@article{GomezHartung2018,
  author    = {Gomez, Christophe and Hartung, Niklas},
  title     = {Stochastic and deterministic models for the metastatic emission process},
  series = {Cancer Systems Biology},
  volume    = {1711},
  journal   = {Cancer Systems Biology},
  publisher = {Humana Press Inc.},
  address   = {Totowa},
  isbn      = {978-1-4939-7493-1},
  issn      = {1064-3745},
  doi       = {10.1007/978-1-4939-7493-1_10},
  pages     = {193 -- 224},
  year      = {2018},
  abstract  = {Although the detection of metastases radically changes prognosis of and treatment decisions for a cancer patient, clinically undetectable micrometastases hamper a consistent classification into localized or metastatic disease. This chapter discusses mathematical modeling efforts that could help to estimate the metastatic risk in such a situation. We focus on two approaches: (1) a stochastic framework describing metastatic emission events at random times, formalized via Poisson processes, and (2) a deterministic framework describing the micrometastatic state through a size-structured density function in a partial differential equation model. Three aspects are addressed in this chapter. First, a motivation for the Poisson process framework is presented and modeling hypotheses and mechanisms are introduced. Second, we extend the Poisson model to account for secondary metastatic emission. Third, we highlight an inherent crosslink between the stochastic and deterministic frameworks and discuss its implications. For increased accessibility the chapter is split into an informal presentation of the results using a minimum of mathematical formalism and a rigorous mathematical treatment for more theoretically interested readers.},
  language  = {en}
}
@article{MelinParraGuillenHartungetal.2018,
  author    = {Melin, Johanna and Parra-Guillen, Zinnia Patricia and Hartung, Niklas and Huisinga, Wilhelm and Ross, Richard J. and Whitaker, Martin J. and Kloft, Charlotte},
  title     = {Predicting Cortisol Exposure from Paediatric Hydrocortisone Formulation Using a Semi-Mechanistic Pharmacokinetic Model Established in Healthy Adults},
  series = {Clinical Pharmacokinetics},
  volume    = {57},
  journal   = {Clinical Pharmacokinetics},
  number    = {4},
  publisher = {Springer},
  address   = {Northcote},
  issn      = {0312-5963},
  doi       = {10.1007/s40262-017-0575-8},
  pages     = {515 -- 527},
  year      = {2018},
  abstract  = {Background and objective Optimisation of hydrocortisone replacement therapy in children is challenging as there is currently no licensed formulation and dose in Europe for children under 6 years of age. In addition, hydrocortisone has non-linear pharmacokinetics caused by saturable plasma protein binding. A paediatric hydrocortisone formulation, Infacort (R) oral hydrocortisone granules with taste masking, has therefore been developed. The objective of this study was to establish a population pharmacokinetic model based on studies in healthy adult volunteers to predict hydrocortisone exposure in paediatric patients with adrenal insufficiency. Methods Cortisol and binding protein concentrations were evaluated in the absence and presence of dexamethasone in healthy volunteers (n = 30). Dexamethasone was used to suppress endogenous cortisol concentrations prior to and after single doses of 0.5, 2, 5 and 10 mg of Infacort (R) or 20 mg of Infacort (R)/hydrocortisone tablet/hydrocortisone intravenously. A plasma protein binding model was established using unbound and total cortisol concentrations, and sequentially integrated into the pharmacokinetic model. Results Both specific (non-linear) and non-specific (linear) protein binding were included in the cortisol binding model. A two-compartment disposition model with saturable absorption and constant endogenous cortisol baseline (Baseline (cort),15.5 nmol/L) described the data accurately. The predicted cortisol exposure for a given dose varied considerably within a small body weight range in individuals weighing < 20 kg. Conclusions Our semi-mechanistic population pharmacokinetic model for hydrocortisone captures the complex pharmacokinetics of hydrocortisone in a simplified but comprehensive framework. The predicted cortisol exposure indicated the importance of defining an accurate hydrocortisone dose to mimic physiological concentrations for neonates and infants weighing < 20 kg.},
  language  = {en}
}
@misc{EhmannZollerMinichmayretal.2018,
  author    = {Ehmann, Lisa and Zoller, Michael and Minichmayr, Iris K. and Schmitt, Maximilian V. and Hartung, Niklas and Huisinga, Wilhelm and Zander, Johannes and Kloft, Charlotte},
  title     = {Development of a tool to identify intensive care patients at risk of meropenem therapy failure},
  series = {International Journal of Clinical Pharmacy},
  volume    = {40},
  journal   = {International Journal of Clinical Pharmacy},
  number    = {1},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {2210-7703},
  pages     = {317 -- 317},
  year      = {2018},
  language  = {en}
}