A population pharmacokinetic model of piperaquine in pregnant and nonpregnant women with uncomplicated Plasmodium falciparum malaria in Sudan.  
Jump to Full Text  
MedLine Citation:

PMID: 23190801 Owner: NLM Status: MEDLINE 
Abstract/OtherAbstract:

BACKGROUND: Pregnancy is associated with an increased risk of developing a malaria infection and a higher risk of developing severe malaria. The pharmacokinetic properties of many antimalarials are also altered during pregnancy, often resulting in a decreased drug exposure. Piperaquine is a promising antimalarial partner drug used in a fixeddose combination with dihydroartemisinin. The aim of this study was to investigate the population pharmacokinetics of piperaquine in pregnant and nonpregnant Sudanese women with uncomplicated Plasmodium falciparum malaria. METHOD: Symptomatic patients received a standard dose regimen of the fixed dose oral piperaquinedihydroartemisinin combination treatment. Densely sampled plasma aliquots were collected and analysed using a previously described LCMS/MS method. Data from 12 pregnant and 12 nonpregnant women were analysed using nonlinear mixedeffects modelling. A Monte Carlo Mapped Power (MCMP) analysis was conducted based on a previously published study to evaluate the power of detecting covariates in this relatively small study. RESULTS: A threecompartment disposition model with a transitabsorption model described the observed data well. Body weight was added as an allometric function on all clearance and volume parameters. A statistically significant decrease in estimated terminal piperaquine halflife in pregnant compared with nonpregnant women was found, but there were no differences in posthoc estimates of total piperaquine exposure. The MCMP analysis indicated a minimum of 13 pregnant and 13 nonpregnant women were required to identify pregnancy as a covariate on relevant pharmacokinetic parameters (80% power and p=0.05). Pregnancy was, therefore, evaluated as a categorical and continuous covariate (i.e. estimate gestational age) in a full covariate approach. Using this approach pregnancy was not associated with any major change in piperaquine elimination clearance. However, a trend of increasing elimination clearance with increasing gestational age could be seen. CONCLUSIONS: The population pharmacokinetic properties of piperaquine were well described by a threecompartment disposition model in pregnant and nonpregnant women with uncomplicated malaria. The modelling approach showed no major difference in piperaquine exposure between the two groups and data presented here do not warrant a dose adjustment in pregnancy in this vulnerable population. 
Authors:

Richard M Hoglund; Ishag Adam; Warunee Hanpithakpong; Michael Ashton; Niklas Lindegardh; Nicholas P J Day; Nicholas J White; Francois Nosten; Joel Tarning 
Publication Detail:

Type: Journal Article; Research Support, NonU.S. Gov't Date: 20121129 
Journal Detail:

Title: Malaria journal Volume: 11 ISSN: 14752875 ISO Abbreviation: Malar. J. Publication Date: 2012 
Date Detail:

Created Date: 20130123 Completed Date: 20130606 Revised Date: 20140812 
Medline Journal Info:

Nlm Unique ID: 101139802 Medline TA: Malar J Country: England 
Other Details:

Languages: eng Pagination: 398 Citation Subset: IM 
Export Citation:

APA/MLA Format Download EndNote Download BibTex 
MeSH Terms  
Descriptor/Qualifier:

Adolescent Adult Antimalarials / administration & dosage, blood, pharmacokinetics* Artemisinins / administration & dosage Biological Availability Drug Combinations Female Humans Malaria, Falciparum / blood, complications*, drug therapy* Metabolic Clearance Rate Models, Biological* Nonlinear Dynamics Pregnancy Pregnancy Complications, Parasitic / blood, drug therapy* Quinolines / administration & dosage, blood, pharmacokinetics* Sudan Young Adult 
Grant Support  
ID/Acronym/Agency:

089275//Wellcome Trust; 093956//Wellcome Trust; //Wellcome Trust 
Chemical  
Reg. No./Substance:

0/Antimalarials; 0/Artemisinins; 0/Drug Combinations; 0/Quinolines; 6A9O50735X/dihydroartemisinin; A0HV2Q956Y/piperaquine 
Comments/Corrections 
Full Text  
Journal Information Journal ID (nlmta): Malar J Journal ID (isoabbrev): Malar. J ISSN: 14752875 Publisher: BioMed Central 
Article Information Download PDF Copyright ©2012 Hoglund et al.; licensee BioMed Central Ltd. openaccess: Received Day: 20 Month: 9 Year: 2012 Accepted Day: 22 Month: 11 Year: 2012 collection publication date: Year: 2012 Electronic publication date: Day: 29 Month: 11 Year: 2012 Volume: 11First Page: 398 Last Page: 398 PubMed Id: 23190801 ID: 3551687 Publisher Id: 1475287511398 DOI: 10.1186/1475287511398 
A population pharmacokinetic model of piperaquine in pregnant and nonpregnant women with uncomplicated Plasmodium falciparum malaria in Sudan  
Richard M Hoglund1  Email: richard.hoglund@neuro.gu.se 
Ishag Adam2  Email: ishagadam@hotmail.com 
Warunee Hanpithakpong3  Email: warunee@tropmedres.ac 
Michael Ashton1  Email: michael.ashton@pharm.gu.se 
Niklas Lindegardh34  Email: niklas@tropmedres.ac 
Nicholas PJ Day34  Email: nickd@tropmedres.ac 
Nicholas J White34  Email: nickwdt@tropmedres.ac 
Francois Nosten345  Email: francois@tropmedres.ac 
Joel Tarning34  Email: joel@tropmedres.ac 
1Unit for Pharmacokinetics and Drug Metabolism, Department of Pharmacology, University of Gothenburg, Gothenburg, Sweden 

2Faculty of Medicine, University of Khartoum, Khartoum, Sudan 

3MahidolOxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, 60th Anniversary Chalermprakiat Building, 420/6 Rajvithi Road, Bangkok, 10400, Thailand 

4Centre for Tropical Medicine, Department of Clinical Medicine, Churchill Hospital, Oxford, UK 

5Shoklo Malaria Research Unit, Mae Sot, Thailand 
Malaria is one of the most important infectious diseases with an estimated 216 million people infected worldwide in 2010 [^{1}]. Pregnant women are at an increased risk of developing a malaria infection [^{2}] and are at a higher risk of progressing to severe malaria [^{3}^{}^{5}]. Plasmodium falciparum malaria is a major contributor to maternal mortality in Sudan; around 37% of all maternal deaths between 1985 and 1999 at the Medani Teaching Hospital in Medani City, Sudan, were attributed to malaria [^{6}]. Malaria also has severe effects on the foetus causing both foetal loss and low birth weight.
Artemisininbased combination therapy (ACT) is recommended as firstline treatment for P. falciparum malaria in all endemic areas. The artemisinin derivatives have a very rapid parasiticidal effect, which substantially reduces the parasite biomass during the first days of treatment. These drugs have a short terminal elimination halflife and are, therefore, used in combination with longer acting antimalarials, with the aim of preventing recrudescence by killing residual parasites. Combination therapies consisting of drugs with different mechanisms of action also reduce the risk of the development of drug resistance [^{7},^{8}].
The oral fixeddose combination of dihydroartemisinin and piperaquine has shown excellent efficacy in the treatment of P. falciparum malaria [^{9}^{}^{13}]. Piperaquine is highly bound to plasma proteins (>99.9%), has a large apparent volume of distribution, (103–874 L/kg), a low apparent elimination clearance (0.61.3 L/h/kg) and, therefore, a long terminal elimination halflife (12–28 days) [^{14}^{}^{20}].
Pregnancy has considerable effects on the pharmacokinetic properties of many drugs. Renal elimination, expression of metabolising enzymes, volume of body water and the degree of plasma protein binding all change during pregnancy [^{21}^{}^{23}]. This could result in lower drug plasma concentrations [^{24}]. Previously published studies have reported a decrease in drug exposure during the later stages of pregnancy for artesunate, artemether, dihydroartemisinin, lumefantrine, sulphadoxine, atovaquone, proguanil and cycloguanil [^{19},^{25}^{}^{31}]. Other antimalarial drugs (e.g. quinine and amodiaquine/desethylamodiaquine) show no differences in pharmacokinetic properties in pregnant women compared to nonpregnant women [^{32}^{}^{34}].
Only one previous study has investigated the impact of pregnancy on the pharmacokinetic properties of piperaquine in patients with uncomplicated P. falciparum malaria [^{19}]. Pregnancy was found to affect the elimination clearance and the bioavailability of piperaquine, but with no change in total drug exposure. This was further supported by a noncompartmental analysis of the same study [^{35}]. No published information is available on the population pharmacokinetic properties of piperaquine in pregnant or nonpregnant women in an African country.
The aim of this study was to describe the population pharmacokinetic properties of piperaquine in pregnant and nonpregnant women with uncomplicated P. falciparum malaria in Sudan.
The study was conducted at the New Halfa Teaching Hospital in New Halfa, Sudan. Clinical details and noncompartmental analysis results are reported in full elsewhere [^{36}]. The participating women received a written and oral explanation of the study in their own language. If the woman could not read, the explanation was read to her. Ethics approval for the study was given by the College of Medical and Technical Studies, Khartoum, Sudan.
Symptomatic pregnant women with uncomplicated P. falciparum malaria in their second or third trimester attending the antenatal clinic in New Halfa were eligible to participate in the study. Nonpregnant women with uncomplicated P. falciparum malaria were also recruited as controls.
All patients received dihydroartemisininpiperaquine tetraphosphate (Duo Cotecxin, 40 mg/320 mg tablets, Beijing HolleyCotec Pharmaceuticals, Co., Ltd.) once daily for three days. Drug administration was directly observed and taken with a glass of water under fasting conditions. The number of tablets was based on the patient’s body weight to achieve a daily dose of 20 mg piperaquine tetraphosphate/kg.
Blood samples were obtained by venous puncture or a threeway tap. PCR, haematology and biochemistry samples were drawn before the first dose and on day 14. Blood samples (2 mL) for pharmacokinetic analysis were drawn predose and at 1.5, 4, 8, 24, 25.5, 28, 32, 48, 49, 50, 52, 56, 60, 72 h after the first dose and on days 5, 7, 14, 21, 28, 35, 42, 49, 56, 63 and 90. The actual time of dosing and sampling were noted and used in the pharmacokinetic analysis. Blood samples were centrifuged at 2000×g for 10 minutes and plasma samples stored in liquid nitrogen until the samples were transferred to Khartoum there they were stored in −80°C.
The chemical analysis was performed using a previously published method with separation and quantification by liquid chromatography (LC) and tandem mass spectrometry (MS/MS) detection [^{37}]. The LCsystem was an Agilent 1200 system consisting of a binary LC pump, a vacuum degasser, autosampler and a column compartment. The MSsystem was an API 5000 triple/quadruple mass spectrometer with a Turbo V ionization source. The lower limit of quantification (LLOQ) was set to 1.5 ng/mL and the lower limit of detection (LLOD) was set to 0.38 ng/mL. This method reported an intra and interday precision of below 10% for all quality control samples.
The data were analysed using nonlinear mixedeffects modelling as implemented in NONMEM version VI (Icon Development Solutions, Ellicott City, Maryland, USA) [^{38}]. Piperaquine plasma concentrations were transformed into their natural logarithms to increase the stability of the numeric analysis. Models were fitted to the data using the firstorder conditional estimation (FOCE) method with interaction [^{39}^{}^{41}]. Census, version 1.1 [^{42}], and Xpose, version 4.04 [^{43}], library for R was used for model diagnostics. PerlspeaksNONMEM (PsN), version 3.4.2, [^{44}] was used to automate the modelling process and for model diagnostics.
Model discrimination was based the on the objective function value (OFV) computed by NONMEM as −2×log likelihood [^{45}]. The OFV is approximately χ^{2} distributed and a decrease in OFV of 3.84 and 6.64 is considered a significant drop with p<0.05 and p<0.01, respectively, when adding one additional parameter (one degree of freedom between two nested models).
Structural models with one, two, three and four disposition compartments were fitted to the data. Several alternative absorption models were investigated; firstorder absorption, firstorder absorption with lag time, zeroorder absorption, sequential zero and firstorder absorption, sequential zero and firstorder absorption with lag time, parallel first and zeroorder absorption, parallel firstorder absorption and transit compartment absorption with a fixed number of 1–10 transit compartments. The full implementation of the transit compartment absorption model, which allows the number of transit compartments to vary between patients, was also evaluated [^{46}].
It was assumed that drug elimination took place from the central compartment and the base model was parameterized as elimination clearance, central volume of distribution, intercompartmental clearance(s) and peripheral distribution volume(s). Bioavailability was added to the model and the population value was fixed to 100%.
The distribution of the individual parameters was assumed to be lognormal and betweensubject variability (BSV) was investigated on all parameters as an exponential random effect [Equation 1].
(1)
Pi=θp·eηi,P 
where P_{i} is the individual estimate for a model parameter (e.g. individual drug clearance) in the i^{th} individual. θ_{p} is the population mean of parameter P and η_{i,P} is individual i^{th} deviation from the population mean. BSV is estimated from a normal distribution with variance ω^{2} and zero mean. Between dose occasion variability (BOV) was evaluated on absorption parameters [Equation 2].
(2)
Pij=θP·eηi,P+κj,P 
Where P_{ij} is the individual parameter estimate for the i^{th} patient on the j^{th} dose occasion, κ is the deviation from the population mean after each dose occasion, taken from a normal distribution with variance Π^{2} and zero mean. An additive residual error model was assumed since data were transformed into their natural logarithms (i.e. essentially equivalent to an exponential error model on an arithmetic scale). Body weight was tried in the model as a simultaneous incorporation of an allometric function on all clearance (power of 0.75) and volume parameters (power of 1), considering the strong biological prior of this covariate relationship [^{47}^{}^{49}].
Basic goodnessoffit plots and simulationbased diagnostics were used to evaluate the final model. Visual and numerical predictive checks [^{50}] were performed using 2000 simulations at each concentrationtime point with binning based on protocol times. The 5^{th}, 50^{th} and 95^{th} percentile of observed data were plotted over the simulated 95% confidence interval of the same percentiles to evaluate the models predictive performance. Bootstrap diagnostics were performed using 1000 resampled datasets, stratified on pregnancy.
A Monte Carlo Mapped Power analysis (MCMP) [^{51}] was conducted based on results from a previously published population analysis [^{19}]. The current study design in terms of sampling times and doses were used to create a modelled data set with 408 pregnant and 408 nonpregnant patients. This data set and the published population pharmacokinetic model was used to estimate the minimum number of individuals needed in each group (i.e. pregnant and nonpregnant) to identify the described covariate relationships (i.e. a 45.0% increase in elimination clearance or a 46.8% increase in bioavailability) at a given power (80%) and significance level (p=0.05). Full power curves were produced by plotting number of patients needed against the power to detect the assumed covariate relationship.
Pregnancy was investigated in the final pharmacokinetic model utilizing a full covariate approach where pregnancy was included as a categorical covariate on all pharmacokinetic parameters. Estimated gestational age (EGA) was evaluated as a continuous covariate on individual parameters using a linear and a power function, and the most appropriate covariate relationship (lowest OFV) was incorporated into a full covariate model for EGA. These two full covariate models were bootstrapped (n=200) to investigate the impact of pregnancy. A pregnancy related change in the parameter estimate of more than 20% was deemed to have clinical relevance.
Fourteen nonpregnant and twelve pregnant women were recruited into the study but two nonpregnant women withdrew their consent and were excluded from the analysis. Full demographics are given in Table 1. The treatment was welltolerated, none of the patients vomited after treatment and no severe adverse events were reported during the study. One nonpregnant woman had a PCRconfirmed new infection on day 35. None of the women presented recrudescent malaria during the nine weeks of followup.
Five hundred sixtyfour (564) postdose plasma samples of piperaquine were used in the pharmacokinetic analysis. A total of 7 (1.2%) of these samples were measured to be below the limit of quantification and omitted. A threecompartmental disposition model resulted in a significantly better model fit compared with a twocompartment model (ΔOFV=−32.8). An additional peripheral compartment (fourcompartment disposition model) did not further improve the fit (ΔOFV=0). A transitcompartment (n=3) absorption model was superior to all other absorption models (ΔOFV≥−44.5). In the final model the absorption rate constant (k_{a}) and the transitcompartment rate constant (k_{tr}) were set equal to increase the stability of the model. An additive residual error model was adequate in describing the residual random variability. BSV could be estimated reliably on elimination clearance, one intercompartmental clearance parameter, and one peripheral volume parameter. The addition of BSV on the bioavailability resulted in a significant improvement in model fit (ΔOFV=−70.9). BOV had considerable impact on both mean transit absorption time and bioavailability (ΔOFV=−340). The final parameter estimates and a schematic picture of the final structural model is presented in Table 2 and Figure 1. Body weight was incorporated with an allometric function on all clearance and volume parameters (ΔOFV=−6.14).
Secondary parameters (i.e. total drug exposure, maximum concentration after first dose, time to maximum concentration, elimination halflife and day 7 concentrations) were analysed using the Mann–Whitney Utest to identify differences between pregnant and nonpregnant women (Table 3). There was a significant difference in terminal elimination halflife (p=0.0014), time to maximum concentration (p=0.0177) and maximum concentration (p=0.0205) [median (range) in pregnant vs. nonpregnant women: 22.1 (19.125.8) vs. 25.7 (20.933.3) days, 3.07 (1.654.64) vs. 1.48 (0.8874.18) hours and 185 (109–363) vs. 102 (40.6235) ng/mL, respectively]. However, no significant differences were found in day 7 concentrations (p=0.67), day 28 concentrations (p=0.84) or the total drug exposure (p=0.80) between the pregnant and nonpregnant women.
The MCMP analysis (5% significance level and 80% power) indicated that 8+8 and 13+13 women are needed to detect pregnancy as a covariate on elimination clearance and bioavailability, respectively (Figure 2). A formal stepwise covariate search was therefore not performed since it might result in a biased covariate selection in this small population sample.
Two full covariate models were constructed from the final model to investigate the clinical relevance of pregnancy and EGA separately. Pregnancy had a relatively large impact on mean transit absorptiontime, volume of distributions and intercompartment clearances but no significant effect on elimination clearance (Figure 3). The inclusion of EGA as a power function or a linear function produced similar results. EGA was therefore implemented as a linear function for the full covariate approach and resulted in similar results compared to pregnancy as a categorical covariate (Figure 4A). Bootstrap results for elimination clearance, stratified by trimester (i.e. nonpregnant, second trimester at 20 weeks, and third trimester at 32 weeks) were also investigated and resulted in a nonsignificant trend of increasing clearance with increasing EGA (Figure 4B).
The final model resulted in good model diagnostic performance and reliable parameter estimates (Figure 5 and Table 2). Calculated epsilonshrinkage was low (13.0%) which indicates that model diagnostics can be assessed reliably. However, etashrinkage was relatively high for certain parameters (CL/F=18.9%, MTT=13.252.8%, F=12.446.6%) (Table 2) and empirical Bayes estimates should therefore be interpreted with caution (Table 3) [^{52}]. The final model had good predictive performance (Figure 6) with 4.8% (95% CI. 1.4%11%) of observed data below and 2.1% (95% CI. 1.4%10%) of observed data above the simulated 90% prediction interval (the three observations at day 90 were excluded because too few patients were followed up to this time for reliable simulations).
In this study, the pharmacokinetic properties of piperaquine have been investigated using nonlinear mixedeffects modelling in pregnant and nonpregnant Sudanese women treated with piperaquinedihydroartemisinin for uncomplicated P. falciparum malaria. Few studies have been performed to evaluate the effect of pregnancy on the population pharmacokinetics of piperaquine, and this is the first study conducted in an African population. The treatment was welltolerated and none of the participating women had recrudescent malaria infections.
Previous studies of piperaquine pharmacokinetics have presented both two and threecompartment disposition models depending on the amount of data included in the analysis [^{14},^{15},^{17},^{19},^{20},^{53}]. A threecompartment disposition model described the piperaquine concentrationtime data adequately in this study. This supports the general finding that a threecompartment disposition is more appropriate than a twocompartment disposition when modelling data from patients followed for a sufficient period of time.
The absorption phase was best described with a transit compartment model with three transit compartments including random effects on bioavailability (BSV and BOV) and mean transit absorption time (BOV). The transitcompartment model provides a more physiological representation of the absorption process compared to the absorption models used in previous studies (i.e. firstorder absorption and parallel firstorder absorption with lag time) [^{15},^{17}]. Recently published studies have also implemented the transitcompartment model but with two and fivetransit compartments which support the absorption model presented here [^{19},^{20}]. Small variations in the number of transit compartments are to be expected when modelling different studies due to population differences, sampling schedules and study size. The inclusion of BSV and BOV in the absorption model improved the description of the data in the absorption phase and accommodated the large betweensubject and betweenoccasion variability in these data. The data in the absorption phase was not rich enough to estimate separate absorption rates for k_{a} and k_{tr}, and they were therefore set to be equal. This is a common limitation and the same approach has been used in previous studies [^{19},^{20}]. Incorporating BOV resulted in an increasing median bioavailability (0.77, 1.19 and 1.40 at dose 1, 2 and 3, respectively) and mean transit absorption time (1.55, 1.95 and 2.05 at dose 1, 2 and 3, respectively) during the treatment regimen. Similar patterns have been identified in previously studies on piperaquine [^{19}]. This might be an effect of disease recovery or differences in the food intake over the course of the dose regimen. This cannot be verified since parasite densities were not counted at each dose and food intake was not monitored in this study.
Pregnant women had a shorter terminal halflife compared to nonpregnant women, which is in agreement with the noncompartmental analysis [^{36}], and higher maximum concentrations after the first dose. However, there were no differences in total piperaquine exposure, day 7 concentrations or day 28 concentrations, which supports previously published findings in an Asian pregnant population [^{19}].
The main aim of this study was to investigate the pharmacokinetic differences between pregnant and nonpregnant women, but the sample size was not large enough to make a conventional covariate search. The MCMP analysis resulted in a minimum of 13 patients needed in each group in order to identify the previously described covariate relationships with 80% power and a significance level of 0.05 (Figure 2). However, this is under the assumption of perfect sampling since the MCMP analysis was based on simulated data using protocol sampling times. In the present study, some patients were not sampled for the complete followperiod and some samples were randomly missing which might increase the number of patients needed to identify the assumed covariaterelationships. Therefore the final model did not include any covariates except body weight, which has a strong biological prior [^{47},^{48}] and in addition gave a drop in OFV when included in the model. The full covariate approach suffered from identifiability issues when incorporating the pregnancy covariate simultaneously on clearance parameters, volume parameters and relative bioavailability. The full covariate approach was therefore used to investigate the net effect of a potential covariate on all parameters except relative bioavailability. This approach resulted in a model with reduced volume of distribution and intercompartment clearance in pregnant women compared with nonpregnant women but no neteffect on apparent clearance. This is in agreement with previously published results where pregnancy affected both clearance and relative bioavailability but in different directions [^{19}]. These covariate relationships would also explain the difference in terminal elimination halflife and the lack of difference in total drug exposure.
The model presented in this study was built on data from few patients and a single individual can therefore have a considerable impact on the results. Piperaquine population pharmacokinetic parameter estimates from the final model are in agreement with previous reports (Table 4). However, the elimination clearance presented in this study for an African population is lower compared to previous studies in nonpregnant and pregnant patients. This might suggest an ethnicity related effect on elimination clearance but this needs to be confirmed in a larger population.
In conclusion, this study presents the population pharmacokinetic properties of piperaquine in pregnant and nonpregnant women with uncomplicated P. falciparum malaria in Sudan. The terminal halflife was shorter in pregnant compared to nonpregnant women, but the total drug exposure was comparable between the two groups. This supports previous findings that no dose adjustments are needed on account of altered piperaquine pharmacokinetics in pregnancy.
The Welcome Trust is a UKbased medical research charity and is independent of all drug companies. It has no financial links with the manufacturers of either the diagnostics tests or the drugs used in this study. The authors declare no conflict of interest.
IA, FN, ND, and NW conceived the project. WH, NL and JT quantified the drug concentrations. RH and JT performed the pharmacokinetic analysis and wrote the first draft of the manuscript. All authors revised the manuscript critically for important intellectual content and approved the final manuscript.
We sincerely thank all women for their participation in completing this study. We also thank the diligent staff from New Halfa Teaching Hospital. The study treatment was kindly provided by Bejing HolleyCotec Pharmaceuticals, Co., Ltd. (Bejing, China). Drug assays were supported by the Malaria in Pregnancy (MIP) consortium, which is funded through a grant from the Bill and Melinda Gates Foundation to the Liverpool School of Tropical Medicine. This investigation was part of the Wellcome TrustMahidol UniversityOxford Tropical Medicine Research Programme, and the PKPDia collaboration, both supported by the Wellcome Trust of Great Britain.
References
WHOSWorld malaria report: 2011Year: 2011Switzerland: World Health Organization  
Lindsay S,Ansell J,Selman C,Cox V,Hamilton K,Walraven G,Effect of pregnancy on exposure to malaria mosquitoesLancetYear: 19722000355  
SchantzDunn J,Nour NM,Malaria and pregnancy: a global health perspectiveRev Obstet GynecolYear: 2009218619219826576  
Abrams ET,Meshnick SR,Malaria during pregnancy in endemic areas: a lens for examining maternalfetal conflictAm J Hum BiolYear: 20092164365010.1002/ajhb.2091919322887  
Smereck J,Malaria in pregnancy: update on emergency managementJ Emerg MedYear: 20104039339620566259  
Dafallah SE,ElAgib FH,Bushra GO,Maternal mortality in a teaching hospital in SudanSaudi Med JYear: 20032436937212754536  
Nosten F,Brasseur P,Combination therapy for malaria: the way forward?DrugsYear: 2002621315132910.2165/000034952002620900000312076181  
White NJ,Delaying antimalarial drug resistance with combination chemotherapyParasitologicaYear: 199941301308  
Ashley EA,Krudsood S,Phaiphun L,Srivilairit S,McGready R,Leowattana W,Hutagalung R,Wilairatana P,Brockman A,Looareesuwan S,Nosten F,White NJ,Randomized, controlled doseoptimization studies of dihydroartemisininpiperaquine for the treatment of uncomplicated multidrugresistant falciparum malaria in ThailandJ Infect DisYear: 20041901773178210.1086/42501515499533  
Ashley EA,McGready R,Hutagalung R,Phaiphun L,Slight T,Proux S,Thwai KL,Barends M,Looareesuwan S,White NJ,Nosten F,A randomized, controlled study of a simple, oncedaily regimen of dihydroartemisininpiperaquine for the treatment of uncomplicated, multidrugresistant falciparum malariaClin Infect DisYear: 20054142543210.1086/43201116028147  
Denis MB,Davis TM,Hewitt S,Incardona S,Nimol K,Fandeur T,Poravuth Y,Lim C,Socheat D,Efficacy and safety of dihydroartemisininpiperaquine (Artekin) in Cambodian children and adults with uncomplicated falciparum malariaClin Infect DisYear: 2002351469147610.1086/34464712471565  
Karunajeewa H,Lim C,Hung TY,Ilett KF,Denis MB,Socheat D,Davis TM,Safety evaluation of fixed combination piperaquine plus dihydroartemisinin (Artekin) in Cambodian children and adults with malariaBr J Clin PharmacolYear: 200457939914678346  
Tran TH,Dolecek C,Pham PM,Nguyen TD,Nguyen TT,Le HT,Dong TH,Tran TT,Stepniewska K,White NJ,Farrar J,Dihydroartemisininpiperaquine against multidrugresistant Plasmodium falciparum malaria in Vietnam: randomised clinical trialLancetYear: 2004363182210.1016/S01406736(03)15163X14723988  
Hung TY,Davis TM,Ilett KF,Karunajeewa H,Hewitt S,Denis MB,Lim C,Socheat D,Population pharmacokinetics of piperaquine in adults and children with uncomplicated falciparum or vivax malariaBr J Clin PharmacolYear: 20045725326214998421  
Roshammar D,Hai TN,Friberg Hietala S,Van Huong N,Ashton M,Pharmacokinetics of piperaquine after repeated oral administration of the antimalarial combination CV8 in 12 healthy male subjectsEur J Clin PharmacolYear: 20066233534110.1007/s002280050084916570188  
Sim IK,Davis TM,Ilett KF,Effects of a highfat meal on the relative oral bioavailability of piperaquineAntimicrob Agents ChemotherYear: 2005492407241110.1128/AAC.49.6.24072411.200515917540  
Tarning J,Ashley EA,Lindegardh N,Stepniewska K,Phaiphun L,Day NP,McGready R,Ashton M,Nosten F,White NJ,Population pharmacokinetics of piperaquine after two different treatment regimens with dihydroartemisininpiperaquine in patients with Plasmodium falciparum malaria in ThailandAntimicrob Agents ChemotherYear: 2008521052106110.1128/AAC.009550718180343  
Annerberg A,Lwin KM,Lindegardh N,Khrutsawadchai S,Ashley E,Day NP,Singhasivanon P,Tarning J,White NJ,Nosten F,A small amount of fat does not affect piperaquine exposure in patients with malariaAntimicrob Agents ChemotherYear: 2011553971397610.1128/AAC.002791121709087  
Tarning J,Rijken MJ,McGready R,Phyo AP,Hanpithakpong W,Day NP,White NJ,Nosten F,Lindegardh N,Population pharmacokinetics of dihydroartemisinin and piperaquine in pregnant and nonpregnant women with uncomplicated malariaAntimicrob Agents ChemotherYear: 2012561997200710.1128/AAC.057561122252822  
Tarning J,Zongo I,Somé FA,Rouamba N,Parikh S,Rosenthal PJ,Hanpithakpong W,Jongrak N,Day NP,White NJ,Nosten F,Ouedraogo JB,Lindegardh N,Population pharmacokinetics and pharmacodynamics of piperaquine in children with uncomplicated falciparum malariaClin Pharmacol TherYear: 20129149750510.1038/clpt.2011.25422258469  
Dawes M,Chowienczyk PJ,Drugs in pregnancy. Pharmacokinetics in pregnancyBest Pract Res Clin Obstet GynaecolYear: 20011581982610.1053/beog.2001.023111800526  
Dean M,Stock B,Patterson RJ,Levy G,Serum protein binding of drugs during and after pregnancy in humansClin Pharmacol TherYear: 19802825326110.1038/clpt.1980.1587398192  
Anderson GD,Pregnancyinduced changes in pharmacokinetics: a mechanisticbased approachClin PharmacokinetYear: 200544989100810.2165/000030882005441000000116176115  
McGready R,Tan SO,Ashley EA,Pimanpanarak M,ViladpaiNguen J,Phaiphun L,Wustefeld K,Barends M,Laochan N,Keereecharoen L,Lindegardh N,Singhasivanon P,White NJ,Nosten F,A randomised controlled trial of artemetherlumefantrine versus artesunate for uncomplicated plasmodium falciparum treatment in pregnancyPLoS MedYear: 20085e25310.1371/journal.pmed.005025319265453  
Green MD,van Eijk AM,van Ter Kuile FO,Ayisi JG,Parise ME,Kager PA,Nahlen BL,Steketee R,Nettey H,Pharmacokinetics of sulfadoxinepyrimethamine in HIVinfected and uninfected pregnant women in Western KenyaJ Infect DisYear: 20071961403140810.1086/52263217922406  
McGready R,Ashley EA,Moo E,Cho T,Barends M,Hutagalung R,Looareesuwan S,White NJ,Nosten F,A randomized comparison of artesunateatovaquoneproguanil versus quinine in treatment for uncomplicated falciparum malaria during pregnancyJ Infect DisYear: 200519284685310.1086/43255116088834  
McGready R,Stepniewska K,Edstein MD,Cho T,Gilveray G,Looareesuwan S,White NJ,Nosten F,The pharmacokinetics of atovaquone and proguanil in pregnant women with acute falciparum malariaEur J Clin PharmacolYear: 20035954555210.1007/s002280030652912955371  
McGready R,Stepniewska K,Lindegardh N,Ashley EA,La Y,Singhasivanon P,White NJ,Nosten F,The pharmacokinetics of artemether and lumefantrine in pregnant women with uncomplicated falciparum malariaEur J Clin PharmacolYear: 2006621021103110.1007/s002280060199717053895  
McGready R,Stepniewska K,Ward SA,Cho T,Gilveray G,Looareesuwan S,White NJ,Nosten F,Pharmacokinetics of dihydroartemisinin following oral artesunate treatment of pregnant women with acute uncomplicated falciparum malariaEur J Clin PharmacolYear: 20066236737110.1007/s002280060118y16552504  
Tarning J,McGready R,Lindegardh N,Ashley EA,Pimanpanarak M,Kamanikom B,Annerberg A,Day NP,Stepniewska K,Singhasivanon P,et al. Population pharmacokinetics of lumefantrine in pregnant women treated with artemetherlumefantrine for uncomplicated Plasmodium falciparum malariaAntimicrob Agents ChemotherYear: 2009533837384610.1128/AAC.001950919564366  
Tarning J,Kloprogge F,Piola P,Dhorda M,Muwanga S,Turyakira E,Nuengchamnong N,Nosten F,Day NP,White NJ,et al. Population pharmacokinetics of Artemether and dihydroartemisinin in pregnant women with uncomplicated Plasmodium falciparum malaria in UgandaMalar JYear: 20121129310.1186/147528751129322913677  
Abdelrahim II,Adam I,Elghazali G,Gustafsson LL,Elbashir MI,Mirghani RA,Pharmacokinetics of quinine and its metabolites in pregnant Sudanese women with uncomplicated Plasmodium falciparum malariaJ Clin Pharm TherYear: 200732151910.1111/j.13652710.2007.00788.x17286785  
Rijken MJ,McGready R,Jullien V,Tarning J,Lindegardh N,Phyo AP,Win AK,Hsi P,Cammas M,Singhasivanon P,White NJ,Nosten F,Pharmacokinetics of amodiaquine and desethylamodiaquine in pregnant and postpartum women with Plasmodium vivax malariaAntimicrob Agents ChemotherYear: 2011554338434210.1128/AAC.001541121709098  
Tarning J,Chotsiri P,Jullien V,Rijken MJ,Bergstrand M,Cammas M,McGready R,Singhasivanon P,Day NP,White NJ,Nosten F,Lindegardh N,Population pharmacokinetic and pharmacodynamic modeling of amodiaquine and desethylamodiaquine in women with Plasmodium vivax malaria during and after pregnancyAntimicrob Agents ChemotherYear: 2012565764577310.1128/AAC.012421222926572  
Rijken MJ,McGready R,Phyo AP,Lindegardh N,Tarning J,Laochan N,Than HH,Mu O,Win AK,Singhasivanon P,White N,Nosten F,Pharmacokinetics of dihydroartemisinin and piperaquine in pregnant and nonpregnant women with uncomplicated falciparum malariaAntimicrob Agents ChemotherYear: 2011555500550610.1128/AAC.050671121947392  
Adam I,Tarning J,Lindegardh N,Mahgoub H,McGready R,Nosten F,Pharmacokinetics of piperaquine in pregnant women in Sudan with uncomplicated Plasmodium falciparum malariaAmJTrop Med HygYear: 201287354010.4269/ajtmh.2012.110410  
Lindegardh N,Annerberg A,White NJ,Day NP,Development and validation of a liquid chromatographictandem mass spectrometric method for determination of piperaquine in plasma stable isotope labeled internal standard does not always compensate for matrix effectsJ Chromatogr B Analyt Technol Biomed Life SciYear: 200886222723610.1016/j.jchromb.2007.12.011  
Beal SLLBS,Boeckmann AJ,NONMEM Users GuidesYear: 2006City, Maryland, USA: Ellicott City, Maryland, USA  
Wahlby U,Bouw MR,Jonsson EN,Karlsson MO,Assessment of type I error rates for the statistical submodel in NONMEMJ Pharmacokinet PharmacodynYear: 20022925126910.1023/A:102025482359712449498  
Wahlby U,Jonsson EN,Karlsson MO,Assessment of actual significance levels for covariate effects in NONMEMJ Pharmacokinet PharmacodynYear: 20012823125210.1023/A:101152712557011468939  
Beal AJB SL,Sheiner LB,NONMEM users guides. University of CalifoniaYear: 1992San Fransisco, CA: NONMEM project group  
Wilkins JJ,NONMEMory: a run management tool for NONMEMComput Methods Programs BiomedYear: 20057825926710.1016/j.cmpb.2005.02.00315899310  
Jonsson EN,Karlsson MO,Xpose–an SPLUS based population pharmacokinetic/pharmacodynamic model building aid for NONMEMComput Methods Programs BiomedYear: 199958516410195646  
Lindbom L,Pihlgren P,Jonsson EN,PsNToolkit–a collection of computer intensive statistical methods for nonlinear mixed effect modeling using NONMEMComput Methods Programs BiomedYear: 20057924125710.1016/j.cmpb.2005.04.00516023764  
Beal SL,Sheiner LB,Estimating population kineticsCrit Rev Biomed EngYear: 198281952226754254  
Savic RM,Jonker DM,Kerbusch T,Karlsson MO,Implementation of a transit compartment model for describing drug absorption in pharmacokinetic studiesJ Pharmacokinet PharmacodynYear: 20073471172610.1007/s109280079066017653836  
Anderson BJ,Holford NH,Mechanismbased concepts of size and maturity in pharmacokineticsAnnu Rev Pharmacol ToxicolYear: 20084830333210.1146/annurev.pharmtox.48.113006.09470817914927  
Anderson BJ,Holford NH,Mechanistic basis of using body size and maturation to predict clearance in humansDrug Metab PharmacokinetYear: 200924253610.2133/dmpk.24.2519252334  
McLeay SC,Morrish GA,Kirkpatrick CM,Green B,The relationship between drug clearance and body size: systematic review and metaanalysis of the literature published from 2000 to 2007Clin PharmacokinetYear: 20125131933010.2165/115989300000000000000022439649  
Holford N,A degenerative predictive check [abstract]. 14th annual Meeting Population approach group EuropeYear: 200573814  
Vong C,Bergstrand M,Nyberg J,Karlsson MO,Rapid sample size calculations for a defined likelihood ratio testbased power in mixedeffects modelsAAPS JYear: 20121417618610.1208/s122480129327822350626  
Savic RM,Karlsson MO,Importance of shrinkage in empirical bayes estimates for diagnostics: problems and solutionsAAPS JYear: 20091155856910.1208/s122480099133019649712  
Karunajeewa HA,Ilett KF,Mueller I,Siba P,Law I,PageSharp M,Lin E,Lammey J,Batty KT,Davis TM,Pharmacokinetics and efficacy of piperaquine and chloroquine in Melanesian children with uncomplicated malariaAntimicrob Agents ChemotherYear: 20085223724310.1128/AAC.005550717967917  
Salman S,PageSharp M,Batty KT,Kose K,Griffin S,Siba PM,Ilett KF,Mueller I,Davis TM,Pharmacokinetic comparison of two piperaquinecontaining artemisinin combination therapies in Papua New Guinean children with uncomplicated malariaAntimicrob Agents ChemotherYear: 2012563288329710.1128/AAC.062321122470119 
Figures
Tables
Admission demographic data of study population
Nonpregnant women  Pregnant women  Pvalue  


Median (Range)

Median (Range)


Number of patients

12

12



Daily piperaquine (phosphate) dose (mg/kg)

18.1 (15.124.2)

17.6 (13.621.7)

0.884

Daily piperaquine (base) dose (mg/kg)

10.5 (8.7113.9)

10.2 (7.8312.5)

0.884

Age (years)

21.0 (16.043.0)

26.0 (18.033.0)

0.977

Body weight (kg)

53.0 (44.081.0)

59.0 (50.072.0)

0.544

Height (cm)

163 (150–174)

166 (150–174)

0.908

Estimated gestational age (weeks)



32.0 (15.3–40.1)



Parasitemia (parasites/μL)

13200 (936–68700)

12900 (624–118000)

0.488

Days of fever

2.5 (1–6)

3 (1–6)

0.095

Fever (°C)

38.3 (36.740.0)

38.2 (36.639.9)

0.795

Haemoglobin (g/dL)

8.70 (7.6011.5)

9.65 (8.0012.0)

0.099

Urea (mg/dL)

26.0 (24.028.0)

25.0 (24.028.0)

0.036

Serum glutamic pyruvic transaminase (IU/L)

5.00 (2.0010.0)

4.50 (2.009.00)

0.445

Serum glutamic oxaloacetic transaminase (IU/L)  13.5 (2.0018.0)  13.0 (3.0021.0)  0.727 
The pvalues are calculated using the Mann–Whitney Utest.
Final parameter estimates describing the piperaquine population pharmacokinetics in women with uncomplicated P. falciparum malaria
Population estimates [RSE %]  95% CI  BSV/BOV† [RSE %]  95% CI  

CL/F (L/h)

44.6 [9.90]

37.353.8

22.5 [31.5]

14.629.0

V_{C}/F (L)

1820 [11.5]

14502240





Q_{1}/F (L/h)

47.7 [19.0]

32.469.2





V_{P1}/F (L)

15900 [12.3]

1260020400





Q_{2}/F (L/h)

352 [11.1]

283431





V_{P2}/F (L)

7520 [17.1]

552010500





MTT (h)

1.70 [8.05]

1.452.00

60.7 [22.8] †

44.576.7

RUV

0.0973 [5.90]

0.07530.120





No. of trans comp

3 fix







F (%)

100 fix



34.7 [59.2]

9.5254.9

64.8 [15.2] †  52.876.0 
Coefficient of variation (%CV) for betweensubject variability (BSV) and (†) between occasion variability (BOV) were calculated as the [exp(estimated variance)1]^{1/2}. Relative standard errors (RSE) and the 95% confidence intervals (CI) were based on 868 successful stratified bootstrap runs (out of 1000) and presented as 100×(standard deviation/mean value) and as 2.5 to 97.5 percentiles, respectively.
CL/F is the apparent elimination clearance. Vc/F is the apparent volume of distribution of the central compartment. Q1/F and Q2/F is the intercompartment clearance between the central and first and second peripheral compartment, respectively. VP1/F and VP2/F is the apparent volume of distribution of first and second peripheral compartment, respectively. MTT is the mean transit time of the absorption model. RUV is the variance of the residual variability. No. of trans comp is the number of transit compartments used in the absorption phase. F represents the relative bioavailability.
Secondary parameters of piperaquine pharmacokinetics in pregnant and nonpregnant women with uncomplicated P. falciparum malaria
Secondary parameters  Total  Nonpregnant women  Pregnant women  pvalue 

C_{MAX} (ng/mL)

158 [40.6363]

102 [40.6235]

185 [109–363]

0.021

T_{MAX} (hours)

2.62 [0.8874.64]

1.48 [0.8874.18]

3.07 [1.654.64]

0.018

Halflife (days)

23.4 [19.133.3]

25.7 [20.933.3]

22.1 [19.125.8]

0.001

Day 7 concentration (ng/mL)

58.3 [16.6146]

55.4 [16.6146]

60.7 [40.1103]

0.671

Day 28 concentration (ng/mL)

15.9 [4.8538.6]

15.4 [4.8538.6]

16.1 [9.6826.8]

0.840

AUC_{0>90} (ng*h/mL)

40600 [12400–100000]

38000 [12400–100000]

42700 [27100–68700]

0.799

AUC_{48h>90} (ng*h/mL)  36400 [10600–90300]  35300 [10600–90300]  37700 [23500–63200]  0.887 
Secondary parameters are predicted using the final model and values are presented as median [range]. The pvalues are calculated with a Mann–Whitney Utest.
C_{MAX} is the predicted maximum concentration after the first dose and T_{MAX} is the time to C_{MAX}. Halflife is the estimated terminal elimination halflife. Day 7 and 28 concentrations are the model predicted plasma concentrations of piperaquine at day 7 and 28, respectively. AUC_{0>90} is the predicted area under the concentrationtime curve from time zero extrapolated to day 90. AUC_{48h>90} is the predicted area under the concentrationtime curve from 48 hours extrapolated to day 90.
A literature comparison of the pharmacokinetic properties of piperaquine
Study population  Age (years)  Study size (Males/Females)  t_{1/2} (days)  CL/F (L/h/kg)  V_{D}/F (L/kg)  Method  Reference 

Piperaquine pharmacokinetics in pregnant women


Pregnant Sudanese women with uncomplicated P. falciparum malaria

1833

12 (0/12)

22.1

0.678

384

Pop PK

This study

Pregnant Thai and Karen women with uncomplicated P. falciparum malaria

1843

24 (0/24)

17.5

1.28

529

Pop PK

[^{19}]

Piperaquine pharmacokinetics in nonpregnant populations


Nonpregnant Sudanese women with uncomplicated P. falciparum malaria

1643

12 (0/12)

25.7

0.739

446

Pop PK

This study

Nonpregnant Thai and Karen women with uncomplicated P. falciparum malaria

1845

24 (0/24)

24.0

1.32

829

Pop PK

[^{19}]

Nonpregnant Thai and Karen males and females with uncomplicated P. falciparum malaria

652

98 (59/39)

27.8

1.37

874

Pop PK

[^{17}]

Nonpregnant Cambodian males and females with uncomplicated P. falciparum malaria

30±13†

38 (20/18)

22.6

0.900

574

Pop PK

[^{14}]

Healthy Vietnamese males

2145

12 (12/0)

23.0

1.82

194

Pop PK

[^{15}]

Piperaquine pharmacokinetics in children


Children in Papua New Guinea with uncomplicated P. falciparum and P. vivax malaria

7.1 ±1.5†

12 (8/4)

21.3

0.573*

385*

Pop PK

[^{54}]

Children in Burkina Faso with uncomplicated P. falciparum malaria

210

236 (131/105)

23.2

0.417

214

Pop PK

[^{20}]

Children in Papua New Guinea with uncomplicated P. falciparum, P. vivax and P. malariae malaria

6.9 ±1.4†

22 (17/5)

17.2

0.850

431

Pop PK

[^{53}]

Cambodian children with uncomplicated P. falciparum malaria

7±2†

47 (26/21)

13.5

1.85

614

Pop PK

[^{14}]

Influence of diet on piperaquine pharmacokinetics


Fasting nonpregnant Thai and Karen males and females with uncomplicated P. falciparum malaria

1855

15 (13/2)

17.5

1.19

700

NCA

[^{18}]

Fed nonpregnant Thai and Karen males and females with uncomplicated P. falciparum malaria

1941

15 (13/2)

21.4

1.01

769

NCA

[^{18}]

Healthy Caucasian males and nonpregnant women, low fat meal

1942

8 (4/4)

20.3*

1.14*

716*

NCA

[^{16}]

Healthy Caucasian males and nonpregnant women, high fat meal  1942  8 (4/4)  20.9*  0.60*  365*  NCA  [^{16}] 
CL/F is the apparent elimination clearance, t_{1/2} is the elimination halflife, V_{D}/F is the apparent volume of distribution, Pop PK represents a population pharmacokinetic analysis and NCA represents a noncompartmental analysis. Age is given as a range or (†) as mean ± standard deviation. Other parameters are given as median or as mean when indicated (*).
Article Categories:
Keywords: Malaria, Piperaquine, Pregnancy, Population pharmacokinetics, Nonlinear mixedeffects modelling. 
Previous Document: Patients with low back pain differ from those who also have leg pain or signs of nerve root involvem...
Next Document: The use of dermal autograft as an adjunct to breast reconstruction with tissue expanders.