Influence of the dosing interval on prolactin release after remoxipride

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.

Understanding the Behavior of Systems Pharmacology Models Using Mathematical Analysis of Differential Equations: Prolactin Modeling as a Case Study

In this tutorial, we introduce basic concepts in dynamical systems analysis, such as phase‐planes, stability, and bifurcation theory, useful for dissecting the behavior of complex and nonlinear models. A precursor‐pool model with positive feedback is used to demonstrate the power of mathematical analysis. This model is nonlinear and exhibits multiple steady states, the stability of which is analyzed. The analysis offers insight into model behavior and suggests useful parameter regions, which simulations alone could not.

The mastermind approach to CNS drug therapy: translational prediction of human brain distribution, target site kinetics, and therapeutic effects

Despite enormous advances in CNS research, CNS disorders remain the world's leading cause of disability. This accounts for more hospitalizations and prolonged care than almost all other diseases combined, and indicates a high unmet need for good CNS drugs and drug therapies.Following dosing, not only the chemical properties of the drug and blood-brain barrier (BBB) transport, but also many other processes will ultimately determine brain target site kinetics and consequently the CNS effects. The rate and extent of all these processes are regulated dynamically, and thus condition dependent. Therefore, heterogenious conditions such as species, gender, genetic background, tissue, age, diet, disease, drug treatment etc., result in considerable inter-individual and intra-individual variation, often encountered in CNS drug therapy.For effective therapy, drugs should access the CNS "at the right place, at the right time, and at the right concentration". To improve CNS therapies and drug development, details of inter-species and inter-condition variations are needed to enable target site pharmacokinetics and associated CNS effects to be translated between species and between disease states. Specifically, such studies need to include information about unbound drug concentrations which drive the effects. To date the only technique that can obtain unbound drug concentrations in brain is microdialysis. This (minimally) invasive technique cannot be readily applied to humans, and we need to rely on translational approaches to predict human brain distribution, target site kinetics, and therapeutic effects of CNS drugs.In this review the term "Mastermind approach" is introduced, for strategic and systematic CNS drug research using advanced preclinical experimental designs and mathematical modeling. In this way, knowledge can be obtained about the contributions and variability of individual processes on the causal path between drug dosing and CNS effect in animals that can be translated to the human situation. On the basis of a few advanced preclinical microdialysis based investigations it will be shown that the "Mastermind approach" has a high potential for the prediction of human CNS drug effects.

Comparison of the agonist-antagonist interaction model and the pool model for the effect of remoxipride on prolactin

AIMS

The tolerance to the prolactin response following administration of antipsychotic drugs has been modelled as a depletion of a prolactin pool (pool model) and a model where the tolerance is explained by a feedback loop including the dopamine interaction of prolactin release (agonist-antagonist interaction model, (AAI model)). The AAI model was superior to the pool model when analyzing data from clinical trials of risperidone and paliperidone. Here we evaluated the two models using the remoxipride data, designed to challenge the short-term prolactin response, from which the original pool model was built.

METHODS

The remoxipride data were collected from a study where eight healthy male subjects received two remoxipride infusions on five occasions. The intervals between the first and second dose on each occasion were 2, 8, 12, 24 and 48 h, respectively. The pool and AAI models were fitted using NONMEM.

RESULTS

According to the objective function values the pool model with a circadian rhythm function fitted the data slightly better, while the AAI model was better in describing the circadian rhythm of prolactin. Visual predictive checks revealed that the models predicted the prolactin profiles equally well.

CONCLUSIONS

According to the analysis performed here, a previous analysis of several clinical studies and literature reports on prolactin concentrations, it appears that the dopamine feedback mechanism included in the AAI model is better than the storage depletion mechanism in the pool model to estimate the bio-rhythm of prolactin time-course and the tolerance development across different populations, drugs, treatment schedules and time.

Treatment response in psychotic patients classified according to social and clinical needs, drug side effects, and previous treatment; a method to identify functional remission

BACKGROUND

Various approaches have been made over the years to classify psychotic patients according to inadequate treatment response, using terms such as treatment resistant or treatment refractory. Existing classifications have been criticized for overestimating positive symptoms; underestimating residual symptoms, negative symptoms, and side effects; or being to open for individual interpretation. The aim of this study was to present and evaluate a new method of classification according to treatment response and, thus, to identify patients in functional remission.

METHOD

A naturalistic, cross-sectional study was performed using patient interviews and information from patient files. The new classification method CANSEPT, which combines the Camberwell Assessment of Need rating scale, the Udvalg for Kliniske Undersøgelser side effect rating scale (SE), and the patient's previous treatment history (PT), was used to group the patients according to treatment response. CANSEPT was evaluated by comparison of expected and observed results.

RESULTS

In the patient population (n = 123), the patients in functional remission, as defined by CANSEPT, had higher quality of life, fewer hospitalizations, fewer psychotic symptoms, and higher rate of workers than those with the worst treatment outcome.

CONCLUSION

In the evaluation, CANSEPT showed validity in discriminating the patients of interest and was well tolerated by the patients. CANSEPT could secure inclusion of correct patients in the clinic or in research.

The differential effects of atypical antipsychotics on prolactin elevation are explained by their differential blood-brain disposition: a pharmacological analysis in rats

All atypical antipsychotics avoid extrapyramidal side-effects yet differ in their propensity to cause other side-effects, like prolactin elevation. We proposed that the atypical antipsychotics with a propensity for prolactin elevation would show a higher pituitary versus striatal D2 receptor occupancy. To investigate this hypothesis, we tested four atypical antipsychotics, two that are commonly associated with prolactin elevation (amisulpride and risperidone) and two that are less frequently associated (quetiapine and olanzapine). In particular, we calculated their ED(50) values to increase plasma prolactin and block peripheral pituitary D2 receptors to their ED(50) values to antagonize apomorphine-induced stereotypy and occupy central striatal D2 receptors. All antipsychotics dose dependently increased prolactin levels and antagonized apomorphine-induced stereotypy. However, the central to peripheral potency (ED(50) for apomorphine antagonism to ED(50) for prolactin elevation) differed remarkably across these drugs: amisulpride (21764), risperidone (14), quetiapine (10), and olanzapine (1.7). Compounds displaying a higher peripheral potency brought about higher prolactin levels for a given level of functional central antagonism. This dissociation between central and peripheral effects was explained by the differential occupancy of D2 receptors in the striatum versus in the pituitary [ratio of striatal/pituitary ED(50) values (milligram per kilogram) for D2 occupancy): amisulpride (17/0.026 = 654), risperidone (0.89/0.081 = 14), quetiapine (24/4.1 = 6), olanzapine (0.30/0.43 = 0.7). These results indicate that dissociation between central and peripheral D2 receptor occupancy is a major determinant of the degree of prolactin elevation observed at therapeutic doses.

Pharmacology of the atypical antipsychotic remoxipride, a dopamine D2 receptor antagonist

Remoxipride is a substituted benzamide that acts as a weak but very selective antagonist of dopamine D2 receptors. It was introduced by Astra (Roxiam) at the end of the eighties and was prescribed as an atypical antipsychotic. This article reviews its putative selective effects on mesolimbic versus nigrostriatal dopaminergic systems. In animals, remoxipride has minimal cataleptic effects at doses that block dopamine agonist-induced hyperactivity. These findings are predictive of antipsychotic activity with a low likelihood of extrapyramidal symptoms. Remoxipride also appears to be effective in more recent animal models of schizophrenia, such as latent inhibition or prepulse inhibition. In clinical studies, remoxipride shows a relatively low incidence of extrapyramidal side effects and its effects on prolactin release are short-lasting and generally mild. The clinical efficacy of remoxipride is similar to that of haloperidol or chlorpromazine. Although its clinical use was severely restricted in 1993, due to reports of aplastic anemia in some patients receiving remoxipride, this drug has been found to exhibit relatively high selectivity for dopamine D2 receptors making remoxipride an interesting tool for neurochemical and behavioral studies.