Development of novel, integrative bioinformatics approaches to identify drug targets with genomic vulnerabilities and illuminate mechanism of action

Abstract

Drug target identification is widely acknowledged as the most critical part of successful development of medicines. Since the sequencing of the first human genome was completed in 2003 a ‘genomic revolution’ has generated vast amounts of data that has illuminated our understanding of how germline (hereditary) and somatic (spontaneous) molecular changes to our genomes drives disease. This in turn has led to development of ‘targeted therapeutic’ small molecule and biologic-based medicines that specifically target these molecular changes, whilst attempting to spare non-affected tissues, and is particularly relevant to disease settings such as oncology where traditional non-targeted treatments such as chemotherapy suffer from significant off-target side-effects and toxicity. The relationship between efficacy and toxicity can be measured as Therapeutic Index (TI), or therapeutic window, defined as the toxic dose (TD) divided by the effective dose (ED) in a defined proportion of the population. In theory targeted therapies should have much larger therapeutic windows than chemotherapeutics, however the clinical trial failure rate is still unacceptably high and there remains significant limitations to the target selection and validation process. The most successful targeted cancer medicines launched during the last two decades have an acceptable TI and acceptable sparing of normal tissues. This PhD by published works aims to develop a suite of new methods which can be applied to target selection and clinical positioning and is divided into three work packages that: 1) develop novel analytical approaches for cancer target selection; 2) develop novel patient selection methods and understand compound mechanism of action and 3) develop the informatics architecture to support these novel approaches.

Date of Award	Jul 2025
Original language	English
Awarding Institution	Queen's University Belfast
Sponsors	Almac Discovery Ltd
Supervisor	Simon McDade (Supervisor), Ian Overton (Supervisor) & Tim Harrison (Supervisor)