Title: Determining the Clinical Utility of Pre-emptive Pharmacogenetic Testing and Defining Optimal Models for Implementation
Funder: Department of Health and Social Care

Abstract: Medicines are the most common therapeutic intervention in healthcare, yet the efficacy and safety of many drugs show considerable inter-personal variation. Some patients are prescribed inefficacious medication, whereas others develop adverse drug reactions. This variation has a significant personal, clinical, and economic impact, leading to poorer individual and societal outcomes. Strategies are required to reduce this variability. One approach is to leverage knowledge of an individual's genetic information to support medicines optimisation, better informing medicine selection and dosing (pharmacogenetics). Evidence-based guidelines to support pharmacogenetic-guided prescribing are available for many commonly prescribed medicines. Despite a good understanding of these medicine-gene relationships, clinical implementation in the UK is limited to a small number of medicines. This is typically carried out reactively, where single genes are analysed when a medication is considered. Given the high population frequency of genetic variation which influences the efficacy and safety of medicines, an alternative approach to pharmacogenetic guided prescribing is pre-emptive panel testing. This involves testing individuals for many common pharmacogenetic variants at a set time, irrespective of the medicine they are prescribed. This information can then be integrated into a patient's medical records and used to inform prescribing. I have developed three work-packages to determine the value of this pre-emptive approach to pharmacogenetic testing and to investigate how best to implement this in clinical practice.I will first review the literature describing previous efforts to implement pre-emptive pharmacogenetic testing. This will be undertaken using the Consolidated Framework for Implementation Research to characterise existing models and identify the determinants of successful clinical implementation. Secondly, I will undertake a cross-sectional study linking patient genotype with prescribing data to measure the clinical utility of pre-emptive pharmacogenetic panel testing. In-patients (n=323) admitted to the Manchester University NHS Foundation Trust through the Acute Medical Unit and outpatients (n=323) in Genomic Medicine will be recruited. A DNA sample will be taken from each participant and tested using the AgenaTM iPLEX PGx 74 and CYP2D6 copy number panels, covering the most relevant variants in 20 principal genes involved in drug metabolism. Inpatient and community prescribing data will be cross-referenced against patient genotype. The primary outcome is the proportion of patients with a genotype related to a medicine they are currently, or have previously been, prescribed. Genotype-phenotype relationships will be assigned where there is high level evidence for clinical actionability. This will determine the potential clinical value of the approach, both in the primary and secondary care settings. Finally, I will undertake a stated preference study, employing a Discrete Choice Experiment (DCE), to identify clinical and non-clinical stakeholder preferences for the design of a pharmacogenetic service. A national sample of secondary care (n=150), primary care (n=150), and public stakeholders (n=300) will be recruited. The DCE will measure the relative value attached to factors influencing the design of a system to deliver pre-emptive pharmacogenetic testing. Implemented effectively, pharmacogenetics has the potential to improve patient outcomes. The outputs from each of these work-packages will inform the development of a local and national pharmacogenetic service.

Lay abstract: Background: Many patients do not respond to their medicines as expected. There are many reasons for this and 'medicines optimisation' is the idea that outcomes can be improved by ensuring patients are on the right medicine, at the right dose, at the right time. This fellowship investigates whether knowing about differences in an individual's genetic code could be used to improve medicines optimisation. A large proportion of medicines need to be activated by chemicals in the body before they work. Codeine, for example, needs to be converted into morphine before it will deliver pain relief. This is performed by an enzyme in the body called CYP2D6 but approximately 10% of people have a genetic change which means their CYP2D6 enzyme does not work effectively. People with this genetic difference have a poor response to codeine. This is an example of how an individual's genetic code can influence their response to medicines, a concept known as pharmacogenetics. It is increasingly recognised that the effectiveness and safety of many routinely prescribed medicines are influenced by relatively common genetic differences in the population. Despite a good basic scientific understanding of these gene-medicine relationships, this knowledge is rarely applied in clinical practice. One approach to implementing pharmacogenetics in clinical practice is to test for many common pharmacogenetic gene changes at the same time, before an individual is prescribed medication. This information can then be integrated into a patient's medical records and used to inform medicine selection when appropriate. Aims: Split over three work-packages, this fellowship aims to investigate the usefulness of pre-emptive pharmacogenetic testing and will consider how best to implement this approach.Methods: I will first review the existing literature to understand previous efforts to implement pharmacogenetics, reviewing the key components of each model. I will perform this using the consolidated framework for implementation research. Secondly, I will measure the potential usefulness of pre-emptive pharmacogenetic testing. Patients attending the Manchester University NHS Foundation Trust (MFT) will be eligible for recruitment. A DNA sample will be taken from each participant and tested for 75 genetic differences related to drug metabolism. I will recruit 323 patients from the outpatient department, and 323 patients from the Acute Medical Unit. Participants will provide consent for access to their inpatient prescription charts and their community prescribing history, via the Manchester Care Record. I will cross-reference anonymised prescribing data against the genetic results, establishing if knowledge of genetics would have influenced prescribing. This will enable judgement of the potential clinical usefulness of the approach, both in the primary and secondary care settings. I will also look to see whether there are certain groups of patients where pre-emptive pharmacogenetic testing would be of particular value.For pharmacogenetics to be used effectively in clinical practice, there needs to be a service performing the genetic testing and then a system which healthcare workers can interact with, allowing them to use the data to improve prescribing. There is no consensus how a system or service like this should be constructed in the UK. Therefore, finally, I will assess public and healthcare-worker preferences around this via a survey which asks participants to choose their preferred models for pharmacogenetic testing.Dissemination Strategy: The findings from this fellowship will be disseminated within NHS England working groups, as part of an ongoing national strategy to support the clinical implementation of pharmacogenetics. Data will be published in peer-reviewed journals and presented at international conferences.Patient and Public Engagement: Public representatives have been involved in the design of this application. A bespoke patient and public engagement programme has been created, which will support protocol development and public dissemination strategies.

Research activity codes: 7.3 MANAGEMENT AND DECISION MAKING
Health categories: GENERIC HEALTH RELEVANCE