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

Comparison of theagonist-antagonistinteraction model and thepool model for the effect ofremoxipride on prolactinGuangli Ma,1 Lena E. Friberg,1 Gunilla Movin-Osswald2 &Mats O. Karlsson1

1Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden and 2R&D

AstraZeneca, Södertälje, Sweden

CorrespondenceProfessor Mats Karlsson, Department ofPharmaceutical Biosciences, Box 591,Uppsala University, SE-751 24 Uppsala,Sweden.Tel.: + 46 1 8471 4105Fax: + 46 1 8471 4003E-mail: mats.karlsson@farmbio.uu.se----------------------------------------------------------------------

Keywordsagonist-antagonist interaction model,circadian rhythm, pool model, prolactin,remoxipride, tolerance----------------------------------------------------------------------

Received15 June 2009

Accepted15 June 2010

WHAT IS ALREADY KNOWN ABOUTTHIS SUBJECT• Prolactin response is a common side effect of

antipsychotic drugs.• The pool model was proposed to describe the

effect of remoxipride on prolactin.• The agonist-antagonist interaction (AAI)

model, which incorporated adopamine-prolactin feedback loop mechanismand circadian rhythm, was used to depict theeffects of risperidone and paliperidone onprolactin.

• The pool model could not characterizeprolactin response in clinical studies ofrisperidone and paliperdone.

WHAT THIS STUDY ADDS• The AAI model and the pool model were both

reconstructed based on the remoxipride dataset from which the original pool model wasbuilt. The pool model was extended with acircadian rhythm component which wasemployed in the AAI model.

• The objective function values calculated byNONMEM revealed that the pool model with acircadian rhythm component best fitted thedata. However, predictive checks of bothmodels were satisfactory and the AAI modelwas superior in describing the circadianrhythm in healthy male volunteers whencompared with earlier studies.

• This study shows that the AAI model wassuperior as it worked well across differentpopulations, study designs and drugs.

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

METHODSThe remoxipride data were collected from a study where eight healthymale subjects received two remoxipride infusions on five occasions.The intervals between the first and second dose on each occasion were2, 8, 12, 24 and 48 h, respectively. The pool and AAI models were fittedusing NONMEM.

RESULTSAccording to the objective function values the pool model with acircadian rhythm function fitted the data slightly better, while the AAImodel was better in describing the circadian rhythm of prolactin. Visualpredictive checks revealed that the models predicted the prolactinprofiles equally well.

CONCLUSIONSAccording to the analysis performed here, a previous analysis of severalclinical studies and literature reports on prolactin concentrations, itappears that the dopamine feedback mechanism included in the AAImodel is better than the storage depletion mechanism in the poolmodel to estimate the bio-rhythm of prolactin time-course and thetolerance development across different populations, drugs, treatmentschedules and time.

British Journal of ClinicalPharmacology

DOI:10.1111/j.1365-2125.2010.03758.x

Br J Clin Pharmacol / 70:6 / 815–824 / 815© 2010 The AuthorsBritish Journal of Clinical Pharmacology © 2010 The British Pharmacological Society

Introduction

A group of unwanted side effects of antipsychotic drugs,such as galactorrhoea, mammary gland development andsexual dysfunction, is caused by prolactin response. Prolac-tin release is regulated by dopamine concentration. Themechanism behind these side effects is that antipsychoticdrugs block not only the central dopamine2 (D2) receptorsin the brain but also the peripheral D2 receptors in theanterior pituitary.Therefore, the inhibition of dopamine onprolactin release from lactotrophs in the adenohypophysisis suppressed by antipsychotic drugs [1].

Pharmacokinetic and pharmacodynamic (PK/PD)models have been developed to describe the relationshipbetween antipsychotic drugs and prolactin response. Pro-lactin is synthesized and secreted by lactotrope cells. Inthe prolactin pool model [2], the response and tolerancedevelopment is depicted by the processes of generation,storage and release of prolactin. The model was used tocharacterize the prolactin response in healthy male vol-unteers to the antipsychotic drug remoxipride after adesign aiming to challenge the prolactin system, twoshort infusions with various administration intervals. Thedata were described by a model with two compartments[2]. The structure of the pool model is presented inFigure 1, but in contrast to the original publication massbalance is preserved, i.e. the input rate at baseline condi-tions is set to be equal to elimination rate at baseline con-ditions, and a circadian function has been added. In theoriginal publication, a linear relationship between remox-

ipride concentration and prolactin release was found suf-ficient to describe the response.

The original pool model was used to describe the pro-lactin response following an experimental design of theantipsychotic drug remoxipride. Later an agonist-antagonist interaction (AAI) model was proposed toexplain the interaction between dopamine concentrationand the antipsychotic drug chlorprothixene on prolactinrelease after a single intravenous or oral dose administra-tion [3]. A phenomenon important to prolactin secretion,the circadian rhythm, was integrated into the AAI modelrecently [4]. The AAI model with a circadian functiondescribed the concentration–time profile of prolactin aftersingle or repeated administration of different formulationsof risperidone and paliperidone in both patients andhealthy volunteers. In contrast, the pool model, with orwithout circadian rhythm, could not describe the datafrom these studies.

By adding knowledge of the mechanism of action andphysiology into PK/PD models, the model may not onlyexplain the data at hand better, but it is more likely that themodel can be used for extrapolation to other doses, sched-ules and drugs than those the model was based on. Boththe AAI model and the pool model have mechanisticsupport. However, only the AAI model could successfullyextrapolate to prolactin response data from new studies asdescribed above.

The objective of this study was to evaluate the perfor-mance of the AAI model, and compare it with that of thepool model, in describing data from the remoxipride study

Prolactin (Pool)

Circadiansubmodel

Circadiansubmodel

Prolactin (Plasma)

Prolactin (Plasma)

Central Peripheral

Dopamine

PD modelPOOL

PD modelAAI

PD modelRemoxipride

kout

kout

kbase

kDA kDA

kin

kform

Figure 1The circadian pool model and the circadian agonist-antagonist interaction model. Rform is the prolactin synthesizing rate; kbase is the rate constant describingprolactin release from the pool compartment to the plasma compartment; kout is the prolactin elimination rate constant. kin is the production rate and kout

is the elimination rate constant of prolactin; kDA is the turnover rate constant of the dopamine system

G. Ma et al.

816 / 70:6 / Br J Clin Pharmacol

with an experimental design, i.e. the data set the originalpool model was developed from in order to determinewhether a single mechanism-based model can describewell prolactin data from different study designs andpopulations.

Methods

The data set, which contained remoxipride and prolactinconcentrations from eight healthy male volunteers, wasthe same as the one used to develop the original poolmodel [5]. The subjects’ age ranged between 29 and45 years (mean 36 � 6 years).On each of the five occasions,two repeated doses of remoxipride 50 mg as intravenousinfusion during 30 min were administered with varyingtime intervals. The time intervals between the first doseand the second dose were 2, 8, 12, 24 and 48 h on the fivedifferent occasions. Subjects were allocated to sequencesof these intervals randomly in a crossover design. On alloccasions, the first infusion started between 08.00 h and09.00 h. For further details regarding material, methodsand the study drug, remoxipride, please refer to the origi-nal publication [2].

Blood samplingBlood samples for determination of remoxipride and pro-lactin concentrations were drawn according to the follow-ing schedule: prior to start of infusion and 10, 15, 20, 30, 40,50, 60, 90 min and 2, 4, 8, 12 and 24 h after the start of theinfusion. For the first infusion, this sampling schedule fol-lowed up to the start of the second administration.

Pharmacokinetic and pharmacodynamicmodelingPharmacokinetic and pharmacodynamic models wereconstructed sequentially. A two compartment pharmaco-kinetic model was implemented according to the previousanalysis [5]. The original parameters were calculated usingthe two-stage method in PCNONLIN® (Statistical Consult-ants, Inc., Lexington, KY, USA) and intra-individual variabil-ity (IIV) was computed from the estimated individualparameters. In the current analysis the typical pharmaco-kinetic parameters and IIV were re-estimated using popu-lation analysis with the first-order conditional estimation(FOCE) method with INTERACTION in NONMEM® VI(GloboMax/ICON, Inc.,Ellicott City,MD,USA).All of the phar-macodynamic models were implemented in NONMEM VIand the individually predicted remoxipride concentrationprofiles used to drive the drug effects were derived fromthe two compartment pharmacokinetic model with thepopulation parameter values fixed, keeping the pharmaco-kinetic data in the data set.

A circadian rhythm model was adopted from the pre-vious circadian AAI model [4] where a double cosine func-tion described the circadian change in release rate ofprolactin [6, 7]:

f AMP t PHSAMP t PHS

DIU( ) = × × × −( )+ × × × −( )( )

1 1

2 2

2 242 12

cos( )cos

ππ (1)

There are two periods, 24 and 12 h, in the equation. AMP1

and AMP2 are the amplitudes of each cosine functions.PHS1

and PHS2 are the phase shifts relative to time (t). t repre-sents a relative time to the first administration, i.e. 08.00 h,which was set to be the start time of the first infusion in thedata set as the exact time was not known (08.00 to09.00 h).

The original pool model and the circadian pool modelare presented in Figure 1. The differential equationsdescribing the time course of prolactin concentration inplasma compartment and the pool compartment aredescribed by:

d dt DIU SPRL base pool out PRLC k f C t k C= × + ( )( )× × ( )− ×1 (2)

d dt R DIU Spool form base poolC k f C t= − × + ( )( )× × ( )1 (3)

where CPRL is the prolactin concentration in plasma; Rform isthe prolactin synthesis rate; kbase is the rate constantdescribing prolactin release from the pool compartmentto the plasma compartment; kout is the prolactin elimina-tion rate constant; S(t) is a function to describe the relation-ship between the drug concentration and the release rateof prolactin; f(DIU) is the circadian function which influ-ences kbase. If f(DIU) is assumed to be constant over timeand fixed to 0, the model is reduced to the original poolmodel.

When the original pool model was modified to adhereto mass-balance principles, the following constraints wereintroduced:

Rform base pool out PRL= × = ×k C k C, ,0 0 (4)

where Cpool,0 and CPRL,0 are Cpool and CPRL, respectively, atbaseline.

Remoxipride concentrations (C) stimulate the prolactinrelease rate, kbase, with a linear relationship with slope M [5].

S t M C( ) = + ×1 (5)

The AAI model and the circadian AAI model are shown inFigure 1. They are described by

dC dt k C C C CC KI f

PRL out PRL DA DA DA

DIU= × × +( )× − (((

+ + ))+ ( ))−, ,0 01 1

1 kk Cout PRL× (6)

dC dt k C C C k CDA DA DA PRL PRL DA DA= × × ( ) − ×, ,0 0γ (7)

where kDA is the turnover rate constant of the dopaminesystem; (CPRL/CPRL,0)g is a feedback component; g is a feed-back parameter; CDA is the scaled dopamine concentrationin a hypothetical dopamine compartment; CDA,0 is thescaled dopamine concentration at baseline, which wasfixed to 10 000; KI is the potency parameter; other symbolsas for the pool model. If f(DIU) = 0, this model is reduced tothe AAI model without circadian rhythm.

Comparison of the agonist-antagonist interaction model and the pool model

Br J Clin Pharmacol / 70:6 / 817

The parameters of the original pool model, the poolmodel with enforced mass-balance, the circadian poolmodel, the AAI model, and the circadian AAI model wereestimated. For all parameters where IIV components weresupported by the data, these were estimated.

Model evaluationModels were evaluated based on standard criteria, includ-ing goodness-of-fit (GOF) plots using R (http://www.r-project.org) and Xpose 4.1 [8]. For model selectionbetween nested models the likelihood ratio test wasapplied, using the objective function values (OFV) pro-vided by the NONMEM program. Numerical predictivechecks (NPC) and visual predictive checks (VPCs), based on1000 simulations for each of the models using PsN 2.2 [9]and in house Perl scripts, were also used to evaluate themodels [10]. As the study only included eight patients andthereby little information on inter-subject variability, 40%prediction intervals were used to evaluate the model.

Results

The typical parameters in the pharmacokinetic modelwhen implemented in NONMEM, CL (6.78 l h-1) and Vss

(40.1 l), were close to the values (6.84 l h-1 and 41.48 l) esti-mated earlier by PCNONLIN® [5]. The estimated values ofIIV for CL and Vss were 15.3% and 12.2%, respectively, whilethey were 15.8% and 14.5%, respectively, in the previousinvestigation where the standard two-stage approach wasused. There was no important difference between thetwo pharmacokinetic models and the VPC presented inFigure 2 shows that predictions based on this pharmaco-kinetic model were adequate.

Original pool model and Circadian pool modelThe original pool model and a pool model including mass-balance were both evaluated. The OFVs were 1568.5 and1651.8, respectively. The original pool model employedmore parameters than the pool model with mass-balance.Most importantly, the baseline prolactin concentrations in

R-R2Above:24% Below:32%





2

0.2

0.02

2

0.2

0.02

2

0.2

0.02

2

0.2

0.02

2

0.2

0.02

0 10 20 30

0 10 20 30 0 10 20 30

0 10 20 30 40 50 60 700 10 20 30

Time (h)

Rem

oxip

ride

co

ncen

trat

ion

(mg

l-1 )

Figure 2Numerical predictive checks (NPC) and visual predictive checks (VPC) for the two compartment pharmacokinetic model with 40% prediction interval (PI).R-R2 to R-R48 are the five different occasions. R is first dose, R2, R8, R12, R24, and R48 indicate that second doses were given at 2, 8, 14, 24, and 48 h,respectively. Time 0 is 08.00 h. Above and Below indicate the percentages of data points above and below the prediction interval, respectively. 40%Prediction interval ( ); Median prediction ( )

G. Ma et al.


the plasma compartment and in the pool compartmentwere predicted to drift over time at the starting time in theoriginal pool model, showing the importance of conserv-ing mass balance in the modeling. In the original poolmodel the prolactin baseline was predicted to increasesystematically from 10 mg l-1 to >13 mg l-1 over the course ofthe experiment.The prolactin concentrations in the plasmaand pool compartment,the prolactin synthesis rate and theprolactin elimination rate estimated in the pool model withmass-balance were all higher than the values from the origi-nal pool model (Table 1).The observed median prolactinconcentration at the start of the study was 10.05 mg l-1. Anonlinear relationship between remoxipride and prolactin,described by an Emax model, was investigated, but asimprovement was limited (decrease in OFV = 3.2) and esti-mated EC50 was 11.5 mg l-1, considerably higher than theobserved concentrations, the linear function was kept.Theoriginal pool model suggested a stronger stimulation ofremoxipride on prolactin release (M, the slope constant)compared with the pool model with mass-balance.

When a circadian function was incorporated into thepool model with mass-balance, OFV reduced significantly(P < 0.001), from 1651.8 to 1479.6. An on average higherbaseline of prolactin concentration in plasma, prolactinsynthesizing rate, rate of prolactin release from pool com-partment to plasma compartment, prolactin eliminationrate and stronger stimulation were estimated by the circa-dian pool model. Residual variability was reduced by inclu-sion of the circadian sub-model, from 19% to 15%.

AAI model and circadian AAI modelThe circadian sub-model also reduced the OFV of the AAImodel, from 1566.9 to 1498.6 when it was added on pro-lactin release. A sensitivity analysis was conducted on thebaseline of dopamine concentration, CDA,0, which was fixedto 10 000. When CDA,0 was larger than 100, it had no sig-nificant influence on OFV and parameter estimation.WhenCDA,0 was larger than 10 000 NONMEM could not completethe computation successfully. The baseline prolactin con-centrations in plasma estimated by the AAI model and thecircadian AAI model were similar, 9.2 mg l-1 and 8.8 mg l-1,respectively. The parameter that changed the mostbetween the AAI model and the circadian AAI model wasthe remoxipride potency parameter, KI. KI in the AAI model,0.0687 mg l-1, was much lower than in the circadian AAImodel (0.111 mg l-1). In these two models, KI was estimatedto have a relatively large IIV, close to 50%. As for the poolmodel, addition of a circadian sub-model reduced theresidual error.

Pool model and AAI model comparisonOFV reflects how well the model fits the data. When mass-balance was preserved but no circadian rhythm functionwas allowed, the AAI model fitted the data better than thepool model. When circadian rhythm was allowed, the poolmodel with a circadian submodel explained the relation-

ship between remoxipride concentration and prolactinrelease slightly better than the AAI model with a circadianrhythm based on OFV (DOFV=19). The amplitude andaverage level of the circadian prolactin predicted profile inthe absence of drug were clearly larger and higher for thepool model than for the AAI model, but peak times weresimilar (Figure 3). Peaks were predicted to occur close to04.00 h and 16.00 h, while troughs occurred around noonand evening (Figure 3).

The VPCs performed to inspect the simulation ability ofthese two models revealed that they were equivalent topredict prolactin concentrations (Figure 4). For a perfectmodel approximately 60% of the observations areexpected to fall outside the 40% prediction intervals. On allfive occasions, the observations outside of the 40% predic-tion intervals were close to 60% for these two models. Acommon shortcoming of these two models revealed bythe NPC is that the percentages of points below the pre-diction interval are larger than those above the predictioninterval (Figure 4). The NPC of the pharmacokinetic model(Figure 2) is also asymmetrical, which indicates the predic-tion bias may come from the pharmacokinetic model.

Discussion

In the present study, two PK/PD models for prolactinrelease after antipsychotic drug administration were com-pared for the remoxipride data set from which the poolmodel was originally developed. This data set is particu-larly informative on the tolerance aspects of remoxiprideon prolactin release. When the first and second doses aregiven with only a 2 h interval, tolerance is pronounced.With increasing dose intervals, the tolerance graduallydisappears until, at a 48 h interval, no tolerance can beobserved. By incorporating observations across all hours ofthe day, the design was also informative on the circadianrhythms of prolactin release.

The pool model incorporates the synthesis of prolactin,a prolactin pool and prolactin release into and eliminationfrom blood. A linear relationship was used to describe theincreased prolactin release from the anterior pituitarybecause of the drug-induced reduction in dopamine inhi-bition [2] and the pool model is based on the assumptionthat the tolerance development of prolactin releaseobserved after repeated administration is caused bydepletion of the prolactin storage pool. Although the cir-cadian sub-model improved the fit of the pool model, inthe absence of drug, the circadian rhythm predicted by thepool model was not in agreement with relative magni-tudes of trough and peak values earlier described inhealthy volunteers (approximately 40% and 160%, respec-tively, of the 24 h mean value) [11]. In addition, the absolutetypical values in this population was predicted to be abovethe laboratory reference values of 2.1–17.7 ng ml-1 forhealthy males [12] during parts of the day.



Tab

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%)

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PRL

(mg

l-1)

9.4

9.88

2812

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(14)

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G. Ma et al.


AAI models extended the dopamine-prolactin relation-ship from a linear equation to a dopamine-prolactin feed-back loop supported by the literature [3]. Three criticalconcepts contribute to this feedback loop: 1) prolactinrelease is inhibited by dopamine; 2) antipsychotic drugsblock dopamine to bind at dopamine2 receptor; 3) prolac-tin stimulates the production of dopamine. In AAI models,the tolerance is described by a drug-dopamine agonist-antagonist interaction mechanism to prolactin release. Afurther development was based on the circadian behav-iour of prolactin [4].

The circadian AAI model to describe prolactin responsewas first implemented for risperidone and paliperidone inboth patients and healthy volunteers [4]. KI following ris-peridone and paliperidone administration was estimatedto 0.00196 mg l-1 (4.8 and 4.6 nmol l-1, respectively), whileit was estimated to 0.111 mg l-1 (302 nmol l-1) for remox-ipride in the present study. The lower potency parameter,KI, for risperidone and paliperidone indicates that thedopamine2 receptor is more effectively blocked by thesedrugs compared with remoxipride. The inhibition of thedopamine2 receptor by antipsychotic drugs is often quan-tified by KIrat, the inhibition constant measured from ratstriatum. Paliperidone is a metabolite of risperidone andthey have a similar capacity to inhibit the dopamine2

receptor [13–15]. The measured inhibition constants KIrat

are 113 nmol l-1 and 1.4 nmol l-1 for remoxipride [16] andrisperidone [17], respectively. The ratios between in vivopotency parameter from the AAI model and in vitro inhibi-tion constant for these two drugs are 0.37 and 0.29, respec-tively, suggesting that the estimated in vivo potency

parameter in the AAI model and the KIrat are correlated.Also, dopamine2-receptor occupancy of about 64% wasachieved when dosing with risperidone 3–8 mg day-1 [18]or paliperidone (extended release) 6 mg [19], while theoccupancy was 73% when dosing with remoxipride100 mg three times daily [20], i.e. for a daily total doseapproximately 50 times higher than a typical paliperidonedose.The estimated KI was 57 times higher for remoxiprideand thus in accordance with the difference in dose amountand the similar apparent clearance values [21, 22] for thecompounds.

The other system-related parameters of the AAI modelswere similar across the two studies, except that kout and theamplitude of the first cosine function were here estimatedto be approximately two and three times higher, respec-tively (Table 1). The elimination half-life of prolactin (ln(2)/kout) has been experimentally determined to 30 min inmale healthy volunteers [23] and was here estimated to35 min by the circadian AAI model. A similar value wasfound when healthy volunteers were allowed to have adifferent kout from patients in the risperidone and paliperi-done analysis [4]. When mass balance was introduced kout

increased in the pool model resulting in an estimated half-life of 17–21 min.

The predicted prolactin concentrations and circadianrhythm should in the absence of drug be independent ofwhich antipsychotic drug is administered. Although theparameters of the two circadian AAI models for healthyvolunteers were estimated based on different drugs, differ-ent administration schedules and different experimentalsites, Figure 3 reveals that the two prolactin profiles were

25

20

15

10

5

00:00 4:00 8:00 12:00

Clock time

Pro

lact

in c

onc

entr

atio

n (m

g l-

1 )

16:00 20:00 24:00

Figure 3Daily variations in prolactin concentrations in the absence of drug predicted by the circadian agonist-antagonist interaction (AAI) model and the circadianpool model in the remoxipride data set or the risperidone and paliperidone data set [4]. The box-and-whisker plot represents the distribution of themeasured prolactin concentrations at 08.00 h before treatment started.Circadian AAl (risperidone and paliperidone) ( ); Circadian AAl (remoxipride) ( );

Circadian pool (remoxipride) ( )



similar. The peak prolactin plasma concentrations havebeen reported to occur 4 h after the onset of sleep [11], or1–2 h before wakening [1], and similar values were pre-dicted by both the circadian AAI model and the circadianpool model (Figure 3). The trough concentrations pre-dicted by these two models were around 11.00 h, whilethey have earlier been reported to be observed around 6 hafter wakening [11]. The observed peak prolactin concen-tration occurred at around 04.00 h [24], which was pre-dicted by both models, while the circadian pool modelpredicted an additional high peak at 16.00 h. As discussedabove, the noteworthy difference between the circadianpool model and the circadian AAI model was the predictedamplitude of peaks and troughs.

Based on the present study and the prolactin study onrisperidone and paliperidone [4], it can be concluded thatAAI models are more able to describe prolactin responseto antipsychotic drugs than pool models. The major differ-ence between these two types of models was the assump-tion on the key mechanism for observed tolerancedevelopment. The plausibility of a drug-dopamine feed-

back for prolactin response, also following a unique experi-mental design such as the one conducted in theremoxipride study, [25] was shown here. There was also adrawback of AAI models when compared with poolmodels. The computation times of circadian AAI models(63 h) were much longer than for circadian pool models(1 h) when the computation environment was CPU Intel(R)Xeon(TM) 2.80GHz, 2GB memory with G77 Fortrancompiler.

In conclusion, the evaluation with NPC and VPC showedthat the circadian pool model and the circadian AAI modelwere approximately equivalent in describing prolactinconcentrations from the experimental study where twoshort infusions of remoxipride had been administered tochallenge the development of tolerance. Prolactin circa-dian rhythm in healthy male volunteers was estimated bythe circadian AAI model to be consistent with prolactinconcentrations reported in the literature and with the pre-vious analysis of prolactin from large clinical studies fol-lowing placebo and risperidone/paliperidone treatment.The analysis presented here also showed that the circadian

R-R2POOL:Above:29% Below:37%AAI :Above:26% Below:39%50

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R-R8POOL:Above:18% Below:39%AAI :Above:18% Below:44%


0 10 20 30

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0 10 20 30 0 10 20 30

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Figure 4Numerical predictive checks (NPC) and visual predictive checks (VPC) for the circadian pool model and the circadian agonist-antagonist interaction (AAI)model with 40% prediction interval (PI). R-R2 to R-R48 are the five different occasions. R is first dose; R2, R8, R12, R24, and R48 indicate that second doses weregiven at 2, 8, 12, 24 and 48 h, respectively. Time 0 is 08.00 h. Above and Below indicate the percentages of data points above and below the predictioninterval, respectively. Circadian pool model, POOL ( ); Median prediction ( ); Circadian AAl model, AAl ( ); Median prediction ( )

G. Ma et al.


AAI model worked across drugs and study situations suc-cessfully. The estimation of prolactin rhythm by the AAImodel supported the importance of a feedback mecha-nism to describe tolerance to prolactin release followingantipsychotic drug administration. The circadian AAImodel appeared promising to predict prolactin releaseacross different antipsychotic drugs and across a widerange of administration schedules.

Competing interests

GM-O is an employee of AstraZeneca AB, Sweden. No otherauthors have competing interests to declare.

Lena Friberg would like to thank the Knut and Alice Wal-lenberg Foundation for financial support.

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

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