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Title: Implementing computational techniques to investigate immune-mediated adverse drug reactions
Author: Ghattaoraya, G.
ISNI:       0000 0004 7428 7008
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2018
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The highly polymorphic human leukocyte antigens are an important player in the immune response against pathogens. However, the variability can also cause problems to patients, clinicians and drug manufacturers due to the phenomenon of immunologically based adverse drug reactions (ADRs) where the interaction between the drug and antigen presenting proteins can interfere with the body’s ability to recognise host cells leading the immune system to mount a response against the host. The underlying mechanisms by which this is brought about are not fully understood. Over recent years a number of studies have reported HLA alleles are associated with adverse drug reactions where this number is growing. This has made research into the field increasingly challenging as relevant data has become spread across the literature. To address this issue, a centralised and searchable web database (HLA-ADR) was constructed which was populated with data extracted from a literature review investigating HLA alleles that have been associated with ADRs. The HLA-ADR database was then used to investigate a question that arose when analysing the data; there was an apparent trend whereby it seems that patients of Asian descent were more prone to ADRs compared to other populations. The analysis in this thesis found no evidence to support this hypothesis and instead revealed potential reporting bias and issues with the poor replication of findings in the literature. Finally, HISTO SPOT, a new HLA typing method that aims to type patients with high turnaround and at low cost where it highlights patients carrying one or more of a panel of HLA alleles known to be associated with immune mediated ADRs was investigated. The method is able to accurately type patients with 100% concordance with currently implemented HLA sequence based typing. Alongside this, a clinical decision support tool was developed to provide clinicians with a means to interpret the HISTO SPOT results by providing expert knowledge. In conclusion, the bioinformatical tools developed in this thesis provide a potential framework by which to aid research and clinical decision making. The tools will hopefully advance the field and provide a stepping stone towards the goal of personalised medicine.
Supervisor: Alfirevic, Ana ; Jones, Andy ; Dickson, Rumona Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral