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MRC Precision Medicine DTP: Non-adherence in chronic conditions (initially tuberculosis): a quantitative, methodological, approach

  • Full or part time
  • Application Deadline
    Monday, April 08, 2019
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Background
Non-adherence to prescribed medications is an international problem with major implications.1 It is, however, frequently unrecognised: undiscovered by prescribers and not divulged by patients.1 Adherence can be particularly problematic in chronic diseases, which last for three months or longer and require correspondingly long treatment. Pan-disease adherence guidelines tend to tacitly assume that all doses are required for successful treatment.2 The reality is complex and dependent on pharmacokinetics- a drug can be more or less ‘forgiving’ of non-adherence.3 Rather than the simplistic thresholds frequently used in trials and other studies, where non-adherence is often defined as taking <80% of doses, three domains need to be considered- initiation (timing of first dose), implementation (taking drugs not as recommended e.g. skipping weekends) and persistence/discontinuation. These components constitute ‘therapeutic coverage’- the proportion of time patients are exposed to efficacious drug concentrations, for individual or clinical reasons.4 In order to improve treatment success, regimens can be designed with the complexity of adherence patterns in mind and should be adopted in light of the differences between adherence patterns in clinical trials and normal care.

Aims
To investigate how adherence patterns should influence our approach to treatment to maximise favourable outcomes, starting with tuberculosis as a model disease:
Objectives
1) Describe non-adherence patterns across the duration of treatment in tuberculosis, using pre-existing and newly collected data sources.
2) Determine how different adherence patterns impact treatment outcomes?
3) Ascertain if particular patient characteristics are associated with being at risk of the most detrimental adherence patterns.
4) Working with modelling colleagues, examine how such patterns could influence optimal dosing.

Training outcomes
This project would suit someone with epidemiological or statistical methods training, or similar quantitative training e.g. through an epidemiologically-orientated Master’s in Public Health. Completion of this PhD will provide the student with a sought-after skillset in epidemiology, statistics and, critically, pharmacoepidemiology, where there is currently a skills shortage. The student will thus have cross-disciplinary expertise that will enable them to make a valuable contribution to drug development and evidence-based drug adoption by policymakers. These skills will therefore be applicable within the academic sphere, as well as in the pharmaceuticals industry and policy arenas. The student will have the opportunity to attend training courses in pharmacology e.g. at King’s College London and pharmacoepidemiology e.g. at the London School of Hygiene & Tropical Medicine, as well as undertake exchange visits to modelling colleagues in the UK and Europe. The student will additionally develop communication skills e.g. through the opportunity to present at conferences, submit journal articles, etc.

Funding Notes

Start: September 2019

Qualifications criteria: Applicants applying for a MRC DTP in Precision Medicine studentship must have obtained, or will soon obtain, a first or upper-second class UK honours degree or equivalent non-UK qualifications, in an appropriate science/technology area.

Residence criteria: The MRC DTP in Precision Medicine grant provides tuition fees and stipend of at least £14,777 (RCUK rate 2018/19) for UK and EU nationals that meet all required eligibility criteria.

Full eligibility details are available: View Website

Enquiries regarding programme:

References

1 Horne R, Weinman J, Barber N, Elliott R, Morgan M. Concordance, adherence and compliance in medicine taking. Southampton (UK), 2005.
2 National Institute for Health and Care Excellence. Medicines adherence: involving patients in decisions about prescribed medications and improving adherence, 2009.
3 Urquhart J. The electronic medication event monitor. Lessons for pharmacotherapy. Clin Pharmacokinet 1997; 32(5): 345-56.
4 Kenna LA, Labbe L, Barrett JS, Pfister M. Modeling and simulation of adherence: approaches and applications in therapeutics. AAPS J 2005; 7(2): E390-E407.

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