Experimental design for discrepant models: selecting mechanistic models of IKr through informative experiments
In cardiac electrophysiology applications, mathematical models are relied upon to provide quantitatively accurate predictions. The potassium current IKr is of particular importance because its blockage by drugs is known to cause dangerous changes in heart rhythm. To help quantify the risk presented...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
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2025
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| Online Access: | https://eprints.nottingham.ac.uk/80409/ |
| _version_ | 1848801244222586880 |
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| author | Shuttleworth, Joseph George |
| author_facet | Shuttleworth, Joseph George |
| author_sort | Shuttleworth, Joseph George |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | In cardiac electrophysiology applications, mathematical models are relied upon to provide quantitatively accurate predictions. The potassium current IKr is of particular importance because its blockage by drugs is known to cause dangerous changes in heart rhythm. To help quantify the risk presented by potential new drugs, we require mathematical models which produce quantitatively accurate predictions and accurately describe the gating behaviour of a cell’s ion channels (particularly those which carry IKr). Building such models requires experimental data that allows both the selection of appropriate model structures and the inference of model parameters. Recently, short “information-rich” experimental designs have been developed, allowing cell-specific models to be fitted. Here, new experimental designs can be specified, which allow the collection of new data under previously unseen IKr dynamics. The resulting data promise to improve models of the gating dynamics of IKr, improve our understanding of cardiac electrophysiology as a whole, and improve the risk-classification of new drugs.
In this thesis, we introduce the methods necessary for the fitting and validation of cell-specific mathematical models of IKr using a diverse ensemble of information-rich experimental designs. This approach allows us to produce empirical quantifications of predictive uncertainty and permits the comparison of literature models in terms of their predictive accuracy and the variability of parameter estimates across cells. Whilst some models produce more accurate predictions than others, a certain amount of model discrepancy seems unavoidable. Our results suggest that this discrepancy is caused, in part, by the presence of experimental artefact effects, which, when unaccounted for, confound our parameter estimates, contributing appreciably to the apparent cell-to-cell variability of parameters relating to the kinetics of channel gating. Moreover, we demonstrate that our broadly applicable multiprotocol approach allows for thorough validation of our models, a realistic quantification of predictive uncertainty, and the selection of suitable mathematical models. |
| first_indexed | 2025-11-14T21:04:22Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-80409 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T21:04:22Z |
| publishDate | 2025 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-804092025-07-31T04:40:15Z https://eprints.nottingham.ac.uk/80409/ Experimental design for discrepant models: selecting mechanistic models of IKr through informative experiments Shuttleworth, Joseph George In cardiac electrophysiology applications, mathematical models are relied upon to provide quantitatively accurate predictions. The potassium current IKr is of particular importance because its blockage by drugs is known to cause dangerous changes in heart rhythm. To help quantify the risk presented by potential new drugs, we require mathematical models which produce quantitatively accurate predictions and accurately describe the gating behaviour of a cell’s ion channels (particularly those which carry IKr). Building such models requires experimental data that allows both the selection of appropriate model structures and the inference of model parameters. Recently, short “information-rich” experimental designs have been developed, allowing cell-specific models to be fitted. Here, new experimental designs can be specified, which allow the collection of new data under previously unseen IKr dynamics. The resulting data promise to improve models of the gating dynamics of IKr, improve our understanding of cardiac electrophysiology as a whole, and improve the risk-classification of new drugs. In this thesis, we introduce the methods necessary for the fitting and validation of cell-specific mathematical models of IKr using a diverse ensemble of information-rich experimental designs. This approach allows us to produce empirical quantifications of predictive uncertainty and permits the comparison of literature models in terms of their predictive accuracy and the variability of parameter estimates across cells. Whilst some models produce more accurate predictions than others, a certain amount of model discrepancy seems unavoidable. Our results suggest that this discrepancy is caused, in part, by the presence of experimental artefact effects, which, when unaccounted for, confound our parameter estimates, contributing appreciably to the apparent cell-to-cell variability of parameters relating to the kinetics of channel gating. Moreover, we demonstrate that our broadly applicable multiprotocol approach allows for thorough validation of our models, a realistic quantification of predictive uncertainty, and the selection of suitable mathematical models. 2025-07-31 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/80409/1/jshuttleworth_thesis_final_w_ack.pdf Shuttleworth, Joseph George (2025) Experimental design for discrepant models: selecting mechanistic models of IKr through informative experiments. PhD thesis, University of Nottingham. medicine mathematical modelling biomathemmatics electrophysiology |
| spellingShingle | medicine mathematical modelling biomathemmatics electrophysiology Shuttleworth, Joseph George Experimental design for discrepant models: selecting mechanistic models of IKr through informative experiments |
| title | Experimental design for discrepant models: selecting mechanistic models of IKr through informative experiments |
| title_full | Experimental design for discrepant models: selecting mechanistic models of IKr through informative experiments |
| title_fullStr | Experimental design for discrepant models: selecting mechanistic models of IKr through informative experiments |
| title_full_unstemmed | Experimental design for discrepant models: selecting mechanistic models of IKr through informative experiments |
| title_short | Experimental design for discrepant models: selecting mechanistic models of IKr through informative experiments |
| title_sort | experimental design for discrepant models: selecting mechanistic models of ikr through informative experiments |
| topic | medicine mathematical modelling biomathemmatics electrophysiology |
| url | https://eprints.nottingham.ac.uk/80409/ |