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Big data approach to systematically investigate adverse drug reactions in older people

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

Project Description

The University of Bath is inviting applications for a PhD position under the supervision of Dr Prasad Nishtala and Professor Neil McHugh

The research project provides an opportunity to combine big data analytics and advance translational research in ageing.

The study will be the first Pharmacoepidemiological study to systematically investigate drug-related adverse events in older people. The risk of adverse drug events in older adults is a pervasive problem and is complicated by the presence of polypharmacy, multimorbidity, and geriatric syndromes. Current pharmacovigilance applications are inadequate to deal with predicting adverse drug events in a complex population of older adults, as it is difficult to precisely conclude and attribute whether or not an adverse drug event is a consequence of a single medication exposure. Post‐marketing surveillance and reports are often based on singletons (single medication), and the complex interplay of polypharmacy, multimorbidity, and geriatric syndromes contributing to adverse drug events in older people is under-recognised and underreported.

In this study, we propose to use novel methodology including association rules method that can be used to characterise the complexity of medication utilisation patterns including medication combinations and drug interactions and to detect adverse drug reactions signals due to confounding observed in observational studies.


Applicants should hold, or expect to receive, a First Class or high Upper Second Class UK Honours degree (or the equivalent qualification gained outside the UK) in a relevant subject. A master’s level qualification would also be advantageous. Non-UK applicants must meet our English language entry requirement

Informal enquiries should be directed to Dr Prasad Nishtala on email address:

Formal applications should be made via the University of Bath’s online application form:

Please ensure that you quote the supervisor’s name and project title in the ‘Your research interests’ section.

More information about applying for a PhD at Bath may be found here:

Anticipated start date: 28 September 2020.

Funding Notes

UK and EU candidates applying for this project will be considered for a University Research Studentship which will cover UK/EU tuition fees, a training support fee of £1,000 per annum and a tax-free maintenance allowance at the UKRI Doctoral Stipend rate (£15,009 in 2019-20) for a period of up to 3.5 years.


1. Nishtala PS, Chyou TY, Held F, Le Couteur DG, Gnjidic D. Association rules method and big data: Evaluating frequent medication combinations associated with fractures in older adults. Pharmacoepidemiology and drug safety. 2018; 27(10):1123-30.

2. Chyou TY, Nishtala PS. Nationwide adverse drug reaction screening using high process computing. Pharmacoepidemiology and drug safety, 28, p.401.

How good is research at University of Bath in Allied Health Professions, Dentistry, Nursing and Pharmacy?

FTE Category A staff submitted: 54.20

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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