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BJA Advance Access originally published online on February 26, 2008
British Journal of Anaesthesia 2008 100(4):525-532; doi:10.1093/bja/aen019
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© The Board of Management and Trustees of the British Journal of Anaesthesia 2008. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org

Covariates of tramadol disposition in the first months of life

K. Allegaert1,*, J. N. van den Anker1, J. N. de Hoon2, R. H. N. van Schaik3, A. Debeer1, D. Tibboel4, G. Naulaers1 and B. J. Anderson5

1 Neonatal Intensive Care Unit, Division of Woman and Child, University Hospitals Leuven, Campus Gasthuisberg, Herestraat 49, 3000 Leuven, Belgium
2 Center for Clinical Pharmacology, University Hospitals Leuven, Campus Gasthuisberg, Leuven, Belgium
3 Department of Clinical Chemistry, Erasmus Medical Center, Rotterdam, The Netherlands
4 Department of Paediatric Surgery, Erasmus Medical Center, Sophia’s Children Hospital, Rotterdam, The Netherlands
5 Department of Anaesthesiology, University of Auckland, Auckland, New Zealand

* Corresponding author. E-mail: karel.allegaert{at}uz.kuleuven.ac.be

Accepted for publication January 10, 2008.


    Abstract
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Funding
 Acknowledgements
 References
 
Background: Data on contributors to between-individual variability in overall tramadol clearance and O-demethyl tramadol (M1) formation in preterm neonates and young infants are limited.

Methods: A population pharmacokinetic analysis of tramadol and M1 was undertaken using non-linear mixed effects model. Covariate analysis included weight, postmenstrual age (PMA), postnatal age (PNA), creatinaemia, (cardiac) surgery, cardiac defect, and cytochrome (CYP)2D6 polymorphisms, classified by CYP2D6 activity score.

Results: In 57 patients (25–54 weeks PMA), 593 observations were collected. Tramadol clearance was described using a two-compartment, zero-order input, first-order elimination linear model. An additional compartment was used to characterize M1. Tramadol clearance at term age was 17.1 litre h–1 (70 kg)–1 (CV, 37.2%). Size (37.8%) and PMA (27.3%) contribute to this variability. M1 formation clearance (CL2M1, i.e. the contribution of M1 synthesis to M clearance) was 4.11 litre h–1 (70 kg)–1 (CV, 110.9%) at term age. Size and PMA were the major contributors to the variability (52.7%); the CYP2D6 activity score contributes 6.4% to this variability.

Conclusions: Overall tramadol clearance estimates confirm earlier reports while CL2M1 variability is explained by size, PMA, and CYP2D6 polymorphisms. The CL2M1 is very low in preterm neonates, irrespective of the CYP2D6 polymorphism with subsequent rapid maturation. The slope of this increase depends on the CYP2D6 activity score. The current pharmacokinetic observations suggest a limited µ-opioid receptor-mediated analgesic effect of M1 in preterm neonates and a potential CYP2D6 polymorphism-dependent effect beyond term age.

Keywords: enzymes, cytochrome P450; neonates; pain, paediatric


    Introduction
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Funding
 Acknowledgements
 References
 
Tramadol is an aminocyclohexanol derivative or 4-phenyl piperidine analogue of codeine. Its analgesic effect is mediated through noradrenaline re-uptake inhibition, increased release of serotonin, and decreased re-uptake of serotonin in the spinal cord. It has also a weak µ-opioid receptor effect with an opioid-receptor affinity that is 6000 times weaker than morphine. Tramadol (M) is metabolized by either O-demethylation in the liver (CYP2D6) to O-demethyl tramadol (M1) or by N-demethylation (CYP3A) to N-demethyl tramadol (M2). The M2 metabolite is of no pharmacodynamic relevance, but the O-demethyl tramadol (+)-M1 metabolite has a µ-opioid-receptor affinity approximately 200 times larger than tramadol.1 As CYP2D6 polymorphisms influence (+)-M1 production with subsequent differences in level of analgesia, CYP2D6 polymorphisms contribute to the variability in tramadol pharmacokinetics and pharmacodynamics in adults and children.24 Consequently, phenotypic cytochrome, (CYP)2D6 iso-enzyme, activity is important for the µ-opioid receptor-mediated analgesic effect although pharmacodynamic observations in (pre)term neonates and young infants and its link with phenotypic 2D6 activity remain unreported.

Phenotypic variation in drug metabolism depends on constitutional, genetic, and environmental factors, but in early life, it mainly reflects the iso-enzyme-specific ontogeny.5 On the basis of observations on in vivo dextromethorphan metabolism in healthy infants and tramadol metabolism in ill (pre)term neonates and young infants, it has been documented that phenotypic activity of N-demethylation (CYP3A) displays a slower increase to adult activity compared with O-demethylation (CYP2D6).6 7 Knowledge about in vivo maturation of phenotypic CYP2D6 activity and the impact of various contributors such as age, size, disease characteristics, and CYP2D6 polymorphisms in early human life is still incomplete.5

No relationship between M1 formation clearance (CL2M1, i.e. M clearance through M1 synthesis) and postmenstrual age (PMA) could be determined in an earlier study that analysed the observations from 20 neonates, 9 children, and 20 adults using a population approach.8 This inability to discern a relationship between CL2M1 and PMA may be because of limited number of observations or because of complex interplay of different covariables (size, CYP2D6 polymorphisms, and disease characteristics) on CL2M1. Therefore, the current investigation explores the impact of size, age, renal function, co-morbidity, and CYP2D6 polymorphisms on tramadol disposition in an extended cohort of critically ill (pre)term neonates and young infants given i.v. tramadol for clinical purposes.


    Methods
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Funding
 Acknowledgements
 References
 
Clinical characteristics
Approval for the study protocol was granted by the local ethical board of the University Hospital, Leuven, Belgium. Patients were included after informed written consent from parents was obtained. The decision to prescribe tramadol (Contramal®, Grünenthal, Aachen, Germany) was made by the attending neonatologist based on standardized evaluation and treatment of pain after a variety of surgical or medical interventions.9 Tramadol was administered by i.v. route [loading dose 2–3 mg kg–1 over >30 min, followed by continuous administration of tramadol hydrochloride 5–8 mg kg–1 (24 h)–1].

Clinical characteristics and indications to initiate treatment were prospectively registered. Postnatal age (PNA) and PMA at initiation of treatment, indication (e.g. cardiac or non-cardiac surgery, medical—cardiac or pain), and renal function (creatinaemia) were recorded. Blood samples (0.2 ml) were obtained from an arterial line at 0.5, 1, 2, 4, 6, 9, 12, 15, 18, and 24 h after initiation of i.v. tramadol. In the smallest infants, the number of samples was lower because the cumulative blood volume collected in a single infant was limited to 1 ml kg–1. Blood samples were centrifuged (3 min, 10 000 rpm, 4°C) shortly after collection, and plasma samples were stored at –20°C until analysis. Concentration–time profiles of 20 out of the 57 neonates and young infants currently included were reported in the literature earlier.8

Tramadol and O-demethyl tramadol assay
Plasma concentrations of tramadol and O-demethyl tramadol were determined by high-performance liquid chromatography (HPLC) in low-volume plasma samples based on modifications and improvements applied to earlier described methods.1012 To 0.1 ml of plasma, 10 µl of standard dilutions of tramadol and O-demethyl tramadol (to obtain a standard range from 0.05 to 5 µg ml–1), 10 µl of the internal standard D617 [2-(3,4-dimethoxy-phenyl)-2-isopropyl-5-methylamino-pentanenitrile, metabolite of verapamil], 0.2 ml of 0.2 M sodium carbonate buffer, pH 10.5, and 2 ml of tert-butyl-methylether were added.

After shaking for 10 min and centrifuging (1286g) for 5 min at 4°C, the organic layer was transferred to conical glass tubes. After evaporation of tert-butyl-methylether at 40°C in a water bath with an air stream, the residues were dissolved in 200 µl of the mobile phase. These mixtures were transferred to Eppendorf tubes (1.5 ml), centrifuged at 9300g for 8 min, and finally transferred into microvials for automatic injection. A Waters 600E pump was used in combination with a Merck-Hitachi fluorescence detector F-1000, set at excitation and emission wavelengths of 280 and 310 nm, respectively. A stainless steel column (250x4.6 mm ID) packed with Spherisorb CN 5µ (Alltech Associates, Deerfield, IL, USA) was used. The mobile phase consisted of a mixture of acetonitrile and 15 mM potassium phosphate buffer, pH 4.0, with 0.05% triethylamine (10/90, v/v) and pumped at a flow rate of 0.9 ml min–1. A good chromatographic separation between tramadol and O-demethyl tramadol was obtained. The linearity of the calibration curves for tramadol and O-demethyl tramadol in plasma was found in the range of 0.05–5 µg ml–1 (y=–0.018+2.05x, r=0.9921 and y=0.031+3.06x, r=0.9949, respectively). The lower limit of quantification for tramadol and O-demethyl tramadol was 0.05 µg ml–1, being the lowest concentration of the standard curve with a coefficient of variation <20%.8

CYP2D6 polymorphisms
Genomic DNA was isolated from 200 µl EDTA whole blood using MagNaPure LC (Roche Diagnostics GmbH, Mannheim, Germany). The CYP2D6 2549delA variant (*3 allele, TaqMan allelic discrimination assay 4312554 (Applied Biosystems), the 1846G>A single nucleotide polymorphism (SNP) (*4 allele, DME C_27102431), the 1707delT variant (*6 allele, DME C_32407243), the 100C>T SNP (*10 allele, DME C_11484460), and the 2988G>A SNP (*41 allele, DME C_34816116) were determined using Taqman allelic discrimination assays (DME type) on a ABI Prism 7000 sequence detection system. All assays were performed on 1 ng genomic DNA, in a total reaction volume of 12.5 µl with Taqman Universal Master Mix, CYP2D6-specific primers and two allele-specific minor groove binding (MGB) probes labelled with either fluorescent dyes VIC or FAM, complementary to either the wild type or the variant sequence. The thermal profile consisted of an initial denaturation step at 95°C for 15 min, followed by 50 cycles of denaturation at 92°C for 15 s and annealing plus extension at 60°C for 1 min. Genotypes were scored by measuring allele-specific fluorescence using the SDS 2.2.2 software for allelic discrimination (Applied Biosystems). The CYP2D6*9 (2613delAGA) was determined based on the PCR–RFLP method by Gaedigk and colleagues.13 The CYP2D6*5 (gene deletion) was determined based on the method of Hersberger and colleagues,14 and the CYP2D6 gene duplication was analysed according to Lovlie and colleagues.15 All patients in whom no specific SNP (*3,*4,*5,*6,*9,*10,*41,*1xN) was detected were assigned to the extensive metabolizer group [i.e. assumed to have an CYP2D6 activity score of 2 (*1/*1)]. Genotyping analyses were classified based on the ‘CYP2D6 activity score’ (score of 0, 0.5, 1, 1.5, 2, or >2).6 16

Population pharmacokinetics
A two-compartment (central and peripheral) zero-order input, first-order elimination linear model was used to describe the parent drug (tramadol) disposition. An additional compartment was used to represent that of the O-demethyl tramadol (M1) metabolite. This model is shown in Figure 1. Tramadol (M) is either cleared through M1 synthesis (CL2M1) or by other routes (CLother). The volume of distribution of the O-demethyl tramadol metabolite (VM1) cannot be identified with the current study design, but a value of 224 litre (70 kg)–1, reported by Campanero and colleagues, was assigned.10 Population parameter estimates were obtained using non-linear mixed effects modelling (NONMEM V, Globomax LLC, Hanover, MD, USA).17 The population parameter variability in model parameters was modelled by a proportional variance model. An additive and a proportional term characterized the residual unknown variability. The population typical parameters, between subject variance and residual variance, were estimated using the first-order conditional interaction estimate method using ADVAN6 TOL5 (differential equation solver) of NONMEM V. Convergence criterion was three significant digits.


Figure 1
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Fig 1 The pharmacokinetic model. A two-compartment (central, peripheral) linear disposition model was used to fit the parent drug. An additional compartment for the M1 metabolite was linked to the central compartment by its formation clearance (CL2M1). M1 metabolite volume of distribution was fixed equivalent to the literature estimate of 224 litre 70 kg–1. Total body clearance of tramadol is the sum of CLother and CL2M1. CLM1 is the clearance of the M1 metabolite.

 
Parameter values were standardized for a body weight of 70 kg using allometric models in order to compare neonatal estimates with those from adults.18 19


Formula

where Wi is the weight in the ith individual. Allometric scaling has a strong theoretical and empirical basis with a PWR exponent of 0.75 for clearance and 1 for distribution volume.2022 Covariate analysis included an exponential model investigating age-related changes for parent tramadol clearance, CL2M1, and M1 elimination clearance.19


Formula

where FPMA is the factor for PMA (in weeks) and is centred on 40 weeks PMA (full-term gestation). SLPCL is a parameter describing the changes in clearance with PMA. In addition, the impact of serum creatinine (SCr, µmol litre–1) on maturation of CLM was investigated. Creatinine clearance (CLcr, litre h–1) was predicted using PMA as a covariate to predict creatinine production rate (CPR) with a scaling constant (Kage) for age. This is based on assuming a CPR of 516 µmol h–1 in a 70 kg, 40-yr-old male.23


Formula

Disease status (e.g. medical or surgical indication to initiate administration, either cardiac or non-cardiac surgery, associated cardiac defect) was handled as a categorical demographic covariate. Six genomic activity states were recorded (CYP=0, 0.5, 1, 1.5, 2, or 3) and activity was assumed to increase (SLPCYP is slope function) linearly,



Formula

The quality of fit of the pharmacokinetic models to the data was assessed by visual examination of plots of observed vs predicted concentrations. Models were nested and an improvement in the objective function was referred to the {chi}2 distribution to assess the significance [e.g. an objective function change ({Delta}OBJ) of 3.84, significant at {alpha}=0.05 was used for probing while an {alpha}<0.01 was considered significant].


    Results
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Funding
 Acknowledgements
 References
 
Patient characteristics and indications for administration of tramadol in neonates and young infants are presented in Table 1. Information on CYP2D6 polymorphisms were collected in 53 of 57 patients. Data on the incidence of the individual CYP2D6 polymorphisms documented and the associated CYP2D6 activity score are provided in Table 2. There were 593 observations from 57 neonates available for the analysis.


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Table 1 Patient characteristics of 57 neonates and young infants given tramadol. Data are reported by median and range or by absolute numbers

 


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Table 2 Individual CYP2D6 polymorphisms and the CYP2D6 activity score in the current cohort.6 16 Information on CYP2D6 polymorphisms could be collected in 53 of 57 patients

 
The initial analysis concerned only the parent compound (i.e. total tramadol clearance, 297 observations from 57 neonates) without investigation of the M1 metabolite. Population parameter estimates of tramadol disposition are shown in Tables 3 and 4. Only size and age (PMA for CL, PNA for V1) influenced the CL and V estimates. The objective function for the final model was –1311.161. Addition of covariates for either the CYP2D6 activity score (SLPCYP, OBJ, –1313.145), cardiac surgery (OBJ, –1311.177), or any surgery (OBJ, –1313.189) did not result in a significantly better model. Total tramadol clearance had a BSV of 37.2%. The difference between BSV without covariates and with covariates is a measure of the predictable decrease in BSV as a result of covariates. The {omega}2 estimates for the different components contributing to variability are shown in Table 4. The ratio of the BSV predictable from covariates (BSVP2) to the total population parameter variance obtained without covariate analysis (PPV2) indicates the relative importance of covariate information. For example, the ratio of 0.747 achieved in this current study for clearance indicates that 74.7% of the overall variance in clearance is predictable from the covariate information. The two major contributors to this variability were size (37.8%) and PMA (27.3%), without any additional impact of disease characteristics or CYP2D6 polymorphism (Table 4).


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Table 3 Standardized tramadol population pharmacokinetic parameter estimates for neonates at PMA 40 weeks (PPV is the population parameter variability, SE is the standard error of the structural estimate) Central volume (V1), peripheral volume (V2), clearance (CL), and intercompartment clearance (Q).

Table 3
CLstd is the population estimates for CL of a neonate at 40 weeks PMA and standardized to a 70 kg person using an allometric model; and SLPcl and SLPvol are slope parameters estimating magnitude of CL or V1 increases with age

 


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Table 4 Impact of each covariate on CL when added sequentially to the model. *Assumed from no covariate model estimate. PPVt2 is the total population parameter variability estimated without covariate analysis, BSVP2 is the between-subject variability (BSV) predictable from covariates, and BSVR is the random BSV estimated on a parameter when covariate analysis is included. BSVP was computed from PPVt2–BSVR2. The ratio of the BSV predictable from covariates (BSVP) to the total population parameter variability obtained without covariate analysis (PPVt2) (i.e. BSVP2/PPVt2) indicates the fraction of the total variability in the parameter that is predictable from covariates. OBJ is the objective function value measuring the goodness of fit

 
Population parameter estimates for metabolite investigation are shown in Tables 5 and 6. Additive errors (0.002, 0.006 µg litre–1) and proportional errors (0.12, 0.09%) were similar for both parent and metabolite compounds. Quality of the fit for both the parent drug and M1 metabolite are shown in Figures 2 and 3, respectively. The CL2M1, tramadol clearance by other routes (CLother), and M1 metabolite clearance (CLM1) all increased with PMA. There was no additional effect from PNA as a covariate. PNA did not affect V1 in this analysis ({Delta}OBJ, 5.369). Neither tramadol clearance by other routes (CLother) nor CL2M1 was influenced by surgery (any type) ({Delta}OBJ, 3.027) or cardiac surgery ({Delta}OBJ, 4.933). The addition of creatinine clearance to CLM1 or CLother had no additional impact over that predicted by PMA alone.


Figure 2
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Fig 2 Quality of fit for parent tramadol in neonates over the study time (x-axes, h). The y-axes display the ratio of measured concentrations to those predicted from the pharmacokinetic analysis. (A) Values from the NONMEM post hoc step based on values of the parameters for the specific individual. (B) Values from the population parameters.

 


Figure 3
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Fig 3 Quality of fit for M1 metabolite in neonates over the study time (x-axes, h). The y-axes display the ratio of measured concentrations to those predicted from the pharmacokinetic analysis. (A) Values from the NONMEM post hoc step based on values of the parameters for the specific individual. (B) Values from the population parameters.

 


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Table 5 Standardized tramadol population pharmacokinetic parameter estimates for neonates at PMA 40 weeks (PPV is the population parameter variability, SE is the standard error of the structural estimate). Central volume (V1), peripheral volume (V2), clearance (CL), and intercompartment clearance (Q)

 


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Table 6 Covariate estimates.

Table 6

Table 6
where CL2M1std is the population estimates for CL2M1 of a neonate at 40 weeks PMA and standardized to a 70 kg person using an allometric model; and SLPcl is a slope parameter estimating magnitude of clearance increase with age. SLPCYP is a slope function for genotype that was applied to CL2M1

 
In this cohort, only one patient was documented to have a CYP2D6 activity score of 0 (Table 1). The M1 metabolite could not be quantified (below the LLQ, i.e. 0.05 µg ml–1). In this patient, a scaling factor of 0 was applied to this CYP2D6 activity score of 0 ({Delta}OBJ 6.954). The CL2M1 had a large BSV of 110.9%. Size and PMA were the major contributors to this variability (52.7%) while the CYP2D6 activity score contributed 6.4% in this population. We were able to demonstrate PMA-related changes in CL2M1 for genotypes CYP 0.5-3 using a slope function (SLPCYP, {Delta}OBJ, 17.311) (Fig. 4).


Figure 4
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Fig 4 M1 metabolite formation clearance increases with postmenstrual age. The population trend of M1 metabolic formation is highest in those neonates grouped as CYP3 (i.e. having a CYP2D6 activity score of 3) and is higher in neonates grouped as CYP2 compared with those grouped as CYP1 or CYP 0.5.

 

    Discussion
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Funding
 Acknowledgements
 References
 
Estimated total tramadol clearance increased with PMA and was 17.1 litre h–1 (70 kg)–1 at term gestation, consistent with both the clearance and rapid clearance maturation estimated previously in a smaller cohort of neonates.8 The current study reveals that 74.7% of the overall variance in tramadol clearance was predictable from covariate information in neonates and young infants. The two major contributors to this variability were size (37.8%) and PMA (27.3%), without additional impact of disease characteristics or CYP2D6 polymorphisms. The BSV of tramadol clearance was 37.2% in neonates, higher than estimated in children (28%), but less than estimated in adults (48.6%).2 24 CYP2D6 polymorphisms, gender, and age have been suggested as covariates contributing to this variability in adults.24 Maturation of clearance pathways (i.e. ontogeny) likely contributes to the increased variability observed in neonates compared with children.5

CL2M1 (i.e. the contribution of M1 synthesis to M clearance) was 4.11 litre h–1 (70 kg)–1 (CV 110.9%) at term age. Size and PMA were the major contributors (52.7%). CYP2D6 polymorphisms had no effect on total tramadol clearance, but contributed 6.4% covariate information for CL2M1. These estimates are consistent with immaturity of the cytochrome P450 enzyme systems in perinatal life.5 2527 Although complete temporal relationship information of CYP2D6 activity during development still is unknown, CYP2D6 ontogeny develops rapidly since CYP2D6 activity was detectable and concordant with genotype by 2 weeks of age, equivalent to 42 weeks PMA after oral dextromethorphan administration.6 In contrast, N-demethylation (CYP3A) developed significantly slower in the first year of life.6 7 It is to be anticipated that renal elimination, rather than metabolic clearance, plays a dominant role in the clearance of tramadol in early life. Of the total amount of tramadol administered in 25 neonates and young infants, 34.5 (SD 6.1)% was retrieved in the urine in the first 24 h. This mainly comprised the parent compound tramadol 79 (SD 18)%, M1 contributed 10 (SD 17)% and M2 contributed 3 (SD 3.4)%.12

CL2M1 reflects phenotypic O-demethylation activity and, therefore, provides us information on the covariates of phenotypic O-demethylation activity in the first months of life. In addition, it is also of pharmacodynamic relevance because the M1 metabolite has a µ-opioid affinity approximately 200 times larger than tramadol. The formation clearance of the CL2M1 had a large BSV of 110.9%, much higher than estimated in children (38%).2

Age-dependent increase in CL2M1 was documented in this study, and its increase related to the CYP2D6 genotype. CL2M1 in extreme and preterm neonates was very low, independent of the CYP2D6 genotype while from term age onwards, CYP2D6 polymorphisms become a relevant covariate of the O-demethylation activity observed (Fig. 4). This is consistent with the very low or undetectable concentrations of hepatic CYP2D6 protein in human foetal hepatic tissues.25 Drug metabolism may also depend on disease characteristics. Cytochrome-mediated drug metabolism is reduced in children with sepsis-induced multiple organ failure.28 Similarly, neonates and infants who have undergone cardiac surgery are reported to display reduced clearance of morphine compared with those who have not undergone surgery.29 However, no significant impact of surgery (any type) or cardiac surgery on either total clearance or CL2M1 was noted in this current cohort.

M1 formation is also of pharmacodynamic relevance. In adults, the impact of CYP2D6 polymorphisms on the level of analgesia as a result of BSV in M1 formation has been repeatedly documented.3 4 In early neonatal life, this phenotypic M1 formation is the final result of both ontogeny [i.e. age-dependent maturation and pharmacogenetics (CYP2D6 activity score)].

Children have the ability to produce enough M1 to achieve proper pain relief: steady-state plasma concentration levels of tramadol and M1 of 100 and 15 µg litre–1 were associated with a 95% probability of adequate pain relief after general surgery in children (2–8 yr).2 Pharmacokinetic estimates in the current paper are similar to the earlier estimates, confirming the adequacy of suggested dosing schedules required to achieve a target concentration of 300 µg litre–1.1 8 However, based on the current observations, we might anticipate reduced effectiveness of this drug in preterm neonates because of lack or very limited analgesic contribution from M1 production. It is anticipated that in term neonates and beyond, CYP2D6 polymorphisms will have greater analgesic relevance. Whether a higher dose of tramadol or co-administration with acetaminophen will result in better balanced analgesia with acceptable side-effects in (pre)term neonates remains to be investigated.30 31 Prospective studies on pharmacodynamics and the relation between pharmacokinetics and -dynamics in this specific population are needed, but it can at least be anticipated that both age and pharmacogenetics will contribute to the BSV.

In conclusion, tramadol clearance and the contributors of its variability confirm an earlier report in neonates, whereas CL2M1 displays important BSV. This variability is, in part, explained by size, PMA, and CYP2D6 activity score. M1 formation clearance is very low in preterm neonates, independent of the CYP2D6 activity score with subsequent rapid increase in phenotypic O-demethylation activity from birth onwards. The slope of this increase depends on the CYP2D6 polymorphisms. The current observations suggest a limited µ-opioid receptor-mediated analgesic effect of M1 in preterm neonates and a CYP2D6 polymorphism dependent effect in term neonates and beyond.


    Funding
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Funding
 Acknowledgements
 References
 
The clinical research of K.A. is supported by the Clinical Research Fund of the University Hospital, Leuven, Belgium. The clinical research of J.N. van den Anker is supported by grants HD45 993 (NICHD) and RR19 729 (NCRR).


    Acknowledgements
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Funding
 Acknowledgements
 References
 
We greatly acknowledge the analytic skills and contributions of Prof. Rene Verbesselt of the Center for Clinical Pharmacology of the University Hospitals Leuven, Belgium.


    References
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Funding
 Acknowledgements
 References
 
1 Grond S, Sablotzki A. Clinical pharmacology of tramadol. Clin Pharmacokinet (2004) 43:879–923.[CrossRef][Web of Science][Medline]

2 Garrido MJ, Habre W, Rombout F, et al. Population pharmacokinetic and pharmacodynamic modelling of the analgesic effects of tramadol in pediatrics. Pharm Res (2006) 23:2014–23.[CrossRef][Medline]

3 Stamer UM, Lehnen K, Höthker F, et al. Impact of CYP2D6 genotype on postoperative tramadol analgesia. Pain (2003) 105:231–8.[CrossRef][Web of Science][Medline]

4 Poulsen L, Arendt-Nielsen L, Brosen K, et al. The hypoalgesic effect of tramadol in relation to CYP2D6. Clin Pharmacol Ther (1996) 60:636–44.[CrossRef][Web of Science][Medline]

5 Kearns GL, Abdel-Rahman SM, Alander SW, et al. Developmental pharmacology: drug disposition, action, and therapy in infants and children. N Engl J Med (2003) 349:1157–67.[Free Full Text]

6 Blake MJ, Gaedigk A, Pearce RE, et al. Ontogeny of dextromethorphan O- and N-demethylation in the first year of life. Clin Pharmacol Ther (2007) 81:510–6.[CrossRef][Medline]

7 Allegaert K, van den Anker JN, Debeer A, et al. Maturational changes in the in vivo activity of CYP3A4 in the first months of life. Int J Clin Pharmacol Ther (2006) 44:303–8.[Medline]

8 Allegaert K, Anderson B, Verbesselt R, et al. Tramadol disposition in the very young: an attempt to assess in vivo cytochrome P4502D6 activity. Br J Anaesth (2005) 95:231–9.[Abstract/Free Full Text]

9 Allegaert K, Tibboel D, Naulaers G, et al. Systematic evaluation of pain in neonates: effect on the number of intravenous analgesics prescribed. Eur J Clin Pharmacol (2003) 59:87–90.[Web of Science][Medline]

10 Campanero MA, Calahorra B, Valle M, et al. Enantiomeric separation of tramadol and its active metabolite in human plasma by chiral high-performance liquid chromatography: application to pharmacokinetic studies. Chirality (1999) 11:272–9.[Medline]

11 Nobilis M, Kopecky J, Kvetina J, et al. High performance liquid chromatographic determination of tramadol and its O-demethylated metabolite in blood plasma. Application to a bioequivalence study in humans. J Chromatogr A (2002) 949:11–22.[CrossRef][Web of Science][Medline]

12 Allegaert K, van den Anker JN, Verbesselt R, et al. O-demethylation of tramadol in the first months of life. Eur J Clin Pharmacol (2005) 61:837–42.[CrossRef][Medline]

13 Gaedigk A, Gotschall RR, Forbes NS, et al. Optimization of cytochrome P450 2D6 (CYP 2D6) phenotype assignment using a genotyping algorithm based on allele frequency data. Pharmacogenetics (1999) 9:669–82.[Web of Science][Medline]

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