Rocuronium pharmacokinetics and pharmacodynamics in the adductor pollicis and masseter muscles.

BACKGROUND: The aim of this study was to characterize the dose-effect relationship of rocuronium at the adductor pollicis and masseter muscles. METHODS: Ten, ASA I, adult patients, received a bolus dose of rocuronium 0.3 mg/kg during propofol based anesthesia. Train-of-four (TOF) was simultaneously monitored at the masseter and the adductor pollicis muscles until recovery. Rocuronium arterial serum concentrations were measured during 120 min. The first twitch of the TOF response was used to characterize the time-effect profile of both muscles using pharmacokinetic-pharmacodynamic analysis in NONMEM. A decrease in NONMEM objective function (∆OFV) of 3.84 points for an added parameter was considered significant at the 0.05 level. RESULTS: Onset time at the masseter (mean ± SD, 1.5 ± 0.9 min) was faster than at the adductor pollicis (2.7 ± 1.4 min, P < 0.05). Recovery, measured as the time to TOF ratio = 0.9 was similar between muscles 29.9 ± 6.7 (adductor pollicis) vs. 29.3 ± 8.1 (masseter). (P = 0.77). The estimated pharmacodynamic parameters [mean (95% CI)] of the adductor pollicis muscle and the masseter muscle were; plasma effect-site equilibration half-time (teq) 3.25 (2.34, 3.69) min vs. 2.86 (1.83, 3.29) min, (∆OFV 383.665); Ce50 of 1.24 (1.13, 1.56) mg/l vs. 1.19 (1.00, 1.21) mg/l, (∆OFV 184.284); Hill coefficient of 3.97 (3.82, 5.62) vs. 4.68 (3.83, 5.71), (∆OFV 78.906). CONCLUSIONS: We found that the masseter muscle has faster onset of blockade and similar recovery profile than adductor pollicis muscle. These findings were best, explained by a faster plasma effect-site equilibration of the masseter muscle to rocuronium.

Pharmacometrics: opportunity for reducing disease burden in the developing world: the case of Africa.

Pharmacometricians are virtually nonexistent in Africa and the developing world. The unrelenting burden of infectious diseases, which are often treated using medicines with narrow effectiveness and safety dose ranges, and the growing prevalence and recognition of non-communicable diseases represent significant threats for the patients, although affording an opportunity for advancing science. This article outlines the case for pharmacometricians to redirect their expertise to focus on the disease burden affecting the developing world.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e69; doi:10.1038/psp.2013.45; published online 28 August 2013.

Influence of obesity on propofol pharmacokinetics: derivation of a pharmacokinetic model.

BACKGROUND: The objective of this study was to develop a pharmacokinetic (PK) model to characterize the influence of obesity on propofol PK parameters. METHODS: Nineteen obese ASA II patients undergoing bariatric surgery were studied. Patients received propofol 2 mg kg(-1) bolus dose followed by a 5-20-40-120 min, 10-8-6-5 mg kg(-1) h(-1) infusion. Arterial blood samples were withdrawn at 1, 3, 5 min after induction, every 10-20 min during propofol infusion, and every 10-30 min for 2 h after stopping the propofol infusion. Arterial samples were processed by high-performance liquid chromatography. Time-concentration data profiles from this study were pooled with data from two other propofol PK studies available at http://www.opentci.org. Population PK modelling was performed using non-linear mixed effects model. RESULTS: The study involved 19 obese adults who contributed 163 observations. The pooled analysis involved 51 patients (weight 93 sd 24 kg, range 44-160 kg; age 46 sd 16 yr, range 25-81 yr; BMI 33 sd 9 kg m(-2), range 16-52 kg m(-2)). A three-compartment model was used to investigate propofol PK. An allometric size model using total body weight (TBW) was superior to all other models investigated (linear TBW, free fat mass, lean body weight, normal fat mass) for all clearance parameters. Variability in V2 and Q2 was reduced by a function showing a decrease in both parameters with age. CONCLUSIONS: We have derived a population PK model using obese and non-obese data to characterize propofol PK over a wide range of body weights. An allometric model using TBW as the size descriptor of volumes and clearances was superior to other size descriptors to characterize propofol PK in obese patients.

Morphine pharmacokinetics and pharmacodynamics in preterm and term neonates: secondary results from the NEOPAIN trial.

BACKGROUND: Relationships between plasma morphine concentrations and neonatal responses to endotracheal tube (ETT) suctioning are unknown in preterm neonates. METHODS: Ventilated preterm neonates (n=898) from 16 centres were randomly assigned to placebo (n=449) or morphine (n=449). After an i.v. loading dose (100 microg kg(-1)), morphine infusions [23-26 weeks postmenstrual age (PMA) 10 microg kg(-1) h(-1); 27-29 weeks 20 microg kg(-1) h(-1); and 30-32 weeks 30 microg kg(-1) h(-1)] were established for a maximum of 14 days. Open-label morphine (20-100 microg kg(-1)) was given for pain or agitation. Morphine assay and neonatal response to ETT suctioning was measured at 20-28 and 70-76 h after starting the drug infusion and at 10-14 h after discontinuation of the study drug. The concentration-effect response was investigated using non-linear mixed effects models. RESULTS: A total of 5119 data points (1598 measured morphine concentrations and 3521 effect measures) were available from 875 neonates for analysis. Clearance was 50% that of the mature value at 54.2 weeks PMA (CLmat(50)) and increased from 2.05 litre h(-1) 70 kg(-1) at 24 weeks PMA to 6.04 litre h(-1) 70 kg(-1) at 32 weeks PMA. The volume of distribution in preterm neonates was 190 litre 70 kg(-1) (CV 51%) and did not change with age. There was no relationship between morphine concentrations (range 0-440 microg litre(-1)) and heart rate changes associated with ETT suctioning or with the Premature Infant Pain Profile. CONCLUSIONS: A sigmoid curve describing maturation of morphine clearance is moved to the right in preterm neonates and volume of distribution is increased compared with term neonates. Morphine does not alter the neonatal response to ETT suctioning.

Mechanism-based concepts of size and maturity in pharmacokinetics.

Growth and development can be investigated using readily observable demographic factors such as weight and age. Size is the primary covariate and can be referenced to a 70-kg person with allometry using a coefficient of 0.75 for clearance and 1 for volume. The use of these coefficients is supported by fractal geometric concepts and observations from diverse areas in biology. Fat free mass (FFM) might be expected to do better than total body weight when there are wide variations in fat affecting body composition. Clearance pathways develop in the fetus before birth. The use of postnatal age as a descriptor of maturation is unsatisfactory because birth may occur prematurely; therefore postmenstrual age is a superior predictor of elimination function. A sigmoid E(max) model (Hill equation) describes gradual maturation of clearance in early life leading to a mature adult clearance achieved at a later age.

Developmental pharmacokinetics of morphine and its metabolites in neonates, infants and young children.

BACKGROUND: Descriptions of the pharmacokinetics and metabolism of morphine and its metabolites in young children are scant. Previous studies have not differentiated the effects of size from those related to age during infancy. METHODS: Postoperative children 0-3 yr old were given an intravenous loading dose of morphine hydrochloride (100 micro g kg(-1) in 2 min) followed by either an intravenous morphine infusion of 10 micro g h(-1) kg(-1) (n=92) or 3-hourly intravenous morphine boluses of 30 micro g kg(-1) (n=92). Additional morphine (5 micro g kg(-1)) every 10 min was given if the visual analogue (VAS, 0-10) pain score was >/=4. Arterial blood (1.4 ml) was sampled within 5 min of the loading dose and at 6, 12 and 24 h for morphine, morphine-3-glucuronide (M3G) and morphine-6-glucuronide (M6G). The disposition of morphine and formation clearances of morphine base to its glucuronide metabolites and their elimination clearances were estimated using non-linear mixed effects models. RESULTS: The analysis used 1856 concentration observations from 184 subjects. Population parameter estimates and their variability (%) for a one-compartment, first-order elimination model were as follows: volume of distribution 136 (59.3) litres, formation clearance to M3G 64.3 (58.8) litres h(-1), formation clearance to M6G 3.63 (82.2) litres h(-1), morphine clearance by other routes 3.12 litres h(-1) per 70 kg, elimination clearance of M3G 17.4 (43.0) litres h(-1), elimination clearance of M6G 5.8 (73.8) litres h(-1). All parameters are standardized to a 70 kg person using allometric 3/4 power models and reflect fully mature adult values. The volume of distribution increased exponentially with a maturation half-life of 26 days from 83 litres per 70 kg at birth; formation clearance to M3G and M6G increased with a maturation half-life of 88.3 days from 10.8 and 0.61 litres h(-1) per 70 kg respectively at birth. Metabolite formation decreased with increased serum bilirubin concentration. Metabolite clearance increased with age (maturation half-life 129 days), and appeared to be similar to that described for glomerular filtration rate maturation in infants. CONCLUSION: M3G is the predominant metabolite of morphine in young children and total body morphine clearance is 80% that of adult values by 6 months. A mean steady-state serum concentration of 10 ng ml(-1) can be achieved in children after non-cardiac surgery in an intensive care unit with a morphine hydrochloride infusion of 5 micro g h(-1) kg(-1) at birth (term neonates), 8.5 micro g h(-1) kg(-1) at 1 month, 13.5 micro g h(-1) kg(-1) at 3 months and 18 micro g h(-1) kg(-1) at 1 year and 16 micro g h(-1) kg(-1) for 1- to 3-yr-old children.

Population PKPD modelling of the long-term hypoglycaemic effect of gliclazide given as a once-a-day modified release (MR) formulation.

AIMS: To study the relationship between the pharmacokinetics (PK) of gliclazide and its long-term pharmacodynamic (PD) effect in a large population of Type 2 diabetic patients and to identify factors predicting intersubject variability. METHODS: A PKPD database of 634 Type 2 diabetic patients with a total of 5,258 fasting plasma glucose (FPG) samples was built up from the data collected during the clinical development of a modified release formulation of gliclazide (gliclazide MR). The PKPD analysis used a nonlinear mixed effect modelling approach. A mixture model was used to identify patients with a FPG response to treatment. In patients identified as responders, the decrease in FPG was related to gliclazide exposure (AUC) by an Emax relationship. An effect compartment was used to describe the link between PK and PD. A linear disease-progression model was used to assess the glycaemic deterioration observable over several months of treatment. Simulations were performed to evaluate the predictive performance of the PKPD model and to illustrate the time course of the antidiabetic effect of gliclazide MR. RESULTS: Disease state was found to be the main explanatory factor for intersubject variability in response to gliclazide. The percentage of responders to gliclazide, used as monotherapy, increased inversely to the number of classes of antidiabetic agents received prior to entry in the studies. In responders, the initial dose (30 mg) of the gliclazide MR dosing regimen induced half of the maximum hypoglycaemic effect. The equilibration half-life between the PK and PD steady states was 3 weeks (intersubject variability of 84%). The rate of disease progression was 0.84 mmol l(-1) year(-1) (intersubject variability 143%). The PKPD model adequately predicted the FPG profiles of 234 patients who received the current formulation of gliclazide. Simulation of a 1-year parallel dose ranging clinical trial illustrated the influence of dose, time and type of previous antidiabetic treatment on the percentage of patients with clinically significant improvement of blood glucose control. CONCLUSIONS: This population PKPD analysis has characterized the relationship between the exposure to gliclazide and its long-term hypoglycaemic effect, and has established that the intersubject variability in response is mostly related to disease state. These results underline the clinical interest of quickly increasing the dose of gliclazide MR according to the response to treatment in order to achieve effective blood glucose control.