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345 results on '"Proost, Johannes H."'

9. A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations

Author

Yamamoto, Yumi, Välitalo, Pyry A., van den Berg, Dirk-Jan, Hartman, Robin, van den Brink, Willem, Wong, Yin Cheong, Huntjens, Dymphy R., Proost, Johannes H., Vermeulen, An, Krauwinkel, Walter, Bakshi, Suruchi, Aranzana-Climent, Vincent, Marchand, Sandrine, Dahyot-Fizelier, Claire, Couet, William, Danhof, Meindert, van Hasselt, Johan G. C., and de Lange, Elizabeth C. M.

Published
2017
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33. Intracellular Delivery of the p38 Mitogen-Activated Protein Kinase Inhibitor SB202190 [4-(4-Fluorophenyl)-2-(4-hydroxyphenyl)-5-(4-pyridyl)1 H-imidazole] in Renal Tubular Cells: A Novel Strategy to Treat Renal Fibrosis

Author

Prakash, Jai, Sandovici, Maria, Saluja, Vinay, Lacombe, Marie, Schaapveld, Roel Q.J., de Borst, Martin H., van Goor, Harry, Henning, Robert H., Proost, Johannes H., Moolenaar, Frits, Këri, György, Meijer, Dirk K.F., Poelstra, Klaas, and Kok, Robbert J.

Published
2006
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41. Predicting Drug Concentration‐Time Profiles in Multiple CNS Compartments Using a Comprehensive Physiologically‐Based Pharmacokinetic Model

Author

Yamamoto, Yumi, Välitalo, Pyry A., Huntjens, Dymphy R., Proost, Johannes H., Vermeulen, An, Krauwinkel, Walter, Beukers, Margot W., van den Berg, Dirk‐Jan, Hartman, Robin, Wong, Yin Cheong, Danhof, Meindert, van Hasselt, John G. C., and de Lange, Elizabeth C. M.

Subjects
Brain Chemistry, Central Nervous System, Small Molecule Libraries, Plasma, Animals, Original Article, Tissue Distribution, Original Articles, Models, Biological, Cerebrospinal Fluid, Rats
Abstract

Drug development targeting the central nervous system (CNS) is challenging due to poor predictability of drug concentrations in various CNS compartments. We developed a generic physiologically based pharmacokinetic (PBPK) model for prediction of drug concentrations in physiologically relevant CNS compartments. System‐specific and drug‐specific model parameters were derived from literature and in silico predictions. The model was validated using detailed concentration‐time profiles from 10 drugs in rat plasma, brain extracellular fluid, 2 cerebrospinal fluid sites, and total brain tissue. These drugs, all small molecules, were selected to cover a wide range of physicochemical properties. The concentration‐time profiles for these drugs were adequately predicted across the CNS compartments (symmetric mean absolute percentage error for the model prediction was

Published
2017

50. Modeling of prolactin response following dopamine Dreceptor antagonists in rats: can it be translated to clinical dosing?

Author

Taneja, Amit, Vermeulen, An, Huntjens, Dymphy R.H., Danhof, Meindert, De Lange, Elizabeth C.M., Proost, Johannes H., Nanomedicine & Drug Targeting, Biopharmaceuticals, Discovery, Design and Delivery (BDDD), Critical care, Anesthesiology, Peri-operative and Emergency medicine (CAPE), and Center for Liver, Digestive and Metabolic Diseases (CLDM)

Subjects
REMOXIPRIDE, RELEASE, PHARMACOKINETICS, SCHIZOPHRENIA, Journal Article, RISPERIDONE, OCCUPANCY, SYSTEMS PHARMACOLOGY, EXTRAPOLATION, HUMANS, IN-VITRO
Abstract

Prolactin release is a side effect of antipsychotic therapy with dopamine antagonists, observed in rats as well as humans. We examined whether two semimechanistic models could describe prolactin response in rats and subsequently be translated to predict pituitary dopamine D2receptor occupancy and plasma prolactin concentrations in humans following administration of paliperidone or remoxipride. Data on male Wistar rats receiving single or multiple doses of risperidone, paliperidone, or remoxipride was described by two semimechanistic models, the precursor pool model and the agonist-antagonist interaction model. Using interspecies scaling approaches, human D2receptor occupancy and plasma prolactin concentrations were predicted for a range of clinical paliperidone and remoxipride doses. The predictions were compared with corresponding observations described in literature as well as with predictions from published models developed on human data. The pool model could predict D2receptor occupancy and prolactin response in humans following single doses of paliperidone and remoxipride. Tolerance of prolactin release was predicted following multiple doses. The interaction model underpredicted both D2receptor occupancy and prolactin response. Prolactin elevation may be deployed as a suitable biomarker for interspecies translation and can inform the clinical safe and effective dose range of antipsychotic drugs. While the pool model was more predictive than the interaction model, it overpredicted tolerance on multiple dosing. Shortcomings of the translations reflect the need for better mechanistic models.

Published
2017

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