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

甲状腺激素对胎儿和婴儿的正常大脑发育，以及儿童和青少年的正常认知功能，正常生长和青春期至关重要。婴儿和儿童的甲状腺疾病（先天性和后天性甲状腺功能亢进或减退）的治疗很困难。首先，必须根据临床经验仔细选择初始剂量。其次，在甲状腺激素达到生理平衡后，需要根据青春期和青春期的年龄和甲状腺功能持续调整个体剂量，以维持甲状腺功能正常。为了减轻负面神经和发育结局（如认知障碍）的风险，必须在新生儿、婴儿和甲状腺功能减退或亢进儿童中建立最佳的个性化给药方案，并不断进行微调。将开发基于群体药代动力学/药效学（PKPD）原理的动态数学模型，其中包含个体协变量效应和来自最优控制理论的模型预测控制算法，并将其应用于不同医院的回顾性纵向疾病测量。开发的模型和算法将根据本项目期间收集的前瞻性数据进行验证。这将允许预测将甲状腺激素维持在适当参考范围内的最佳个性化给药策略。一般来说，计算婴儿和儿童最佳个性化给药的模型和算法是优化长期神经学结果并因此提高学校和专业教育表现以及提高儿科患者及其父母生活质量的医学必需品。开发的最佳控制算法将免费提供用于教育目的，并可能应用于其他疾病领域。

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. Treatment of thyroid diseases (congenital and acquired hyper- or hypothyroidism) is difficult in 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 thyroid function during adolescence and puberty is required to maintain euthyroidism. To mitigate the risk of negative neurological and developmental outcome such as cognitive impairment, it is essential to establish an optimal, personalized dosing that is continuously fine-tuned in neonates, infants and children with hypo- or hyperthyroidism. Dynamical mathematical models based on population pharmacokinetic / pharmacodynamic (PKPD) principles with individual covariate effects and model predictive control algorithms from optimal control theory will be developed and applied to retrospective longitudinal disease measurements from different hospitals. Developed models and algorithms will be validated based on prospective collected data during the duration of this project. This will allow the prediction of an optimal personalized dosing strategy that maintains thyroid hormones in an appropriate reference range. In general, models and algorithms to compute optimal personalized dosing in 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. Developed optimal control algorithms will be made freely available for educational purposes and for possible application to other disease areas.