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The THY-MOD Study - Personalized Dosing in Children with Hyper- or Hypothyroidism Computed by Mathematical Modeling

Research Project
 | 
01.06.2019
 - 30.11.2021

Thyroid hormones are essential for normal brain development in the foetus and the infant, and for normal cognitive functions, normal growth and puberty in children and adolescents. However, treatment of thyroid diseases (congenital and acquired hyper- or hypothyroidism) is difficult in neonate, infants and children. First, a carefully selected initial dose based on clinical experience is necessary. Second, after reaching a physiological balance of thyroid hormones, a continuous adjustment of the individual dose depending on age and severity of thyroid disease is required to maintain euthyroidism during childhood and adolescence. To mitigate the risk of negative neurological and developmental outcome such as cognitive impairment, it is essential to establish an optimal, personalized dosing strategy that is continuously fine-tuned to account for specific needs in neonates, infants and children with hyper- or hypothyroidism. Dynamical mathematical models based on population pharmacokinetic / pharmacodynamic (PKPD) principles with individual covariate effects together with algorithms from optimal control theory will be developed and applied to retrospective longitudinal disease measurements from 5 Swiss paediatric hospitals. Developed models and algorithms will be validated based on prospective collected data in a large international paediatric thyroid centre. This will allow the prediction of an optimal personalized dosing strategy that maintains thyroid hormones in the normal reference range. Models and algorithms to compute optimal personalized dosing in neonates, infants and children are a medical necessity to optimize long-term neurological outcome and consequently enhance performance in school and professional education, and to increase life quality of paediatric patients and their parents.

Funding

The THY-MOD Study - Personalized Dosing in Children with Hyper- or Hypothyroidism Computed by Mathematical Modeling

SNF Schweizerischer Nationalfonds, 06.2019-11.2021 (30)
CI : Szinnai, Gabor.

Publications

Bachmann, Freya et al. (2023) ‘Computing optimal drug dosing with OptiDose: implementation in NONMEM’, Journal of Pharmacokinetics and Pharmacodynamics, 50, pp. 173–188. Available at: https://doi.org/10.1007/s10928-022-09840-w.

URLs
URLs

Steffens, Britta et al. (2023) ‘Clinically practical pharmacometrics computer model to evaluate and personalize pharmacotherapy in pediatric rare diseases: application to Graves” disease’, Frontiers in Medicine, 10. Available at: https://doi.org/10.3389/fmed.2023.1099470.

URLs
URLs

Koch, Gilbert et al. (2021) ‘Modeling of levothyroxine in newborns and infants with congenital hypothyroidism: challenges and opportunities of a rare disease multi-center study’, Journal of Pharmacokinetics and Pharmacodynamics, 48, pp. 711–723. Available at: https://doi.org/10.1007/s10928-021-09765-w.

URLs
URLs

Bachmann F et al. (2021) ‘OptiDose: Computing the individualized optimal drug dosing regimen using optimal control’, J of Optimization Theory and Applications, (189), pp. 45–65.

Members (6)

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Gabor Szinnai

Co-Investigator
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Gilbert Koch

Principal Investigator
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Marc Pfister

Co-Investigator
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Daniel Konrad

Collaborator Kinderspital Zürich
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Christa Flück

Collaborator Inselspital Bern
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Dagmar L'allemand

Collaborator Ostschweizer Kinderspital