Toward the prediction of CNS drug-effect profiles in physiological and pathological conditions using microdialysis and mechanism-based pharmacokinetic-pharmacodynamic modeling

Lange, Elizabeth C. M. de; Ravenstijn, Paulien; Groenendaal, Dorien; Steeg, Tamara J. van

doi:10.1208/aapsj070354

Cited by 88 publications

(48 citation statements)

References 93 publications

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“…To that end, it is important to connect such data to information on drug distribution to target sites, target binding kinetics, signal trans- [ 88] duction, and homeostatic feedback mechanisms. Such insight is obtained by integration of data obtained from multilevel studies, that is, measurement of different biomarker types in a time-dependent manner [19,71,91,92,93]. In all cases, the experimental approach should be such that a distinction can be made between drug-specific and system-specific properties, to allow for scaling between drugs and/or scaling between species [61].…”

Section: Biomarkers Of Drug Effects and Diseasementioning

confidence: 99%

Novel CNS drug discovery and development approach: model-based integration to predict neuro-pharmacokinetics and pharmacodynamics

Lange

Brink

Yamamoto

et al. 2017

Expert Opinion on Drug Discovery

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Introduction: CNS drug development has been hampered by inadequate consideration of CNS pharmacokinetic (PK), pharmacodynamics (PD) and disease complexity (reductionist approach). Improvement is required via integrative model-based approaches. Areas covered: The authors summarize factors that have played a role in the high attrition rate of CNS compounds. Recent advances in CNS research and drug discovery are presented, especially with regard to assessment of relevant neuro-PK parameters. Suggestions for further improvements are also discussed. Expert opinion: Understanding time-and condition dependent interrelationships between neuro-PK and neuro-PD processes is key to predictions in different conditions. As a first screen, it is suggested to use in silico/in vitro derived molecular properties of candidate compounds and predict concentrationtime profiles of compounds in multiple compartments of the human CNS, using time-course based physiology-based (PB) PK models. Then, for selected compounds, one can include in vitro drug-target binding kinetics to predict target occupancy (TO)-time profiles in humans. This will improve neuro-PD prediction. Furthermore, a pharmaco-omics approach is suggested, providing multilevel and paralleled data on systems processes from individuals in a systems-wide manner. Thus, clinical trials will be better informed, using fewer animals, while also, needing fewer individuals and samples per individual for proof of concept in humans. ARTICLE HISTORY

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Section: Biomarkers Of Drug Effects and Diseasementioning

confidence: 99%

Novel CNS drug discovery and development approach: model-based integration to predict neuro-pharmacokinetics and pharmacodynamics

Lange

Brink

Yamamoto

et al. 2017

Expert Opinion on Drug Discovery

Self Cite

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show abstract

“…13 μD has found its most important role, perhaps, in the measurement of compounds in the brain. These studies have examined not only endogenous compounds (eg, neurotransmitters) but also, in the past several years, the drug distribution to specifi c regions of the central nervous system (CNS).…”

Section: E50mentioning

confidence: 99%

AAPS-FDA workshop white paper: Microdialysis principles, application, and regulatory perspectives report from the Joint AAPS-FDA Workshop, November 4–5, 2005, Nashville, TN

Chaurasia

Müller

Bashaw

et al. 2007

AAPS J

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“…biomarker types in a time-dependent manner and advanced pharmacokinetic/pharmacodynamic (PK/PD) modeling (5)(6)(7).…”

Section: Introductionmentioning

confidence: 99%

Revealing the Neuroendocrine Response After Remoxipride Treatment Using Multi-Biomarker Discovery and Quantifying It by PK/PD Modeling

Brink

Wong

Gülave

et al. 2016

AAPS J

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Abstract.To reveal unknown and potentially important mechanisms of drug action, multibiomarker discovery approaches are increasingly used. Time-course relationships between drug action and multi-biomarker profiles, however, are typically missing, while such relationships will provide increased insight in the underlying body processes. The aim of this study was to investigate the effect of the dopamine D2 antagonist remoxipride on the neuroendocrine system. Different doses of remoxipride (0, 0.7, 5.2, or 14 mg/kg) were administered to rats by intravenous infusion. Serial brain extracellular fluid (brainECF) and plasma samples were collected and analyzed for remoxipride pharmacokinetics (PK). Plasma samples were analyzed for concentrations of the eight pituitary-related hormones as a function of time. A Mann-Whitney test was used to identify the responding hormones, which were further analyzed by pharmacokinetic/ pharmacodynamic (PK/PD) modeling. A three-compartment PK model adequately described remoxipride PK in plasma and brainECF. Not only plasma PRL, but also adrenocorticotrophic hormone (ACTH) concentrations were increased, the latter especially at higher concentrations of remoxipride. Brain-derived neurotropic factor (BDNF), follicle stimulating hormone (FSH), growth hormone (GH), luteinizing hormone (LH), and thyroid stimulating hormones (TSH) did not respond to remoxipride at the tested doses, while oxytocin (OXT) measurements were below limit of quantification. Precursor pool models were linked to brainECF remoxipride PK by E max drug effect models, which could accurately describe the PRL and ACTH responses. To conclude, this study shows how a multi-biomarker identification approach combined with PK/PD modeling can reveal and quantify a neuroendocrine multi-biomarker response for single drug action.

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Toward the prediction of CNS drug-effect profiles in physiological and pathological conditions using microdialysis and mechanism-based pharmacokinetic-pharmacodynamic modeling

Cited by 88 publications

References 93 publications

Novel CNS drug discovery and development approach: model-based integration to predict neuro-pharmacokinetics and pharmacodynamics

Novel CNS drug discovery and development approach: model-based integration to predict neuro-pharmacokinetics and pharmacodynamics

AAPS-FDA workshop white paper: Microdialysis principles, application, and regulatory perspectives report from the Joint AAPS-FDA Workshop, November 4–5, 2005, Nashville, TN

Revealing the Neuroendocrine Response After Remoxipride Treatment Using Multi-Biomarker Discovery and Quantifying It by PK/PD Modeling

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