Please use this identifier to cite or link to this item: https://doi.org/10.1098/rsif.2019.0083
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dc.titleHyperthyroidism in the personalized medicine era: The rise of mathematical optimization
dc.contributor.authorMeng F.
dc.contributor.authorLi E.
dc.contributor.authorYen P.M.
dc.contributor.authorLeow M.K.S.
dc.date.accessioned2020-10-15T04:33:05Z
dc.date.available2020-10-15T04:33:05Z
dc.date.issued2019
dc.identifier.citationMeng F., Li E., Yen P.M., Leow M.K.S. (2019). Hyperthyroidism in the personalized medicine era: The rise of mathematical optimization. Journal of the Royal Society Interface 16 (155). ScholarBank@NUS Repository. https://doi.org/10.1098/rsif.2019.0083
dc.identifier.issn1742-5689
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/177505
dc.description.abstractThyroid over-activity or hyperthyroidism constitutes a significant morbidity afflicting the world. The current medical practice of dose titration of antithyroid drug (ATD) treatment for hyperthyroidism is relatively archaic, being based on arbitrary and time-consuming trending of thyroid function that requires multiple clinic monitoring visits before an optimal dose is found. This prompts a re-examination into more deterministic and efficient treatment approaches in the present personalized medicine era. Our research project seeks to develop a personalized medicine model that facilitates optimal drug dosing via the titration regimen. We analysed 49 patients' data consisting of drug dosage, time period and serum free thyroxine (FT4). Ordinary differential equation modelling was applied to describe the dynamic behaviour of FT4 concentration. With each patient's data, an optimization modelwas developed to determine parameters of synthesis rate, decay rate and IC50. We derived the closed-form time- and dose-dependent solution which allowed explicit estimates of personalized predicted FT4. Our equation system involving time, drug dosage and FT4 can be solved for any variable provided the values of the other two are known. Compared against actual FT4 data within a tolerance, we demonstrated the feasibility of predicting the FT4 subsequent to any prescribed dose of ATD with favourable accuracy using the initial three to five patient-visits' data respectively. This proposed mathematical model may assist clinicians in rapid determination of optimal ATD doses within allowable prescription limits to achieve any desired FT4 within a specified treatment period to accelerate the attainment of euthyroid targets. © 2019 The Author(s) Published by the Royal Society. All rights reserved.
dc.publisherRoyal Society Publishing
dc.sourceScopus
dc.subjectAnti-thyroid drug dosing
dc.subjectGraves' disease
dc.subjectMathematical optimization
dc.subjectOrdinary differential equation modelling
dc.subjectPersonalized medicine
dc.typeArticle
dc.contributor.departmentDUKE-NUS MEDICAL SCHOOL
dc.description.doi10.1098/rsif.2019.0083
dc.description.sourcetitleJournal of the Royal Society Interface
dc.description.volume16
dc.description.issue155
dc.published.statePublished
dc.grant.fundingagencySingapore Institute for Clinical Sciences, SICS
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