Projects & Collaborations

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LeukemiaCort: A Swiss prospective multicenter longitudinal assessment of hypothalamic-pituitary-adrenal axis suppression after glucocorticoid therapy for leukemia and lymphoblastic lymphoma in children. An explorative study.

Research Project | 4 Project Members

Glucocorticoid therapy is an important component of the treatment regimen for childhood acute lymphoblastic leukaemia and lymphoblastic lymphoma by inducing apoptosis of lymphoblastic cells. However, the use of supraphysiological doses of glucocorticoids can lead to hypothalamic-pituitary-adrenal axis suppression. This suppression can result in a reduced cortisol response, leading to impaired stress response and inadequate host defence against infections, which can ultimately result in morbidity and mortality. To date, there is insufficient high-quality research to inform evidence-based guidelines for glucocorticoid replacement therapy in this populatioon.

Hence, in this prospective multicenter study, we aim to analyze the patterns of suppression of the hypothalamic-pituitary-adrenal axis suppression in children receiving glucocorticoid therapy for acute lymphoblastic leukaemia and lymphoblastic lymphoma.

OptiThyDose: Intelligent Digital Decision Support Tool to Personalise Dosing for Children with Thyroid Diseases

Research Project | 8 Project Members

Thyroid hormones are critical for normal brain development, growth, and puberty. Hypo-/hyperthyroidism manifests at birth or during childhood. Thus, prompt, adequate medical treatment is crucial to protect cognitive and physiological development in affected children. Current guidelines recommend standard dosing regimens, despite a wide spectrum of disease variability in terms of severity, activity and receptivity. Over- and under-dosing is frequent, making a decision support tool for optimal and fine-tuned personalised dosing essential for adequate medical care.

The aim of this project is to provide personalised treatment plans for children with a thyroid disease. The consortium will build upon their existing work on an intelligent decision support tool that optimises and computes personalised treatment dosing. The researchers will use computer models that consider individual disease characteristics obtained from observational studies in combination with optimal dosing algorithms to develop an intelligent clinical decision support tool “OptiThyDose” to personalise and optimize dosing regimens. OptiThyDose iteratively computes individual dose regimens based on the patient's age, weight and disease severity to restore and maintain thyroid hormone balance.

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

Research Project | 6 Project Members

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.