Therapeutic drug monitoring of phenytoin and valproic acid in critically ill patients at Windhoek Central Hospital, Namibia.

Background: Phenytoin and valproic acid, anticonvulsants, have a low therapeutic index and are highly plasma protein bound, mainly to albumin. Hypoalbuminaemia is common in critically ill patients and increases the unbound drug concentration. Thus, monitoring unbound rather than total plasma drug concentrations is recommended to optimise the dosing of these drugs. Objective: This retrospective study determined unbound plasma concentrations of phenytoin and valproic as a more accurate value of drug levels than total plasma drug concentrations. Methods: Total plasma concentrations were retrieved for 56 Intensive Care Unit patients for phenytoin and 93 for valproic acid. Total drug concentrations were converted to unbound concentrations using a serum albumin-based normalising equation. Results: Total phenytoin plasma concentration was below (41.1% of patients), within (46.4%) or above (12.5%) the therapeutic range (10 µg/mL - 20 µg/mL). However, the predicted unbound plasma concentration of phenytoin was above the therapeutic range (1 µg/mL - 2 µg/mL) in the majority of patients (57.1%). For valproic acid, the total plasma concentration of most patients (87.1%) was below the therapeutic range (50 µg/mL - 100 µg/mL); among remaining patients (12.9%), it was within the therapeutic range. In the majority of patients (91.4%), the predicted unbound plasma concentration of valproic acid was between 2.5 µg/mL and 20 µg/mL. Conclusion: The usefulness of monitoring the total phenytoin or valproic acid levels for dose optimisation is limited as it is an inaccurate indicator of a patient's drug therapeutic state. Thus, the unbound plasma drug concentrations should be quantified experimentally or predicted in resource-limited settings.

Performance of the allometric power model in scaling from adult to paediatric antiretroviral dose in children at a Referral Hospital in Windhoek, Namibia.

Background: World Health Organization (WHO) advocates use of weight bands in antiretroviral therapy (ART) guidelines. Allometric scaling could be a more reliable method because it uses a non-linear approach in relating dose to body weight. This study evaluates performance of the allometric ¾ power model in comparison to WHO weight band method in children receiving ART. Methods: Records of children receiving (ABC/3TC) + DTG were reviewed. Paediatric ABC/3TC dose was calculated from the adult dose using the allometric ¾ power model and compared to WHO weight band dose. Results: WHO weight band strategy grouped 50.6% of the children in the 25 kg category and therefore received the adult dose of ABC/3TC (600 mg/300 mg); only 1.1% received this dose with allometric scaling. Mean dose (3.8 tablets) for the WHO weight band dosing method was found to be significantly higher (p<0.0001) than for allometric scaling (1.5 tablets). Conclusions: WHO weight bands may result in the 25 kg weight category receiving a much higher dose leading to ADRs. Using allometric scaling, we recommend a weight band strategy that could improve paediatric ABC/3TC dosing.

Performance of the allometric power model in scaling from adult to paediatric antiretroviral dose in children at a Referral Hospital in Windhoek, Namibia

Background: World Health Organization (WHO) advocates use of weight bands in antiretroviral therapy (ART) guidelines. Allometric scaling could be a more reliable method because it uses a non-linear approach in relating dose to body weight. This study evaluates performance of the allometric ¾ power model in comparison to WHO weight band method in children receiving ART. Methods: Records of children receiving (ABC/3TC) + DTG were reviewed. Paediatric ABC/3TC dose was calculated from the adult dose using the allometric ¾ power model and compared to WHO weight band dose. Results: WHO weight band strategy grouped 50.6% of the children in the 25 kg category and therefore received the adult dose of ABC/3TC (600 mg/300 mg); only 1.1% received this dose with allometric scaling. Mean dose (3.8 tablets) for the WHO weight band dosing method was found to be significantly higher (p<0.0001) than for allometric scaling (1.5 tablets). Conclusions: WHO weight bands may result in the 25 kg weight category receiving a much higher dose leading to ADRs. Using allometric scaling, we recommend a weight band strategy that could improve paediatric ABC/3TC dosing

Should Codeine Still be Considered a WHO Essential Medicine?

Codeine continues to be widely used as an analgesic, antidiarrhoeal and antitussive agent. Its analgesic effect depends on its biotransformation to morphine, a strong opioid. The highly variable biotransformation of codeine to morphine, catalysed by CYP2D6, underlies the pronounced interindividual variability of its analgesic response. Randomized controlled trials have demonstrated that codeine administered alone has the poorest analgesic effect among all commonly used analgesics in acute postoperative pain. Moreover, it is highly unlikely that the low dose of codeine contributes to the pain-relieving effect of the non-opioid component in combination analgesic products. In addition, there is a lack of reliable clinical evidence to support the use of codeine as an antitussive in acute or chronic cough. Codeine use, through its active metabolite morphine, has the potential to lead to abuse and dependence. The World Health Organization (WHO) removed codeine from the essential medicines list for children in 2011. Based on the available information in the scientific literature on the efficacy and safety of codeine, the WHO should seriously consider removing it also from the list of essential medicines for adults, which would be a strong signal for all health professionals to prescribe and dispense codeine with the utmost caution.

Predictors of loss to follow-up of tuberculosis cases under the DOTS programme in Namibia.

BACKGROUND: In Namibia, one out of every 25 cases of tuberculosis (TB) is "lost to follow-up" (LTFU). This has impacted negatively on national efforts to end the disease by 2035. The aim of this study was to determine the trends and predictors of LTFU under the directly observed treatment short-course (DOTS) programme in Namibia. METHODS: The study involved a retrospective longitudinal analysis of a nationwide cohort of TB cases registered under the DOTS programme in Namibia from 2006 to 2015. The trends and predictors of LTFU among cases in the National Electronic TB Register of the National TB and Leprosy Program were respectively determined by interrupted time series and multivariate logistic regression analyses using R-Studio software. RESULTS: Out of 104 203 TB cases, 3775 (3.6%) were LTFU. A quarter (26%) of cases with poor outcomes were due to LTFU. The annual decline in cases of LTFU was significant between the first (2005-2010) and second (2010-2015) medium-term plan period for TB programme implementation (p=0.002). The independent predictors of LTFU were male sex (p=0.004), 15-24 years age group (p=0.03), provider of treatment (p<0.001), intensive phase (p=0.047) and living in border/transit regions (p<0.001). HIV co-infection and TB regimen were not significant predictors of LTFU. CONCLUSIONS: There were declining trends in LTFU in Namibia. DOTS programmes should integrate socioeconomic interventions for young and middle-aged adult male TB cases to reduce LTFU.

Predictors of tuberculosis treatment success under the DOTS program in Namibia.

OBJECTIVES: Optimal treatment success rates are critical to end tuberculosis in Namibia. Despite the scale-up of high quality directly observed therapy short-course strategy (DOTS) in Namibia, treatment success falls short of the global target of 90%. The objective of this study was to ascertain the predictors of treatment success rates under DOTS in Namibia to provide future direction. METHODS: A nation-wide comparative analysis of predictors of treatment success was undertaken. Tuberculosis cases in the electronic tuberculosis register were retrospectively reviewed over a 10-year period, 2004-2016. The patient, programmatic, clinical, and treatment predictors of treatment success were determined by multivariate logistic regression modeling using R software. RESULTS: 104,603 TB cases were registered at 300 DOTS sites in 37 districts. The 10-year period treatment success rate was 80%, and varied by region (77.2%-89.2%). The patient's sex and age were not significant predictors. The independent predictors for treatment success as were: Region of DOTS implementation (p=0.001), type of directly observed treatment (DOT) supporter (p<0.001), sputum conversion at 2 months (p=0.013), DOT regimen (p<0.001), cotrimoxazole prophylaxis (p=0.002), and HIV co-infection (p=0.001). CONCLUSION: Targeted programmatic, clinical and treatment interventions are required to enhance DOTS treatment success in Namibia. These are now ongoing.

Monitoring of gentamicin serum concentrations in obstetrics and gynaecology patients in Namibia.

Background Therapeutic drug monitoring is frequently used to optimize the gentamicin dose. Objective The study investigated whether a 240 mg once daily standard dose achieves the recommended target serum gentamicin concentrations. Setting The prospective, observational study took place in the 2 major public hospitals in Namibia. Method Twenty-nine female patients receiving a standard dose (240 mg gentamicin once daily) participated in the study. Two blood samples were withdrawn to estimate gentamicin pharmacokinetic parameters. Serum creatinine was used to calculate creatinine clearance with the Cockcroft-Gault formula (CLcr), and estimate glomerular filtration rate (eGFR) by the Modified Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations. Main outcome measure The outcome measure was the proportion of patients receiving 240 mg gentamicin once daily having Cmax values above 15 mg/L. Results Total body weight (TBW) and body mass index were highly variable: 43-115 kg, and 17.3-41.3 kg/m2, respectively. The gentamicin dose normalized for TBW (adjusted body weight for obese patients) was relatively low, i.e. 4.2 ± 0.8 mg/kg (mean SD). Gentamicin Cmax was 14.4 ± 4.7 mg/L; only 9 patients (31%) had a Cmax > 15 g/mL. eGFR (MDRD-4) correlated well with CLcr, but eGFR (EPI-CKD) formula showed systematic deviations from CLcr. Conclusions (1) a standard 240 mg dose results in gentamicin Cmax values below 15 mg/L in the majority of the patients, (2) eGFR formulas to estimate kidney function will have to be evaluated for their usefulness in the Namibian patient population.

Biowaiver Monographs for Immediate-Release Solid Oral Dosage Forms: Enalapril.

Literature data relevant to the decision to allow a waiver of in vivo bioequivalence testing for the marketing authorization of immediate-release, solid oral dosage forms containing enalapril maleate are reviewed. Enalapril, a prodrug, is hydrolyzed by carboxylesterases to the active angiotensin-converting enzyme inhibitor enalaprilat. Enalapril as the maleate salt is shown to be highly soluble, but only 60%-70% of an orally administered dose of enalapril is absorbed from the gastrointestinal tract into the enterocytes. Consequently, enalapril maleate is a Biopharmaceutics Classification System class III substance. Because in situ conversion of the maleate salt to the sodium salt is sometimes used in production of the finished drug product, not every enalapril maleate-labeled finished product actually contains the maleate salt. Enalapril is not considered to have a narrow therapeutic index. With this background, a biowaiver-based approval procedure for new generic products or after major revisions to existing products is deemed acceptable, provided the in vitro dissolution of both test and reference preparation is very rapid (at least 85% within 15 min at pH 1.2, 4.5, and 6.8). Additionally, the test and reference product must contain the identical active drug ingredient.

Optimizing treatment outcome of first-line anti-tuberculosis drugs: the role of therapeutic drug monitoring.

INTRODUCTION: Tuberculosis (TB) remains one of the world's deadliest communicable diseases. Although cure rates of the standard four-drug (rifampicin, isoniazid, pyrazinamide, ethambutol) treatment schedule can be as high as 95-98 % under clinical trial conditions, success rates may be much lower in less well resourced countries. Unsuccessful treatment with these first-line anti-TB drugs may lead to the development of multidrug resistant and extensively drug resistant TB. The intrinsic interindividual variability in the pharmacokinetics (PK) of the first-line anti-TB drugs is further exacerbated by co-morbidities such as HIV infection and diabetes. METHODS: Therapeutic drug monitoring has been proposed in an attempt to optimize treatment outcome and reduce the development of drug resistance. Several studies have shown that maximum plasma concentrations (C max), especially of rifampicin and isoniazid, are well below the proposed target C max concentrations in a substantial fraction of patients being treated with the standard four-drug treatment schedule, even though treatment's success rate in these studies was typically at least 85 %. DISCUSSION: The proposed target C max concentrations are based on the concentrations of these agents achieved in healthy volunteers and patients receiving the standard doses. Estimation of C max based on one or two sampling times may not have the necessary accuracy since absorption rate, especially for rifampicin, may be highly variable. In addition, minimum inhibitory concentration (MIC) variability should be taken into account to set clinically meaningful susceptibility breakpoints. Clearly, there is a need to better define the key target PK and pharmacodynamic (PD) parameters for therapeutic drug monitoring (TDM) of the first-line anti-TB drugs to be efficacious, C max (or area under the curve (AUC)) and C max/MIC (or AUC/MIC). CONCLUSION: Although TDM of first-line anti-TB drugs has been successfully used in a limited number of specialized centers to improve treatment outcome in slow responders, a better characterization of the target PK and/or PK/PD parameters is in our opinion necessary to make it cost-effective.

The Lidose hard capsule formulation of fenofibrate is suprabioavailable compared to the nanoparticle tablet formulation under high-fat fed conditions.

PURPOSE: The therapeutic equivalence of multiple registered fenofibrate formulations, several of which are suprabioavailable and therefore marketed at lower dosage strengths than their reference products, is based on the results of bioequivalence studies. Most of these formulations show a higher bioavailability when taken with a high-fat meal. The relative bioavailability of two of these formulations, the 200 mg Lidose hard capsules and the 145 mg nanoparticle tablets, was assessed when taken with a high-fat meal. METHODS: In this single dose, 2-way, randomized, crossover study, 24 healthy subjects received a 200 mg fenofibrate Lidose hard capsule (Test) and a 145 mg nanoparticle tablet (Reference) under high-fat fed conditions. Plasma concentrations of fenofibric acid were measured up to 72 hours by using a validated LC-MS/MS method. RESULTS: The geometric mean ratios (Test/Reference) and the 90% confidence intervals for AUC0-t and Cmax were 1.37 (131.58 - 142.88) and 1.38 (124.60 - 152.93), respectively. The median (range) Tmax- values of fenofibric acid were 4.5 h (3.0 - 8.0 h) and 3.25 h (1.0 - 6.5 h) after administration of the Lidose hard capsule and the nanoparticle tablet, respectively. CONCLUSION: Under high-fat fed conditions the extent of fenofibrate absorption was 37% higher for the 200 mg Lidose hard capsule compared to the 145 mg nanoparticle tablet, which is exactly as expected based on a mg-to-mg weight basis. The results of the present study underline the importance of assessing bioequivalence of fenofibrate formulations under identical fed conditions, and preferentially after a high-fat meal as this condition represents the worst-case scenario. Furthermore, the results of this study demonstrate that the 145 mg nanoparticle tablet is not bioequivalent to the 200 mg Lidose hard capsule when administered under high-fat meal conditions.

Prediction of paraquat exposure and toxicity in clinically ill poisoned patients: a model based approach.

AIMS: Paraquat poisoning is a medical problem in many parts of Asia and the Pacific. The mortality rate is extremely high as there is no effective treatment. We analyzed data collected during an ongoing cohort study on self-poisoning and from a randomized controlled trial assessing the efficacy of immunosuppressive therapy in hospitalized paraquat-intoxicated patients. The aim of this analysis was to characterize the toxicokinetics and toxicodynamics of paraquat in this population. METHODS: A non-linear mixed effects approach was used to perform a toxicokinetic/toxicodynamic population analysis in a cohort of 78 patients. RESULTS: The paraquat plasma concentrations were best fitted by a two compartment toxicokinetic structural model with first order absorption and first order elimination. Changes in renal function were used for the assessment of paraquat toxicodynamics. The estimates of toxicokinetic parameters for the apparent clearance, the apparent volume of distribution and elimination half-life were 1.17 l h(-1) , 2.4 l kg(-1) and 87 h, respectively. Renal function, namely creatinine clearance, was the most significant covariate to explain between patient variability in paraquat clearance.This model suggested that a reduction in paraquat clearance occurred within 24 to 48 h after poison ingestion, and afterwards the clearance was constant over time. The model estimated that a paraquat concentration of 429 µg l(-1) caused 50% of maximum renal toxicity. The immunosuppressive therapy tested during this study was associated with only 8% improvement of renal function. CONCLUSION: The developed models may be useful as prognostic tools to predict patient outcome based on patient characteristics on admission and to assess drug effectiveness during antidote drug development.

Population pharmacokinetic analysis of tacrolimus early after pediatric liver transplantation.

BACKGROUND: Tacrolimus (TAC) pharmacokinetics (PKs) show considerable unexplained variability, particularly in the early period after transplantation. Therefore, TAC is a good candidate for therapeutic drug monitoring. The main objective of the present work was to propose a robust PK model for TAC in the early period after transplantation, with the final goal to provide practitioners with a tool for dose individualization in pediatric patients. METHODS: TAC concentration data were obtained from 82 pediatric liver allograft recipients during the first 2 weeks after transplantation. Previously published models, and a model recently developed by our group for pediatrics early after pediatric liver transplantation, were fitted to the data and their predictive performance compared with the performances of a model developed using the data from 82 pediatric patients. RESULTS: During the data-driven analysis, the PKs of TAC were best described by a 1-compartment model with time-varying first order elimination. Apparent volume of distribution and blood clearance estimates were 283 L and 10 L/h, respectively. The absorption was also considered to be a first order process, with a first order rate fixed to 4.45 hours. Parameters were estimated with good precision and accuracy. Although hematocrit levels, time after transplantation, liver weight, and body weight influenced the clearance, body weight was the only covariate retained on volume of central and peripheral compartments. Two of the 5 previous models showed acceptable predictive performances using the observed data. CONCLUSIONS: Time after transplantation, body weight, and hematocrit levels were shown to influence TAC PK in the early pediatric post-liver transplantation period and should be considered, besides therapeutic drug monitoring, by clinicians for the TAC posology prescription and adaptation.

Statistical tools for dose individualization of mycophenolic acid and tacrolimus co-administered during the first month after renal transplantation.

AIM: To predict simultaneously the area under the concentration-time curve during one dosing interval [AUC(0,12 h)] for mycophenolic acid (MPA) and tacrolimus (TAC), when concomitantly used during the first month after transplantation, based on common blood samples. METHODS: Data were from two different sources, real patient pharmacokinetic (PK) profiles from 65 renal transplant recipients and 9000 PK profiles simulated from previously published models on MPA or TAC in the first month after transplantation. Multiple linear regression (MLR) and Bayesian estimation using optimal samples were performed to predict MPA and TAC AUC(0,12 h) based on two concentrations. RESULTS: The following models were retained: AUC(0,12 h) = 16.5 + 4.9 × C1.5 + 6.7 × C3.5 (r(2) = 0.82, rRMSE = 9%, with simulations and r(2) = 0.66, rRMSE = 24%, with observed data) and AUC(0,12 h) = 24.3 + 5.9 × C1.5 + 12.2 × C3.5 (r(2) = 0.94, rRMSE = 12.3%, with simulations r(2) = 0.74, rRMSE = 15%, with observed data) for MPA and TAC, respectively. In addition, bayesian estimators were developed including parameter values from final models and values of concentrations at 1.5 and 3.5 h after dose. Good agreement was found between predicted and reference AUC(0,12 h) values: r(2) = 0.90, rRMSE = 13% and r(2) = 0.97, rRMSE = 5% with simulations for MPA and TAC, respectively and r(2) = 0.75, rRMSE = 11% and r(2) = 0.83, rRMSE = 7% with observed data for MPA and TAC, respectively. CONCLUSION: Statistical tools were developed for simultaneous MPA and TAC therapeutic drug monitoring. They can be incorporated in computer programs for patient dose individualization.

The revised EMA guideline for the investigation of bioequivalence for immediate release oral formulations with systemic action.

On August 1, 2010, a revised guidance regarding bioequivalence (BE) assessment for the approval of innovator (bridging studies, variations, line extensions) and generic medicinal products in the EU came into effect (EMA Guideline on the Investigation of Bioequivalence, CPMP/EWP/QWP/1401/98 Rev. 1/Corr**, London, 20 January 2010). This guideline specifies the requirements for BE assessment for immediate release oral dosage forms with systemic action. Compared to the previous BE guideline of the EMA, clearer guidance is now given on several topics including BE assessment of highly variable drugs/drug products (HVDs/HVDPs), the use of metabolite data, acceptance criteria for narrow therapeutic index drugs (NTIDs), BCS-based biowaivers, and dose strength to be used in case of application for marketing authorization of several strengths. However, the health authorities of the various EU member states do not necessarily apply the same rules as far as substitution and switchability between medicinal products are concerned. Moreover, differences still exist between the BE guidelines of the major health authorities (FDA, EMA, NIHC, ...) on topics such as HVDs/HVDPs, NTIDs and BCS-based biowaivers. Global harmonization should be the next logical step to guarantee accessibility to safe and efficacious drug products for patients in all parts of the world.

Population pharmacokinetics of four ß-lactams in critically ill septic patients comedicated with amikacin.

OBJECTIVES: The study aimed to characterize the pharmacokinetics (PK) of four ß-lactams (piperacillin, ceftazidime, cefepime, and meropenem) in patients comedicated with amikacin (AMK), and to confirm the predictive performance of AMK data, obtained from therapeutic drug monitoring (TDM), on these PK, using a population modeling approach. DESIGN AND METHODS: Serum samples were collected in 88 critically ill septic patients. For each ß-lactam, the covariate model was optimized using renal function. Furthermore, predictive performance of AMK concentrations and PK parameters was assessed on ß-lactam PK. RESULTS: A two-compartment model with first-order elimination best fitted the ß-lactam data. Results supported the superiority of AMK concentrations, over renal function and AMK PK parameters, to assess the ß-lactam PK. CONCLUSION: The study confirmed the significant link between the exposure to AMK and to ß-lactams, and presented population models able to guide ß-lactam dosage adjustments using renal biomarkers or TDM-related aminoglycoside data.

Acenocoumarol sensitivity and pharmacokinetic characterization of CYP2C9 *5/*8,*8/*11,*9/*11 and VKORC1*2 in black African healthy Beninese subjects.

This study aimed at investigating the contribution of CYP2C9 and VKORC1 genetic polymorphisms to inter-individual variability of acenocoumarol pharmacokinetics and pharmacodynamics in Black Africans from Benin. Fifty-one healthy volunteers were genotyped for VKORC1 1173C>T polymorphism. All of the subjects had previously been genotyped for CYP2C9*5, CYP2C9*6, CYP2C9*8, CYP2C9*9 and CYP2C9*11 alleles. Thirty-six subjects were phenotyped with a single 8 mg oral dose of acenocoumarol by measuring plasma concentrations of (R)- and (S)-acenocoumarol 8 and 24 h after the administration using chiral liquid-chromatography tandem mass-spectrometry. International normalized ratio (INR) values were determined prior to and 24 h after the drug intake. The allele frequency of VKORC1 variant (1173C>T) was 1.96% (95% CI 0.0-4.65%). The INR values did not show statistically significant difference between the CYP2C9 genotypes, but were correlated with body mass index and age at 24 h post-dosing (P < 0.05). At 8 h post dose, the (S)-acenocoumarol concentrations in the CYP2C9*5/*8 and CYP2C9*9/*11 genotypes were about 1.9 and 5.1 fold higher compared with the CYP2C9*1/*1 genotype and 2.2- and 6.0-fold higher compared with the CYP2C9*1/*9 group, respectively. The results indicated that pharmacodynamic response to acenocoumarol is highly variable between the subjects. This variability seems to be associated with CYP2C9*5/*8 and *9/*11 variant and demographic factors (age and weight) in Beninese subjects. Significant association between plasma (S)-acenocoumarol concentration and CYP2C9 genotypes suggested the use of (S)-acenocoumarol for the phenotyping purpose. Larger number of subjects is needed to study the effect of VKORC1 1173C>T variant due to its low frequency in Beninese population.

Comparative oral bioavailability of non-fixed and fixed combinations of artesunate and amodiaquine in healthy Indian male volunteers.

OBJECTIVE: The aim of the present study was to compare the pharmacokinetic properties, bioavailability and tolerability of artesunate (AS) and amodiaquine (AQ) administered as a fixed-dose combination (Amonate FDC tablets; Dafra Pharma, Turnhout, Belgium) or as a non-fixed dose combination of separate AS tablets (Arsuamoon; Guilin Pharmaceutical Co, Shanghai, China) and AQ tablets (Flavoquine; Sanofi-Aventis, Paris, France). METHODS: This was a randomized, open label, two-period, two-treatment, two-sequence, cross-over study in which 60 healthy male Indian volunteers were given a single total oral dose of 100 mg AS and 400 mg AQ hydrochloride either as two tablets of Amonate FDC (AS 50 mg and AQ hydrochloride 200 mg) or as two AS tablets of the co-blister Arsuamoon (50 mg AS) together with two Flavoquine tablets (200 mg AQ hydrochloride). Plasma AS and blood AQ concentrations, as well as those of their respective active metabolites dihydroartemisinin (DHA) and desethylamodiaquine (DEAQ), were measured by high-performance liquid chromatography-tandem spectrometry. The pharmacokinetic parameters of AS, DHA, AQ and DEAQ were determined by non-compartmental analysis. Bioequivalence assessment was performed by analysis of variance (ANOVA), and calculation of the 90% confidence intervals of the geometric mean ratio test (fixed)/reference (non-fixed) for AUC(0-t) and C(max) for AS, AQ, DHA and DEAQ. RESULTS: Interim analysis showed that both treatments were not bioequivalent; therefore, statistical analysis was carried out on the results of all subjects for whom blood/plasma concentrations were available for all four analytes (n=26). The C(max) (maximum plasma/blood concentration) of AS was 67.0 ± 37.1 and 154.8 ± 116.2 ng/mL for the fixed-dose and non-fixed dose administration, respectively. The AUC(0-t) (area under the plasma concentration-time curve from time zero to the last measurable concentration) of AS was 60.1 ± 27.5 and 81.8 ± 44.3 ng h/mL for the fixed-dose and non-fixed dose administration, respectively. The 90% confidence intervals for C(max) and AUC(0-t) of AS were outside the 80-125% acceptance range: 37.02-61.62% and 70.10-83.47%, respectively. The C(max) of AQ was 33.8 ± 13.6 and 31.4 ± 14.1 ng/mL for the fixed-dose and non-fixed dose administration, respectively. The AUC(0-t) of AQ was 332.3 ± 116.6 and 329.8 ± 99.5 ng h/mL for the fixed and non-fixed dose administration, respectively. For AQ, the 90% CIs for C(max) and AUC(0-t) were within the 80-125% acceptance range: 99.17-121.71 and 89.53-107.35%, respectively. Bioequivalence assessment based on the active metabolite data supported the bioequivalence conclusions based on the parent compound data. Both the fixed-dose and non-fixed dose administration of 100 mg AS and 400 mg AQ were well tolerated. CONCLUSION: Bioequivalence of the fixed-dose AS/AQ formulation with the non-fixed dose combination of the same drugs was not demonstrated for AS, but it was shown for AQ for both C(max) and AUC(0-t). The results obtained on the active metabolites support this conclusion. Overall, the fixed-dose 50 mg AS/200 mg AQ tablets were not technically bioequivalent with 50 mg AS tablets and 200 mg AQ tablets administered separately. The difference cannot be explained by the pharmaceutical properties of the tablets and seems to be biologically related.

Population pharmacokinetic modeling and optimal sampling strategy for Bayesian estimation of amikacin exposure in critically ill septic patients.

Because the sepsis-induced pharmacokinetic (PK) modifications need to be considered in aminoglycoside dosing, the present study aimed to develop a population PK model for amikacin (AMK) in severe sepsis and to subsequently propose an optimal sampling strategy suitable for Bayesian estimation of the drug PK parameters. Concentration-time profiles for AMK were obtained from 88 critically ill septic patients during the first 24 hours of antibiotic treatment. The population PK model was developed using a nonlinear mixed effects modeling approach. Covariate analysis included demographic data, pathophysiological characteristics, and comedication. Optimal sampling times were selected based on a robust Bayesian design criterion. Taking into account clinical constraints, a two-point sampling approach was investigated. A two-compartment model with first-order elimination best fitted the AMK concentrations. Population PK estimates were 19.2 and 9.34 L for the central and peripheral volume of distribution and 4.31 and 2.21 L/h for the intercompartmental and total body clearance. Creatinine clearance estimated using the Cockcroft-Gault equation was retained in the final model. The two optimal sampling times were 1 hour and 6 hours after onset of the drug infusion. Predictive performance of individual Bayes estimates computed using the proposed optimal sampling strategy was reported: mean prediction errors were less than 5% and root mean square errors were less than 30%. The present study confirmed the significant influence of the creatinine clearance on the PK disposition of AMK during the first hours of treatment in critically ill septic patients. Based on the population estimates, an optimal sampling strategy suitable for Bayesian estimation of the drug PK parameters was developed, meeting the need of clinical practice.