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Predicting QRS and PR interval prolongations in humans using nonclinical data
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Bergenholm, Linnéa (2017) Predicting QRS and PR interval prolongations in humans using nonclinical data. PhD thesis, University of Warwick.
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WRAP_Theses_Bergenholm_2017.pdf - Submitted Version - Requires a PDF viewer. Download (5Mb) | Preview |
Official URL: http://webcat.warwick.ac.uk/record=b3100799~S15
Abstract
Risk of cardiac conduction slowing (QRS/PR interval prolongations in monitored electrocardiograms) is assessed in nonclinical studies, where the current AstraZeneca strategy involves ensuring high margins to in vitro effects and statistical tests to identify in vivo effects. This thesis aims to improve QRS/PR risk assessment using pharmacokinetic-pharmacodynamic modelling for describing QRS/PR effects and evaluating translation to human effects.
Data for six compounds were collected from the literature and previously performed in vitro (sodium/calcium channel), in vivo (guinea pig/dog) and clinical AstraZeneca studies. Mathematical models were developed and evaluated to describe and compare effects across compounds and species.
Key results were that proportional drug effect models often suffice for small
QRS/PR changes (up to 20%), while larger effects require nonlinear models. Heartrate correction and circadian rhythm models reduced residuals primarily for describing baseline PR intervals, with highest impact in humans followed by dogs and guinea pigs. Meaningful (10%) human QRS/PR changes correlated to low levels of sodium channel block (3-7%) and calcium channel binding (13-21%) and to small effects in guinea pigs and dogs (QRS 2.3-4.6% and PR 2.3-10%). This suggests that worst case human effects can be predicted by assuming four times greater effects at the same concentration from dog/guinea pig.
Small changes in vitro and in vivo consistently translate to meaningful PR/QRS changes in humans across compounds. Accurate characterisation of concentration-effect relationships therefore require a model-based approach. Although the presented work is limited by the small number of investigated compounds, it provides a starting point for predicting human risk using routine QRS/PR data to improve the safety of new drugs.
Item Type: | Thesis (PhD) | ||||
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Subjects: | R Medicine > RM Therapeutics. Pharmacology | ||||
Library of Congress Subject Headings (LCSH): | Pharmacokinetics -- Mathematical models, Pharmacology -- Mathematical models, Drugs -- Design -- Mathematical models, Cardiovascular system -- Abnormalities -- Forecasting, Heart -- Effect of drugs on, Drugs -- Side effects -- Testing | ||||
Official Date: | February 2017 | ||||
Dates: |
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Institution: | University of Warwick | ||||
Theses Department: | School of Engineering | ||||
Thesis Type: | PhD | ||||
Publication Status: | Unpublished | ||||
Supervisor(s)/Advisor: | Chappell, M. J. (Michael J.) ; Evans, Neil D. | ||||
Sponsors: | Seventh Framework Programme (European Commission) | ||||
Format of File: | |||||
Extent: | xxi, 200 leaves : illustrations, charts | ||||
Language: | eng |
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