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

Subject Area Pharmacology
Mathematics
Term from 2019 to 2023
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 401331681
 
Final Report Year 2022

Final Report Abstract

The overall aim of the DFG sub-project in the common SNF-DFG project was the development of computational algorithms to individualize, control and optimize treatments. These algorithms can adaptively incorporate possible changes of covariate values such as weight of patients. The problem was very challenging because i) the drug administration leads to impulsive differential equations, and ii) at the start of the treatment the individual patient parameters are unknown. To overcome the difficulties we developed an algorithmic treatment strategy which combines model predictive optimal control techniques to compute the optimal doses with extended Bayesian estimates (EBE) to calculate the individual patient parameters. The interplay between the optimization methods and the EBE steps was done in an efficient and smart way which represents the core of a patent application. In addition, the total research output of this SNF-DFG Grant led to the successful application of the follow up Grant “OptiThyDose: Intelligent Digital Decision Support Tool to Personalise Dosing for Children with Thyroid Diseases” sponsored by the Botnar Research centre for Child Health (BRCCH).

Publications

 
 

Additional Information

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