI to Combat Drug Resistance - an Interview with PhD student Rosan Kuin
Rosan Kuin started her PhD in July at the LACDR under supervision of prof. Gerard van Westen and Dr. Meindert Lamers. She completed a BSc. in Pharmaceutical Sciences at the VU University in Amsterdam in 2017. After that she started two master programs, Drug Discovery & Safety with a specialization in Computational Drug Design and the program Bioinformatics & Systems Biology with a major in Bioinformatics.
What is your research focused on?
‘Tuberculosis (TB) is a bacterial infection that most often affects the lungs, that causes many deaths every day. While there are a number of antibiotic treatments available, resistant forms of TB form a growing threat to global health. Hence, there is an urgent need for new antibiotics to increase treatment options.’
‘My research is focused on understanding how specific bacterial TB proteins become resistant to their inhibitors. Such understanding can be obtained by understanding the effect of point mutations in TB. In this project we aim to predict the effect of all possible mutations for therapeutically relevant proteins using AI. By interpreting such AI models we hope to better understand the mechanisms that lead to antibiotic resistance. This knowledge can then be used to search for new candidate drugs that inhibit these proteins and circumvent the mechanisms of drug resistance.’
‘While there are a number of antibiotic treatments available, resistant forms of TB form a growing threat to global health.’
What is the goal you want to reach with this research?
‘The ultimate goal that I want to reach is to build an AI model that is able to accurately predict the effect of all mutations for therapeutically relevant TB proteins. Ideally, we want to use these predictions to search for or design new candidate antibiotics that are less vulnerable towards resistance.’
What will be the benefit for society if you succeed in your aim?
‘If I succeed in my aim there will be a fundamentally better understanding of how bacteria acquire resistance to antibiotics in TB. This knowledge can then be applied as starting point for the search for new antibiotics, from which society will benefit.’