Associate Professor Michael Ward

Excludes commercial-in-confidence projects.

Research outputs for the last seven years are shown below. Some long-standing staff members may have older outputs included. To see earlier years visit ORCID, ResearcherID or Scopus

Open access indicates that an output is open access.

Chapters

Journal Articles

Reports

The broad focus of my research is upon the factors that influence the way in which patients respond to drug therapy. I have a particular interest in the interface between foundational sciences and clinical practice. My specific interests include;

Pharmacogenetics

Pharmacogenetics seeks to individualise drug therapy according to genetic differences between patients. This field is developing at a rapid pace and is likely to change the way in which medicine is practiced in the future. Pharmacogenetics has the potential to greatly accelerate the implementation of personalised medicine, using therapeutic regimens tailored to each individual’s genetic profile. Despite this promise and although productivity in basic pharmacogenetic research continues to escalate dramatically, harnessing this progress to achieve positive clinical outcomes poses considerable challenges. I have previously been involved in the development of provisionally patented software, SNiPPED, that facilitates multiplex genotyping with the use of denaturing high performance liquid chromatography.

Drug Metabolism and Interactions

Drug metabolism and interactions are major contributors to patient drug response. I am currently involved in a number of studies aimed at further understanding the molecular basis of drug metabolising enzyme function and of drug interactions at both a laboratory and clinical level. Laboratory based analyses involve the use of animal models including transgenic mice and isolated perfused organs. Clinical studies focus upon the impact of drug metabolism and interactions upon clinical outcomes.

Pharmacometrics

Pharmacometrics utilises computational modelling approaches to predict drug response. These models describe the relationship between drug concentrations (pharmacokinetics), mechanism of action (pharmacology), patient variables and disease characteristics to predict response to medications. Drug metabolism is an important contributor to elements of these models. Increasingly these models require the inclusion of pharmacogenetic data and understanding.