2010 - Berlin - Germany

PAGE 2010: Clinical Applications
Klas Petersson

Predictions of in vivo prolactin levels from in vitro Ki values of D2 receptor antagonists using an agonist-antagonist interaction model.

Petersson KJF (1), Vermeulen AM (2), Friberg LE (1)

(1) Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden (2) Advanced PK/PD Modeling and Simulation, Johnson & Johnson Pharmaceutical Research and Development, a Division of Janssen Pharmaceutica N.V., Beerse, Belgium

Objectives: Treatment of schizophrenia has traditionally been focused on antagonizing the central D2-receptor and sufficient central D2 occupancy is a prerequisite for treatment efficacy. However, antagonism of peripheral and central dopamine D2-receptors does result in a range of other, unwanted effects such as elevated serum prolactin levels and extrapyramidal side effects. Prolactin release from the anterior pituitary is tonically inhibited by endogenous dopamine occupying D2-receptors. Antipsychotic treatment with D2-receptor antagonists abolishes this inhibition and as a result serum prolactin levels are elevated. The drug-induced elevation in prolactin levels has been shown to be correlated with the affinity of the drug, where older, high-affinity drugs show a higher prolactin response than newer drugs with lower affinities.

A model including this agonist-antagonist interaction between endogenous dopamine and drug, in addition to the diurnal rhythm of prolactin release, was developed earlier and used to describe the prolactin-time profiles following risperidone and paliperidone treatment [1]. The model has also been successfully applied to remoxipride data [2]. In both these analyses, the ratios of the estimated Ki values to the Ki values determined from in vitro assays on D2-recpeptor affinity were approximately the same.

The aim of this work was to apply the agonist-antagonist interaction model to new data sets from a number of other compounds, spanning a range of D2-receptor affinities and varying data density and compare model-estimates of Ki to those determined in vitro. If the model is successful in describing prolactin release for a range of drugs with similar system-related parameters estimated across data sets, and there is a relationship between in vitro Ki and model-estimated Ki, the model may allow prediction of prolactin-time profiles early in development using drug D2-receptor affinities as determined in vitro. This could eventually lead to optimizing dose selection early in development.

Methods: Rich pharmacokinetic and prolactin Phase I data from 2 compounds (A and B) and sparse olanzapine Phase III comparator data from risperidone and paliperidone trials were included in this analysis, in addition to the risperidone and paliperidone data the model was developed from. The in vitro Ki values for these compounds ranged from 0.9 ng/mL for risperidone/paliperidone to 62 ng/mL for remoxipride.

In total 2132 individuals and 16291 prolactin observations were analysed using NONMEM. Phase I data originated from both single ascending and multiple ascending dose trials with one or more full PK profiles as well as one or more full 24 hour prolactin profile(s). In the sparser olanzapine data set prolactin was sampled pre-dose at baseline, day 14, day 35 and end of trial across the seven week trial period. Individual PK profiles derived from developed PK models were used to drive the prolactin model.

The agonist-antagonist interaction model was applied to each dataset independently, on the one hand with the system-specific parameters fixed to published values, estimating only the drug-dopamine interaction, and on the other hand re-estimating all parameters for the rich data sets. The comparison between the predicted in vivo prolactin response using in vitro determined Ki and Ki estimated by the model was made with the elevation expressed as the 24 hour prolactin AUC after the first dose and at steady state.

Results: The semi-mechanistic model was successful in describing the prolactin data from all trials. There was a good correlation between the Ki estimated from the model using the clinical data and the Ki values determined in vitro (r2=0.91). The relative differences between in vitro Ki and estimated Ki ranged from 56% for compound A to 397% for olanzapine. These relative differences translated into predicted relative differences in prolactin elevations during 24 hours that ranged from 47% for remoxipride to 232% for olanzapine.

When re-estimating all parameters for the rich datasets, system-related parameters showed good concordance across different data sets both for prolactin and dopamine turnover as well as for the circadian rhythm.

Conclusions: The agonist-antagonist interaction model performed well over the 80-fold range in D2 affinity values investigated and was shown to estimate similar system-related parameters across the different drugs. The estimates of the in vivo derived Ki values were all less or around a factor 2 of the in vitro values, except for olanzapine where the in vivo information was sparse and may have resulted in a poor Ki estimate by the model.

For four out of five substances the estimated Ki values were higher than those determined in vitro resulting in over prediction of in vivo prolactin response. Accounting for that unbound concentrations was used in the in vitro experiments and total concentrations in vivo did however not fully account for the observed discrepancies. Affinity to other receptor systems counteracting prolactin release in vivo could be one explanation to the differences. This could possibly be corrected for by taking the intermediate step of performing animal studies. This is being investigated by applying the model to longitudinal prolactin measurements after administration of D2 - receptor antagonists in rat.

Since the typical prolactin-time profiles predicted based on in vitro values were similar to those estimated from the trials this indicates that typical prolactin-time profiles in both patients and in healthy volunteers for different dose levels may be predicted early in development based on in vitro Ki for the compound, the agonist-antagonist interaction model and its system-related parameters, and some information on PK. This could help decision making in choosing between drug candidates and dose levels, both from a safety perspective and from an efficacy perspective, as prolactin elevation is a sign of at least peripheral D2 - occupancy.

[1] Friberg et al. Clin Pharmacol Ther. 2009 Apr; 85(4):409-17
[2] Ma et al. [www.page-meeting.org/?abstract=1299]

Reference: PAGE 19 (2010) Abstr 1712 [www.page-meeting.org/?abstract=1712]
Oral Presentation: Clinical Applications