A comparison of two semi-mechanistic models for prolactin release and prediction of receptor occupancy following administration of dopamine D2 receptor antagonists in rats

Development of a non-human primate model to support CNS translational research: Demonstration with D-amphetamine exposure and dopamine response

BACKGROUND

Challenges specific to the discovery and development of candidate CNS drugs have led to implementation of various in silico, in vitro and in vivo approaches to improve the odds for commercialization of novel treatments.

NEW METHOD

Advances in analytical methodology and microdialysis probe design have enabled development of a non-human primate model capable of measuring concentrations of drugs or endogenous chemicals in brain extracellular fluid (ECF) and cerebrospinal fluid (CSF). Linking these to population modeling reduces animal numbers to support predictive translational sciences in primates. Application to measure D-amphetamine exposure and dopamine response in ECF and CSF demonstrate the approach.

RESULTS

Following a 0.1 mg/kg intravenous bolus dose of D-amphetamine, a population approach was used to build a plasma compartmental-based and brain physiologic-based pharmacokinetic (PK) model linking drug concentrations in plasma to brain ECF and CSF concentrations. Dopamine was also measured in brain ECF. The PK model was used to simulate the relationship between D-amphetamine exposure and dopamine response in ECF over a wide dose range.

COMPARISONS WITH EXISTING METHODS

Ability to co-sample and measure drug and endogenous substances in blood, brain ECF and/or CSF, coupled with population modeling, provides an in vivo approach to evaluate CNS drug penetration and effect in non-human primates.

CONCLUSIONS

A method to measure drug and endogenous neurochemicals in non-human primate brain fluids is demonstrated. Its basis in non-human primates merits improved confidence regarding predictions of drug exposure and target engagement in human CNS.

Fingerprints of CNS drug effects: a plasma neuroendocrine reflection of D2 receptor activation using multi-biomarker pharmacokinetic/pharmacodynamic modelling

BACKGROUND AND PURPOSE

Because biological systems behave as networks, multi-biomarker approaches increasingly replace single biomarker approaches in drug development. To improve the mechanistic insights into CNS drug effects, a plasma neuroendocrine fingerprint was identified using multi-biomarker pharmacokinetic/pharmacodynamic (PK/PD) modelling. Short- and long-term D2 receptor activation was evaluated using quinpirole as a paradigm compound.

EXPERIMENTAL APPROACH

Rats received 0, 0.17 or 0.86 mg·kg-1 of the D2 agonist quinpirole i.v. Quinpirole concentrations in plasma and brain extracellular fluid (brainECF ), as well as plasma concentrations of 13 hormones and neuropeptides, were measured. Experiments were performed at day 1 and repeated after 7-day s.c. drug administration. PK/PD modelling was applied to identify the in vivo concentration-effect relations and neuroendocrine dynamics.

KEY RESULTS

The quinpirole pharmacokinetics were adequately described by a two-compartment model with an unbound brainECF -to-plasma concentration ratio of 5. The release of adenocorticotropic hormone (ACTH), growth hormone, prolactin and thyroid-stimulating hormone (TSH) from the pituitary was influenced. Except for ACTH, D2 receptor expression levels on the pituitary hormone-releasing cells predicted the concentration-effect relationship differences. Baseline levels (ACTH, prolactin, TSH), hormone release (ACTH) and potency (TSH) changed with treatment duration.

CONCLUSIONS AND IMPLICATIONS

The integrated multi-biomarker PK/PD approach revealed a fingerprint reflecting D2 receptor activation. This forms the conceptual basis for in vivo evaluation of on- and off-target CNS drug effects. The effect of treatment duration is highly relevant given the long-term use of D2 agonists in clinical practice. Further development towards quantitative systems pharmacology models will eventually facilitate mechanistic drug development.

Schizophrenia: synthetic strategies and recent advances in drug design

Schizophrenia is a complex and unpredictable mental disorder which affects several domains of cognition and behaviour. It is a heterogeneous illness characterised by positive, negative, and cognitive symptoms, often accompanied by signs of depression. In this tutorial review, we discuss recent progress in understanding the target sites and mechanisms of action of second-generation antipsychotic drugs. Progress in identifying and defining target sites has been accelerated recently by advances in neuroscience, and newly developed agents that regulate signalling by the main excitatory neurotransmitters in the brain are surveyed. Examples of novel molecules for the treatment of schizophrenia in preclinical and clinical development and their industrial sponsors are highlighted.

Modeling of prolactin response following dopamine D2 receptor antagonists in rats: can it be translated to clinical dosing?

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 D₂ receptor 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 D₂ receptor 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 D₂ receptor 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 D₂ receptor 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.

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

To reveal unknown and potentially important mechanisms of drug action, multi-biomarker 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.

Summary data of potency and parameter information from semi-mechanistic PKPD modeling of prolactin release following administration of the dopamine D2 receptor antagonists risperidone, paliperidone and remoxipride in rats

We provide the reader with relevant data related to our recently published paper, comparing two mathematical models to describe prolactin turnover in rats following one or two doses of the dopamine D2 receptor antagonists risperidone, paliperidone and remoxipride, "A comparison of two semi-mechanistic models for prolactin release and prediction of receptor occupancy following administration of dopamine D2 receptor antagonists in rats" (Taneja et al., 2016) [1]. All information is tabulated. Summary level data on the in vitro potencies and the physicochemical properties is presented in Table 1. Model parameters required to explore the precursor pool model are presented in Table 2. In Table 3, estimated parameter comparisons for both models are presented, when separate potencies are estimated for risperidone and paliperidone, as compared to a common potency for both drugs. In Table 4, parameter estimates are compared when the drug effect is parameterized in terms of drug concentration or receptor occupancy.