Pharmacokinetic-pharmacodynamic modelling and simulation of methotrexate dosing in patients with rheumatoid arthritis.

AIMS: To develop a non-linear mixed-effects population pharmacokinetic and pharmacodynamic (PK-PD) model describing the change in the concentration of methotrexate polyglutamates in erythrocytes (ery-MTX-PGn with "n" number of glutamate, representing PK component) and how this relates to modified 28-joint Disease Activity Score incorporating erythrocyte sedimentation rate (DAS-28-3) for rheumatoid arthritis (RA), representing PD component. METHODS: An existing PK model was fitted to data from a study consisting of 117 RA patients. The estimation of population PK-PD parameters was performed using stochastic approximation expectation maximisation algorithm in Monolix 2021R2. The model was used to perform Monte Carlo simulations of a loading dose regimen (50mg subcutaneous methotrexate as loading doses, then 20mg weekly oral methotrexate) compared to a standard dosing regimen (10mg weekly oral methotrexate for 2 weeks, then 20mg weekly oral methotrexate). RESULTS: Every 40 nmol/L increase in ery-MTX-PG3-5 total concentration correlated with 1-unit reduction in DAS-28-3. Significant covariate effects on the therapeutic response of methotrexate included the use of prednisolone in the first 4 weeks (positive use correlated with 25% reduction in DAS-28-3 when other variables were constant) and patient age (every 10-year increase in age correlated with 3.4% increase in DAS-28-3 when other variables were constant). 4 methotrexate loading doses led to a higher percentage of patients achieving a good/moderate response compared to the standard regimen (Week 4: 87.6% vs. 39.8%; Week 10: 64.7% vs. 57.0%). CONCLUSIONS: A loading dose regimen was more likely to achieve higher ery-MTX-PG concentration and better therapeutic response after 4 weeks of methotrexate treatment.

Spatio-temporal trends in livestock exposure to per- and polyfluoroalkyl substances (PFAS) inform risk assessment and management measures.

The migration of per- and polyfluoroalkyl substances (PFAS) onto agricultural properties has resulted in the accumulation of PFAS in livestock. The environmental determinants of PFAS accumulation in livestock from the grazing environment are poorly understood, resulting in limited capacity to manage livestock exposure and subsequent transfer of PFAS through the food chain. Analytical- (n = 978 samples of soil, water, pasture, and serum matrices), farm management/practice- and livestock physiology data were collated and interrogated from environmental PFAS investigations across ten farms, from four agro-ecological regions of Victoria (Australia). Statistical analysis identified perfluorooctane sulfonate (PFOS) and perfluorohexane sulfonate (PFHxS) as key analytes of concern for livestock bioaccumulation. PFOS and PFHxS concentrations in livestock drinking water were positively correlated with serum concentrations while other intake pathways (pasture and soil) had weaker correlations. Seasonal trends in PFAS body burden (serum concentrations) were identified and suggested to be linked to seasonal grazing behaviours and physiological water requirements. The data showed for the first time that livestock exposure to PFAS is dynamic and with relatively short elimination half-lives, there is opportunity for exposure management. Meat from cattle, grazed on PFAS impacted sites, may exceed health-based guideline values for PFAS, especially for markets with low limits (like the European Commission Maximum Limits or EC MLs). This study found that sites with mean livestock drinking water concentrations as low as 0.003 µg PFOS/L may exceed the EC ML for PFOS in cattle meat. Risk assessment can be used to prioritise site cleanup and development of management plans to reduce PFAS body burden by considering timing of stock rotation and/or supplementation of primary exposure sources.

Population pharmacokinetic model of subcutaneous fentanyl in older acute care patients.

PURPOSE: Subcutaneous fentanyl injection is commonly prescribed to manage acute pain in older patients; however, there is a gap in the literature describing the pharmacokinetic parameters for this route of administration in this population. The aim of this study was to develop and evaluate a population pharmacokinetic model for subcutaneous fentanyl injection in older patients. METHODS: Twenty-one patients who received subcutaneous fentanyl injections (50 to 75 µg) were recruited. Fentanyl concentrations were determined using a validated liquid chromatography/tandem mass spectrometry method. A population pharmacokinetic model was developed using non-linear mixed-effects modelling. A base model was selected based on the Akaike information criterion. Age, sex, body weight, number of previous fentanyl doses, number of prescribed medications, creatinine clearance, Charlson Comorbidity Index, Identification of Seniors at Risk score and concurrent use of CYP3A4 inhibitors were covariates considered for inclusion. A p value of < 0.05 was considered statistically significant for inclusion of covariates in the final model by stepwise addition. The simulation performance of the model was assessed by visual predictive check. RESULTS: A one-compartment, first-order absorption with lag time and linear elimination model was the best to fit to the fentanyl concentration data. The absorption rate constant was 0.136 h-1 (between subject variability (BSV), 46%), lag time 0.66 h (BSV 51%), apparent volume of distribution 6.28 L (BSV 30%), and apparent clearance 16.3 L.h-1 (BSV 54%). The Charlson Comorbidity Index was the only covariate included in the final model, where a higher value of the index increased fentanyl exposure and Cmax. CONCLUSION: This is the first report of subcutaneous fentanyl population pharmacokinetic model to evaluate fentanyl pharmacokinetic in older patients. The between subject variability in clearance and subcutaneous absorption rate was relatively high, and some patients recorded high fentanyl concentrations in the context of their titration to effect.

Population pharmacokinetics of lenalidomide in patients with B-cell malignancies.

AIMS: Lenalidomide is an immunomodulatory imide drug used broadly in the treatment of multiple myeloma and lymphoma. It continues to be evaluated in chronic lymphocytic leukaemia (CLL) at lower doses due to dose-related toxicities including tumour flare and tumour lysis syndrome. This study aimed to develop a population pharmacokinetic model for lenalidomide in multiple cancers, including CLL, to identify any disease-related differences in disposition. METHODS: Lenalidomide concentrations from 4 clinical trials were collated (1999 samples, 125 subjects), covering 4 cancers (multiple myeloma, CLL, acute myeloid leukaemia and acute lymphoblastic leukaemia) and a large dose range (2.5-75 mg). A population pharmacokinetic model was developed with NONMEM and patient demographics were tested as covariates. RESULTS: The data were best fitted by a 1-compartment kinetic model with absorption described by 7 transit compartments. Clearance and volume of distribution were allometrically scaled for fat-free mass. The population parameter estimates for apparent clearance, apparent volume of distribution and transit rate constant were 12 L/h (10.8-13.6), 68.8 L (61.8-76.3), and 13.5 h-1 (11.9-36.8) respectively. Patients with impaired renal function (creatinine clearance <30 mL/min) exhibited a 22% reduction in lenalidomide clearance compared to patients with creatinine clearance of 90 mL/min. Cancer type had no discernible effect on lenalidomide disposition. CONCLUSIONS: This is the first report of a lenalidomide population pharmacokinetic model to evaluate lenalidomide pharmacokinetics in patients with CLL and compare its pharmacokinetics with other B-cell malignancies. As no differences in pharmacokinetics were found between the observed cancer-types, the unique toxicities observed in CLL may be due to disease-specific pharmacodynamics.

Converting from Transdermal to Buccal Formulations of Buprenorphine: A Pharmacokinetic Meta-Model Simulation in Healthy Volunteers.

Objective: To develop a model to predict buprenorphine plasma concentrations during transition from transdermal to buccal administration. Design: Population pharmacokinetic model-based meta-analysis of published data. Methods: A model-based meta-analysis of available buprenorphine pharmacokinetic data in healthy adults, extracted as aggregate (mean) data from published literature, was performed to explore potential conversion from transdermal to buccal buprenorphine. The time course of mean buprenorphine plasma concentrations following application of transdermal patch or buccal film was digitized from available literature, and a meta-model was developed using specific pharmacokinetic parameters (e.g., absorption rate, apparent clearance, and volumes of distribution) derived from analysis of pharmacokinetic data for intravenously, transdermally, and buccally administered buprenorphine. Results: Data from six studies were included in this analysis. The final transdermal absorption model employed a zero-order input rate that was scaled to reflect a nominal patch delivery rate and time after patch application (with decline in rate over time). The transdermal absorption rate constant became zero following patch removal. Buccal absorption was a first-order process with a time lag and bioavailability term. Simulations of conversion from transdermal 20 mcg/h and 10 mcg/h to buccal administration suggest that transition can be made rapidly (beginning 12 hours after patch removal) using the recommended buccal formulation titration increments (75-150 mcg) and schedule (every four days) described in the product labeling. Conclusions: Computer modeling and simulations using a meta-model built from data extracted from publications suggest that rapid and straightforward conversion from transdermal to buccal buprenorphine is feasible.

Population in vitro-in vivo pharmacokinetic model of first-pass metabolism: itraconazole and hydroxy-itraconazole.

The aim of this study was to develop a population in vitro-in vivo pharmacokinetic model that simultaneously describe the absorption and accumulation kinetics of itraconazole (ICZ) and hydroxy-itraconazole (HICZ) in healthy subjects. The model integrated meta-models of gastrointestinal pH and gastrointestinal transit time and in vitro dissolution models of ICZ with the absorption and disposition kinetics of ICZ and HICZ. Mean concentration intravenous data, and single- and multi-dose oral data were used for model development. Model development was conducted in NONMEM in a stepwise manner. First, a model of intravenous data (systemic kinetics) was established and then extended to include the oral data. The latter was then extended to establish the in vitro-in vivo pharmacokinetic model. The systemic disposition of ICZ was best described by a 3-compartment model with oral absorption described by 4-transit compartments and HICZ distribution by a 1-compartment model. ICZ clearance was best described using a mixed inhibition model that allowed HICZ concentrations to inhibit the clearance of parent drug. HICZ clearance was described by Michaelis-Menten elimination kinetics. An in vitro-in vivo model was successfully established for both formulations. The presented model was able to describe ICZ and HICZ plasma concentrations over a wide range of oral and intravenous doses and allowed the exploration of complexities associated with the non-linear ICZ and HICZ kinetics. The model may provide insight into the variability in exposure of ICZ with respect to relating in vivo dissolution characteristics with in vivo disposition kinetics.

Population Pharmacokinetic Model of Doxycycline Plasma Concentrations Using Pooled Study Data.

The literature presently lacks a population pharmacokinetic analysis of doxycycline. This study aimed to develop a population pharmacokinetic model of doxycycline plasma concentrations that could be used to assess the power of bioequivalence between Doryx delayed-release tablets and Doryx MPC. Doxycycline pharmacokinetic data were available from eight phase 1 clinical trials following single/multiple doses of conventional-release doxycycline capsules, Doryx delayed-release tablets, and Doryx MPC under fed and fasted conditions. A population pharmacokinetic model was developed in a stepwise manner using NONMEM, version 7.3. The final covariate model was developed according to a forward inclusion (P < 0.01) and then backward deletion (P < 0.001) procedure. The final model was a two-compartment model with two-transit absorption compartments. Structural covariates in the base model included formulation effects on relative bioavailability (F), absorption lag (ALAG), and the transit absorption rate (KTR) under the fed status. An absorption delay (lag) for the fed status (FTLAG2 = 0.203 h) was also included in the model as a structural covariate. The fed status was observed to decrease F by 10.5%, and the effect of female sex was a 14.4% increase in clearance. The manuscript presents the first population pharmacokinetic model of doxycycline plasma concentrations following oral doxycycline administration. The model was used to assess the power of bioequivalence between Doryx delayed-release tablets and Doryx MPC, and it could potentially be used to critically examine and optimize doxycycline dose regimens.

Use of Calculated Physicochemical Properties to Enhance Quantitative Response When Using Charged Aerosol Detection.

Universal quantitative detection without the need for analyte reference standards would offer substantial benefits in many areas of analytical science. The quantitative capability of high-performance liquid chromatography (HPLC) with charged aerosol detection (CAD) was investigated for 50 compounds with a wide range of physical and chemical properties. It is widely believed that CAD is a mass detector. Quantification of the 50 compounds using a generic calibrant and mass calibration achieved an average error of 11.4% relative to 1H NMR. Correction factors are proposed that estimate the relative surface area of particles in the detector, taking into account the effects of the density and charge of analytes. Performing these corrections and quantifying with surface area calibration, rather than mass, shows considerably improved linearity and uniformity of detection, reducing the average error relative to 1H NMR to 7.1%. The accuracy of CAD quantification was most significantly improved for highly dense compounds, with traditional mass calibration showing an average error of 34.7% and the newly proposed surface area calibration showing an average error of 5.8%.

Intracellular CD3+ T Lymphocyte Teriflunomide Concentration Is Poorly Correlated with and Has Greater Variability Than Unbound Plasma Teriflunomide Concentration.

Leflunomide's active metabolite teriflunomide inhibits dihydro-oroate dehydrogenase, an enzyme essential to proliferation of T lymphocytes. As teriflunomide must reach the target site to have this effect, this study assessed the distribution of teriflunomide into T lymphocytes, as intracellular concentrations may be a superior response biomarker to plasma concentrations. CD3 MicroBeads (Miltenyi Biotec, Bergisch Gladbach, Germany) were used to extract CD3+ T cells from the peripheral blood of patients with rheumatoid arthritis who were taking a stable dose of leflunomide. Unbound plasma and intra-CD3+ T cell teriflunomide concentrations were quantified using liquid chromatography-mass spectrometry. Concentration (log transformed) and partition differences were assessed through paired Student t tests. Sixteen patients provided plasma steady-state teriflunomide samples, and eight provided a sample 6-12 weeks later. At time-point one, the geometric mean teriflunomide concentration (range) in CD3+ T cells was 18.12 µg/L (6.15-42.26 µg/L) compared with 69.75 µg/L (32.89-263.1 µg/L) unbound in plasma (P < 0.001). The mean partition coefficient (range) for unbound plasma teriflunomide into CD3+ T cells was 0.295 (0.092-0.632), which was significantly different from unity (P < 0.001). The median (range) change in teriflunomide concentration between the two time points was 14% (-10% to 40%) in unbound plasma and -29% (-69 to 138%) for CD3+ T cells. Because teriflunomide concentrations in CD3+ T cells were lower and displayed a higher intraindividual variability than the unbound plasma concentrations, its applicability as a therapeutic drug-monitoring marker may be limited.

Comparison of non-compartmental and mixed effect modelling methods for establishing bioequivalence for the case of two compartment kinetics and censored concentrations.

Non-compartmental analysis (NCA) is regarded as the standard for establishing bioequivalence, despite its limitations and the existence of alternative methods such as non-linear mixed effects modelling (NLMEM). Comparisons of NCA and NLMEM in bioequivalence testing have been limited to drugs with one-compartment kinetics and have included a large number of different approaches. A simulation tool was developed with the ability to rapidly compare NCA and NLMEM methods in determining bioequivalence using both R and NONMEM and applied to a drug with two-compartment pharmacokinetics. Concentration-time profiles were simulated where relative bioavailability, random unexplained variability (RUV) at the lower limit of quantification (LLOQ) differed between simulations. NLMEM analyses employed either the M1 or M3 methods for dealing with values below the LLOQ. It was used to elucidate the impact of changes in (i) RUV at the LLOQ, (ii) the extent of censoring data below the LLOQ and (iii) the concentration sampling times. The simulations showed NLMEM having a consistent 20-40% higher accuracy and sensitivity in identifying bioequivalent studies when compared to NCA, while NCA was found to have a 1-10% higher specificity than NLMEM. Increasing data censoring by increasing the LLOQ resulted in decreases of ~10% to the accuracy and sensitivity of NCA, with minimal effects on NLMEM. The tool provides a platform for comparing NCA and NLMEM methods and its use can be extended beyond the scenarios reported here. In the situations examined it is seen that NLMEM is more accurate than NCA and may offer some advantages in the determination of bioequivalence.

A model-based evaluation of single metrics for discriminating changes in rheumatoid arthritis disease activity.

AIMS: Composite indices for quantifying rheumatoid arthritis (RA) disease activity such as the 28-joint disease activity score (DAS28) are comprised of single parameters ('metrics') in various combinations. Population modelling methods were used to evaluate single metrics for their ability to reflect changes in disease activity with a view to understanding and improving composite indices. METHODS: A total of 11 single metrics of RA disease activity (tender and swollen joint counts, acute phase reactants and global health, pain and physical function assessments) were obtained from 203 patients with recent onset RA. Participants received combination disease-modifying anti-rheumatic drugs (DMARDs) according to a treat-to-target approach with a pre-defined protocol for treatment intensification. Models describing each metric's magnitude and variability of change from baseline to a single 'treated' state in the population were developed using nonmem(®) . Measures that displayed uniformly large changes between states across the population were ranked higher in terms of discriminatory capacity. RESULTS: Joint counts demonstrated a greater ability to discriminate changes in RA disease activity than others. Correlations between metrics demonstrated that erythrocyte sedimentation rate (ESR) had limited relationships with others for baseline scores and changes in RA disease activity (r generally < 0.2). However it appeared to be important in describing changes for those individuals where ESR levels were initially elevated. CONCLUSION: It appears unlikely that a single group of metrics may be suitable to capture disease activity changes across all RA patients and defining the most appropriate metric(s) for individual patients will be an important area of future research.

Genetic polymorphism of CYP1A2 but not total or free teriflunomide concentrations is associated with leflunomide cessation in rheumatoid arthritis.

AIM: Leflunomide, via its active metabolite teriflunomide, is used in rheumatoid arthritis (RA) treatment, yet approximately 20 to 40% of patients cease due to toxicity. The aim was to develop a time-to-event model describing leflunomide cessation due to toxicity within a clinical cohort and to investigate potential predictors of cessation such as total and free teriflunomide exposure and pharmacogenetic influences. METHODS: This study included individuals enrolled in the Early Arthritis inception cohort at the Royal Adelaide Hospital between 2000 and 2013 who received leflunomide. A time-to-event model in nonmem was used to describe the time until leflunomide cessation and the influence of teriflunomide exposure and pharmacogenetic variants. Random censoring of individuals was simultaneously described. The clinical relevance of significant covariates was visualized via simulation. RESULTS: Data from 105 patients were analyzed, with 34 ceasing due to toxicity. The baseline dropout hazard and baseline random censoring hazard were best described by step functions changing over discrete time intervals. No statistically significant associations with teriflunomide exposure metrics were identified. Of the screened covariates, carriers of the C allele of CYP1A2 rs762551 had a 2.29 fold increase in cessation hazard compared with non-carriers (95% CI 2.24, 2.34, P = 0.016). CONCLUSIONS: A time-to-event model described the time between leflunomide initiation and cessation due to side effects. The C allele of CYP1A2 rs762551 was linked to increased leflunomide toxicity, while no association with teriflunomide exposure was identified. Future research should continue to investigate exposure-toxicity relationships, as well as potentially toxic metabolites.

Population In Vitro-In Vivo Correlation Model Linking Gastrointestinal Transit Time, pH, and Pharmacokinetics: Itraconazole as a Model Drug.

PURPOSE: To establish an in vitro-in vivo correlation (IVIVC) model for Sporanox and SUBA-itraconazole formulations and to understand the impact of gastrointestinal (GI) pH and transit times on itraconazole dissolution and absorption. METHODS: IVIVC was developed based on fed/fasted pharmacokinetic data from randomized cross-over trials, in vitro dissolution studies, and prior information about typical and between subject variability of GI pH and transit times. Data were analysed using the population modelling approach as implemented in NONMEM. RESULTS: Dissolution kinetics were described using first order models. The in vivo pharmacokinetics of itraconazole was described with a 2-compartment model with 4-transit absorption compartments. Pharmacokinetic profiles for fasted itraconazole periods were described based on the in vitro dissolution model, in vivo disposition model, and the prior information on GI pH and transit times. The IVIVC model indicated that drug dissolution in the fed state required an additional pH-independent dissolution pathway. The IVIVC models were presented in a 'Shiny' application. CONCLUSION: An IVIVC model was established and internally evaluated for the two itraconazole formulations. The IVIVC model provides more insight into the observed variability of itraconazole pharmacokinetics and indicated that GI pH and transit times influence in vivo dissolution and exposure.

An introduction to physiologically-based pharmacokinetic models.

Physiologically-based pharmacokinetic (PBPK) models represent drug kinetics in one or more 'real' organs (and hence require submodels of organs/tissues) and they describe 'whole-body' kinetics by joining together submodels with drug transport by blood flow as dictated by anatomy. They attempt to reproduce 'measureable' physiological and/or pharmacokinetic processes rather than more abstract rate constants and volumes. PBPK models may be built using a 'bottom-up' approach, where parameters are chosen from first principles, literature, or in vitro data as opposed to a 'top-down' approach, where all parameters are estimated from data. The basic principles of PBPK models are described, focusing on the equations for three individual organs: a single flow-limited compartment describing distribution only, a membrane-limited compartment describing distribution, and a single flow-limited compartment with elimination. These organ models are linked to make a basic three-compartment physiological model of the whole body. PBPK models are particularly suited to scaling kinetics across body size (e.g., adult to neonate) and species (e.g., animal to first-in-man) as physiology and pharmacology can be represented by independent parameters. Maturation models can be incorporated as for compartmental models. PBPK models are now available in commercial software packages, and are perhaps now more accessible than ever. Alternatively, even complex PBPK models can be represented in generic differential equation-solving software using the simple principles described here. The relative ease of constructing the code for PBPK models belies the most difficult aspect of their implementation-collecting, collating, and justifying the data used to parameterize the model.

A Chemical Probe for the ATAD2 Bromodomain.

ATAD2 is a cancer-associated protein whose bromodomain has been described as among the least druggable of that target class. Starting from a potent lead, permeability and selectivity were improved through a dual approach: 1) using CF2 as a sulfone bio-isostere to exploit the unique properties of fluorine, and 2) using 1,3-interactions to control the conformation of a piperidine ring. This resulted in the first reported low-nanomolar, selective and cell permeable chemical probe for ATAD2.

Population pharmacokinetic modeling of itraconazole and hydroxyitraconazole for oral SUBA-itraconazole and sporanox capsule formulations in healthy subjects in fed and fasted states.

Itraconazole is an orally active antifungal agent that has complex and highly variable absorption kinetics that is highly affected by food. This study aimed to develop a population pharmacokinetic model for itraconazole and the active metabolite hydroxyitraconazole, in particular, quantifying the effects of food and formulation on oral absorption. Plasma pharmacokinetic data were collected from seven phase I crossover trials comparing the SUBA-itraconazole and Sporanox formulations of itraconazole. First, a model of single-dose itraconazole data was developed, which was then extended to the multidose data. Covariate effects on itraconazole were then examined before extending the model to describe hydroxyitraconazole. The final itraconazole model was a 2-compartment model with oral absorption described by 4-transit compartments. Multidose kinetics was described by total effective daily dose- and time-dependent changes in clearance and bioavailability. Hydroxyitraconazole was best described by a 1-compartment model with mixed first-order and Michaelis-Menten elimination for the single-dose data and a time-dependent clearance for the multidose data. The relative bioavailability of SUBA-itraconazole compared to that of Sporanox was 173% and was 21% less variable between subjects. Food resulted in a 27% reduction in bioavailability and 58% reduction in the transit absorption rate constant compared to that with the fasted state, irrespective of the formulation. This analysis presents the most extensive population pharmacokinetic model of itraconazole and hydroxyitraconazole in the literature performed in healthy subjects. The presented model can be used for simulating food effects on itraconazole exposure and for performing prestudy power analysis and sample size estimation, which are important aspects of clinical trial design of bioequivalence studies.

Population pharmacokinetics of orally administered mefloquine in healthy volunteers and patients with uncomplicated Plasmodium falciparum malaria.

BACKGROUND: The determination of dosing regimens for the treatment of malaria is largely empirical and thus a better understanding of the pharmacokinetic/pharmacodynamic properties of antimalarial agents is required to assess the adequacy of current treatment regimens and identify sources of suboptimal dosing that could select for drug-resistant parasites. Mefloquine is a widely used antimalarial, commonly given in combination with artesunate. PATIENTS AND METHODS: Mefloquine pharmacokinetics was assessed in 24 healthy adults and 43 patients with Plasmodium falciparum malaria administered mefloquine in combination with artesunate. Population pharmacokinetic modelling was conducted using NONMEM. RESULTS: A two-compartment model with a single transit compartment and first-order elimination from the central compartment most adequately described mefloquine concentration-time data. The model incorporated population parameter variability for clearance (CL/F), central volume of distribution (VC/F) and absorption rate constant (KA) and identified, in addition to body weight, malaria infection as a covariate for VC/F (but not CL/F). Monte Carlo simulations predict that falciparum malaria infection is associated with a shorter elimination half-life (407 versus 566 h) and T>MIC (766 versus 893 h). CONCLUSIONS: This is the first known population pharmacokinetic study to show falciparum malaria to influence mefloquine disposition. Protein binding, anaemia and other factors may contribute to differences between healthy individuals and patients. As VC/F is related to the earlier portion of the concentration-time profiles, which occurs during acute malaria, and CL/F is more related to the terminal phase during convalescence after treatment, this may explain why malaria was found to be a covariate for VC/F but not CL/F.

A population model of early rheumatoid arthritis disease activity during treatment with methotrexate, sulfasalazine and hydroxychloroquine.

AIMS: To develop a population model describing the disease activity (DAS28) time course in patients with early rheumatoid arthritis (RA) treated with triple disease-modifying anti-rheumatic drug (DMARD) therapy (methotrexate, sulfasalazine and hydroxychloroquine). METHODS: DAS28 was obtained in 263 patients with early RA from initiation of therapy until 60 weeks. Using NONMEM(®), base models (DAS28 vs. time) and covariate influences were investigated for the population. RESULTS: The best model was an exponential model of DAS28 vs. time that was additive to baseline DAS28, with covariance between parameters, and a combined residual error model. Age and patient smoking history were covariates significantly affecting response to therapy. Population estimates were baseline DAS28 (5.7), extent of change in DAS28 (-2.8) and the half-life of disease activity (6.2 weeks; time to steady disease state achieved within approximately 30 weeks). Older individuals exhibited more severe baseline DAS28, described by a power function centred around 57 years (baseline DAS28 for 40- and 70-year-old patients were 5.4 vs. 5.8, respectively) and current smokers took longer to achieve a steady disease state (approximately 50 weeks). There was considerable within-patient random variability in DAS28 over time (empirical 90% CI for DAS28 in a population typical patient at 60 weeks: 1.8, 4.2 with median value of 2.8). CONCLUSIONS: This is the first report of a disease activity model for early RA treated with triple DMARD therapy. Smoking and age were identified as covariates.

Improving the passive permeability of macrocyclic peptides: Balancing permeability with other physicochemical properties.

A number of methods to improve the passive permeability of a set of cyclic peptides have been investigated using 6- and 7-mer macrocyclic templates. In many cases the peptides were designed by molecular dynamics calculations to evaluate the methods. The aim of this study was not only to improve passive permeability, but also to balance permeability with other physicochemical properties with the goal of understanding and applying the knowledge to develop active cyclic peptides into drug candidates. Evaluation of the methods herein suggest that increasing passive permeability often occurs at the expense of solubility and lipophilicity. Computational methods can be useful when attempting to predict and design features to balance these properties, though limitations were observed.

Pharmacokinetics of tramadol after subcutaneous administration in a critically ill population and in a healthy cohort.

BACKGROUND: Tramadol is an atypical centrally acting analgesic agent available as both oral and parenteral preparations. For patients who are unable to take tramadol orally, the subcutaneous route of administration offers an easy alternative to intravenous or intramuscular routes. This study aimed to characterise the absorption pharmacokinetics of a single subcutaneous dose of tramadol in severely ill patients and in healthy subjects. METHODS/DESIGN: Blood samples (5 ml) taken at intervals from 2 minutes to 24 hours after a subcutaneous dose of tramadol (50 mg) in 15 patients (13 male, two female) and eight healthy male subjects were assayed using high performance liquid chromatography. Pharmacokinetic parameters were derived using a non-compartmental approach. RESULTS: There were no statistically significant differences between the two groups in the following parameters (mean ± SD): maximum venous concentration 0.44 ± 0.18 (patients) vs. 0.47 ± 0.13 (healthy volunteers) mcg/ml (p = 0.67); area under the plasma concentration-time curve 177 ± 109 (patients) vs. 175 ± 75 (healthy volunteers) mcg/ml*min (p = 0.96); time to maximum venous concentration 23.3 ± 2 (patients) vs. 20.6 ± 18.8 (healthy volunteers) minutes (p = 0.73) and mean residence time 463 ± 233 (patients) vs. 466 ± 224 (healthy volunteers) minutes (p = 0.97). CONCLUSIONS: The similar time to maximum venous concentration and mean residence time suggest similar absorption rates between the two groups. These results indicate that the same dosing regimens for subcutaneous tramadol administration may therefore be used in both healthy subjects and severely ill patients. TRIAL REGISTRATION: ACTRN12611001018909.