Nonlinear Mixed-effects Approach Research Articles

Population pharmacokinetics of PF-06438179/GP1111 (an infliximab biosimilar) and reference infliximab in patients with moderately to severely active rheumatoid arthritis

ABSTRACT Background: PF-06438179/GP1111 (PF-SZ-IFX) is an infliximab (IFX) biosimilar. Pharmacokinetic (PK) similarity of PF-SZ-IFX and reference IFX authorized in the European Union (ref-IFX-EU) and in the US (ref-IFX-US) was demonstrated in healthy subjects. Safety and efficacy of PF-SZ-IFX were investigated in a multinational, double-blind, randomized study in rheumatoid arthritis (RA) patients. This work aims to evaluate the population pharmacokinetics (PopPK) of ref-IFX-EU and PF-SZ-IFX in RA patients. Research design and methods: Patients with moderately to severely active RA (N = 650) were randomized 1:1 to PF-SZ-IFX or ref-IFX-EU. PopPK modeling with data collected from the study was performed using a nonlinear mixed-effects approach (NONMEM 7.2.0). Results: The PK of ref-IFX-EU and PF-SZ-IFX were adequately described using a two-compartment model with linear elimination. Clearance (CL) estimates were 0.014 L/h and 0.015 L/h for PF-SZ-IFX and ref-IFX-EU, with inter-individual variability (IIV) on CL of 43.1% and 40.1%, respectively. Volumes of distribution in the central compartment (V1) were 3.38 L and 3.57 L, with IIV on V1 of 28.1% and 23.7%, respectively. The same covariates of sex and antidrug antibody titers on CL, and body weight on V1, influenced the PK variability of ref-IFX-EU and PF-SZ-IFX. Conclusions: PopPK analysis revealed no appreciable differences between the PK of ref-IFX-EU and PF-SZ-IFX in RA patients. Trial registration: ClinicalTrials.gov identifier: NCT02222493.

Modelling site index of Chinese fir plantations using a random effects model across regional site types in Hunan province, China

Site index is a popular method used for assessing site productivity. Based on sampling of 418 plots of Chinese fir (Cunninghamia lanceolata) across Hunan province, China, a site index model of this species in relation to site type as a random effect was developed. First, site factors (topography) influencing stand dominant height were screened as main factors through one-way ANOVA analysis. The results showed that elevation was the most significant factor, followed by soil type, aspect, and slope. Second, ten widely base models were developed, and found that these models performed poorly (R2 ranged from 0.3850 to 0.4977). Although the models performed poorly, the best base model (M4) was selected (R2 = 0.4977). Considering the influence of site factors on the site index curve, the different site factors and its combination as a random effect were simulated by nonlinear mixed-effect approach. The R2 values had improved from 0.3850 ∼ 0.4977 to 0.5132 ∼ 0.9018, and the model with combined site type (110 levels) performed best (R2 = 0.9018). K-means cluster method was used to cluster the 110 site types into 8 site type groups, and then a mixed-effects model with random effect of site type groups was developed and resulted in improved model performance (R2 = 0.9268). The results have practical utility and guidelines for regional level forest productivity estimation.

Improving individualised dosimetry in radioiodine therapy for hyperthyroidism using population biokinetic modelling

The application of an individualised dosimetric procedure for radioiodine therapy requires the intensive use of resources in nuclear medicine facilities. In practice, the amount of data taken per patient is too limited to obtain an accurate estimate of the absorbed dose in the thyroid. The individualised absorbed dose estimates can be enhanced using statistical tools for population-based approaches. The aim of this work was to build a population biokinetic model of thyroid uptake and elimination of radioiodine using a nonlinear mixed-effects approach in patients with Graves’ disease. Input data for the model development were taken from a dosimetric method based on 123I imaging data. 123I decay-corrected uptake values were estimated at 4, 24, and 96 h post-administration and for 58 patients. The root mean squared error (RMSE) for predicted 123I uptake values by the fitted model was 4%. The root mean squared error of prediction (RMSEP) for out-of-sample 123I uptake values, computed by a leave-one-out cross-validation, was 12%. We calculated 131I activity to administer from out-of-sample predicted 123I uptake values and compared the result with that calculated from observed 123I uptake values. RMSEP values for therapeutic activity revealed that there were measuring points with higher weight than others in the model. The mixed-effects approach can be used to enhance the accuracy of dosimetric calculations in therapies using 131I. Assessing the accuracy of the predictive model enables choosing among different time-sampling schedules of the radioiodine thyroid uptake curve. This methodology can also be applied in other areas of radiation dosimetry.

Rapid onset of effect of benralizumab on morning peak expiratory flow in severe, uncontrolled asthma

BackgroundBenralizumab is a unique eosinophil-depleting monoclonal antibody that significantly reduces asthma exacerbations, improves lung function and asthma symptoms, and permits the reduction of maintenance oral corticosteroid dosage for patients with severe, uncontrolled eosinophilic asthma. ObjectiveTo assess benralizumab's onset of action and efficacy by examining change in morning peak expiratory flow (PEF) after initiation of treatment in the phase 3 clinical trials SIROCCO, CALIMA, and ZONDA. MethodsMixed-model repeated-measures analysis was used to calculate PEF using daily least squares mean changes from baseline in morning PEF as well as differences between the benralizumab every 8 weeks (first 3 doses every 4 weeks) and placebo groups. A Bayesian nonlinear mixed-effects approach with an exponential relationship was used to model trial data to determine time to clinically meaningful improvement in morning PEF (defined as ≥25 L/min). ResultsLeast squares mean morning PEF improvement from baseline was numerically greater by Day 2 after initiation of benralizumab therapy in all 3 trials. The Bayesian nonlinear mixed-effects model indicated that PEF improvement reached the clinically meaningful threshold within 3 weeks in SIROCCO and CALIMA and 2 weeks in ZONDA. ConclusionIn 3 phase 3 randomized clinical trials, benralizumab provided notable improvement in morning PEF 2 days after initiation and clinically meaningful improvements within 3 weeks for patients with severe, uncontrolled eosinophilic asthma. The rapid improvement in PEF demonstrated in these trials suggests that benralizumab's unique mechanism of action rapidly improves lung function for patients with severe, eosinophilic asthma. Trial RegistrationClinicalTrials.gov Identifiers: NCT01928771 (SIROCCO), NCT01914757 (CALIMA), and NCT02075255 (ZONDA).

A Simple and Flexible Computational Framework for Inferring Sources of Heterogeneity from Single-Cell Dynamics.

Single-cell time-lapse data provide the means for disentangling sources of cell-to-cell and intra-cellular variability, a key step for understanding heterogeneity in cell populations. However, single-cell analysis with dynamic models is a challenging open problem: current inference methods address only single-gene expression or neglect parameter correlations. We report on a simple, flexible, and scalable method for estimating cell-specific and population-average parameters of non-linear mixed-effects models of cellular networks, demonstrating its accuracy with a published model and dataset. We also propose sensitivity analysis for identifying which biological sub-processes quantitatively and dynamically contribute to cell-to-cell variability. Our application to endocytosis in yeast demonstrates that dynamic models of realistic size can be developed for the analysis of single-cell data and that shifting the focus from single reactions or parameters to nuanced and time-dependent contributions of sub-processes helps biological interpretation. Generality and simplicity of the approach will facilitate customized extensions for analyzing single-cell dynamics.

Safety, tolerability, pharmacokinetics and pharmacokinetic-pharmacodynamic modelling of the novel H4 receptor inhibitor SENS-111 using a modified caloric test in healthy subjects.

A Phase 1 study was performed to evaluate safety, pharmacokinetics (PK) and pharmacodynamics (PD) of the selective histamine H4 receptor antagonist SENS-111, an oral small molecule. One hundred healthy subjects were randomized in a placebo-controlled, double-blind study evaluating single-ascending doses (SAD; 100-500mg) and multiple-ascending doses (MAD; 50-150mgday-1 , 4 days; 200-250mgday-1 , 7 days). Effects of SENS-111 on nystagmus and vertigo induced by modified caloric tests were measured in the MAD studies. Population PK and PK/PD models were developed using a nonlinear mixed-effects approach. SENS-111 was well tolerated with mild to moderate events. No sedation was reported. A maximal tolerated dose was not reached. Dose-proportional increases in concentrations were seen up to 200mg and more than dose-proportional thereafter, with mean half-life between 24 and 56h. The caloric test induced mild but measurable vertigo and nystagmus with large intra/inter-individual variation for all parameters. SENS-111 did not significantly impact nystagmus but significantly improved latency of vertigo appearance/disappearance, duration and European Evaluation of Vertigo questionnaire parameters vs. baseline. A two-compartment model with first-order absorption, distribution and elimination best fit the data. PK/PD indirect modelling applied to vertigo duration and latency of appearance indicated maximum activity between 100 and 500ngml-1 plasma concentrations, corresponding to 100 and 200mgday-1 , which are appropriate for clinical efficacy evaluations in vestibular diseases. SENS-111 is a well-tolerated first-in-class H4 receptor antagonist with acceptable PK for oral daily dosing. PK/PD modelling determined plasma concentrations and doses for efficacy studies in patients with vertigo symptoms.

P081] A population-based and mixed model approach for enhancing iodine biokinetics in radioiodine therapy for hyperthyroidism

Purpose Individualized calculation of radioiodine 131 I activity for the treatment of benign thyroid disease is imperative according to Euratom Directive 59/13. In general, measurements taken per patient are very limited to obtain an accurate estimate of the absorbed dose in the thyroid. The application of statistical tools can improve the accuracy of the biokinetic parameters used to calculate personalized activity. The aim of this work was to model the population biokinetics of thyroid for hyperthyroid patients using a nonlinear mixed-effects approach. Methods The model data were obtained from planar scintigraphic images obtained 4, 24 and 96 hours after the pretherapeutic administration of 111 MBq of 123 I-NaI . A total of 174 uptake measurements corrected for physical decay in patients who received 131 I - NaI for Graves’ disease were included in the study. The root mean squared error (RMSE), coefficient of determination (R2) and leave-one-out cross-validation (LOOCV) method were used to evaluate the goodness of the fit and performance of the model. The predicted and calculated uptake values were used to calculate the activity of 131 I for giving 120 Gy in thyroid from the MIRD (Medical Internal Radiation Dose) formula and the differences were evaluated using RMSE. Results The model fit to the data was very good (R2=0.9977 and RMSE=4%) and the standard deviation of the residual error was of 3%. The fitted model predicts with high accuracy the left-out observations and the calculated activities of I-131(RMSE=12%) and especially, when the 24-h observation was left out (RMSE=7% and 8.5%,respectively). The highest RMSE corresponded to the 96-hours measurement. Conclusions A population-based and mixed model approach can enhance the accuracy of biokinetic parameters included in the MIRD formula for the calculation of the optimum therapeutic activity of 131I. A high ability for predicting new observations and observed uptake values was found. The quantification of the accuracy of prediction of the model enables choose among different time sampling schedules of the radioiodine thyroid uptake curve. In our case, we could use a 2-point schedule with a low loss of accuracy against a 3-points schedule. This methodology could be extended to other areas where repeated measurements are made.

Nonlinear Mixed-Effects Models for PET Data.

The current state-of-the-art for compartment modeling of dynamic PET data can be described as a two-stage approach. In Stage 1, individual estimates of kinetic parameters are obtained by fitting models using standard techniques, such as nonlinear least squares, to each individual's data one subject at a time. Population-level effects, such as the difference between diagnostic groups, are analyzed in Stage 2 using standard statistical methods by treating the individual estimates as if they were observed data. While this approach is generally valid, it is possible to increase efficiency and precision of the analysis, allow more complex models to be fitted, and also to permit parameter-specific investigation by fitting data across subjects simultaneously. We explore the application of nonlinear mixed-effects (NLME) models for estimation and inference in this setting. In the NLME framework, subjects are modeled simultaneously through the inclusion of random effects of subjects for each kinetic parameter; meanwhile, population parameters are estimated directly in a joint model. Simulation results indicate that NLME outperforms the two-stage approach in estimating group-level effects and also has improved power to detect differences across groups. We applied our NLME approach to clinical PET data and found effects not detected by the two-stage approach. The proposed NLME approach is more accurate and correspondingly more powerful than the two-stage approach in compartment modeling of PET data. The NLME method can broaden the methodological scope of PET modeling because of its efficiency and stability.

Climatic Effects on Site Productivity of Red Pine Plantations

Climatic effects on site productivity of red pine (Pinus resinosa Aiton) plantations were examined. A stand height/site index equation with climate variables incorporated in the height growth model was developed from stem analysis data. These data were collected from 90 dominant or co-dominant red pine trees sampled from even-aged monospecific plantations located on 30 sites (3 trees per site) broadly distributed across Ontario, Canada. The stand height equation was fit using a nonlinear mixed-effects approach. Climatic effects on site productivity were examined by regressing site index against commonly reported climate variables. Three site-specific climate attributes explained 63% of the variability in observed site index. These climate variables were examined to be incorporated into the stand height growth models. However, only two climate variables—growing season total precipitation (GSTP) and growing season mean temperature (GSMT)—were significant in the model without random effects and autocorrelation. In the presence of random effects and autocorrelation, however, only GSMT remained significant in the model. Stand heights were predicted for three randomly selected locations (eastern, western, and southern Ontario) for the growth periods 2011 to 2040 and 2041 to 2070 under two (2.6 and 8.5 Watts/m2) emissions trajectories known as Representative Concentration Pathways (RCPs). At the end of both growth periods, projected heights were reduced under both climate change scenarios (compared to those under a no-climate-change scenario) at all locations. Under both scenarios, the decrease in height growth was more pronounced in the south than in the east or west. The developed height growth models can be used to estimate stand heights for red pine plantations in a changing climate. Using the same models, site index of a plot/stand can also be estimated by calculating height at a given base (index) age. In the absence of climate data, the model fitted without climate variables can be applied to estimate stand heights and site indices.

Investigation of factors influencing radioiodine (131I) biokinetics in patients with benign thyroid disease using nonlinear mixed effects approach.

Radioiodine (131I) therapy is the common treatment option for benign thyroid diseases. The objective of this study was to characterize 131I biokinetics in patients with benign thyroid disease and to investigate and quantify the influence of patients' demographic and clinical characteristics on intra-thyroidal 131I kinetics by developing a population model. Population pharmacokinetic analysis was performed using a nonlinear mixed effects approach. Data sets of 345 adult patients with benign thyroid disease, retrospectively collected from patients' medical records, were evaluated in the analysis. The two-compartment model of 131I biokinetics representing the blood compartment and thyroid gland was used as the structural model. Results of the study indicate that the rate constant of the uptake of 131I into the thyroid (ktu) is significantly influenced by clinical diagnosis, age, functional thyroid volume, free thyroxine in plasma (fT4), use of anti-thyroid drugs, and time of discontinuation of therapy before administration of the radioiodine (THDT), while the effective half-life of 131I is affected by the age of the patients. Inclusion of the covariates in the base model resulted in a decrease of the between subject variability for ktu from 91 (3.9) to 53.9 (4.5)%. This is the first population model that accounts for the influence of fT4 and THDT on radioiodine kinetics. The model could be used for further investigations into the correlation between thyroidal exposure to 131I and the outcome of radioiodine therapy of benign thyroid disease as well as the development of dosing recommendations.

Population pharmacokinetics of enoxaparin in early stage of paediatric liver transplantation.

Preventing post-liver transplantation (LT) hepatic artery and portal vein thrombosis includes enoxaparin administration. Enoxaparin pharmacokinetics (PK) has not been investigated in children following LT. We described an enoxaparin PK model in 22 children the first week following LT. Anti-Xa activity time-courses were analysed using a nonlinear mixed effects approach with Monolix version 2016R. Anti-Xa activity time-courses were well described by a one-compartment model with first order absorption and elimination. Bodyweight prior to surgery (BWPREOP ) and the related postoperative variation (BW(t)) were the main covariates explaining CL and V between subject variabilities. Parameter estimates were CLi =CLTYP * (BWPREOP /70)3/4 ; Vi =VTYP * (BW(t)/70)1 ; where typical clearance (CLTYP ) and typical volume of distribution (VTYP ) were 1.23lh-1 and 14.6l, respectively. Standard dosing regimens of 50IUkg-1 12h-1 were insufficient to reach the target range of anti-Xa activity of 0.2-0.4IUml-1 . Specifically, seven children (32%) never attained the target range during the whole period of treatment and all children were at least once underdosed. According to the final results, we simulated individualized dosing regimens within 4h following the first administration. More than 100IUkg-1 12h-1 are suggested to reach the target range of anti-Xa activity of 0.2-0.4IUml-1 from the first day. Thanks to this model, the initial and maintenance doses could be assessed to rapidly achieve the target range. Higher doses per kg, especially in the youngest children, are suggested.

A Population WB-PBPK Model of Colistin and its Prodrug CMS in Pigs: Focus on the Renal Distribution and Excretion.

The objective was the development of a whole-body physiologically-based pharmacokinetic (WB-PBPK) model for colistin, and its prodrug colistimethate sodium (CMS), in pigs to explore their tissue distribution, especially in kidneys. Plasma and tissue concentrations of CMS and colistin were measured after systemic administrations of different dosing regimens of CMS in pigs. The WB-PBPK model was developed based on these data according to a non-linear mixed effect approach and using NONMEM software. A detailed sub-model was implemented for kidneys to handle the complex disposition of CMS and colistin within this organ. The WB-PBPK model well captured the kinetic profiles of CMS and colistin in plasma. In kidneys, an accumulation and slow elimination of colistin were observed and well described by the model. Kidneys seemed to have a major role in the elimination processes, through tubular secretion of CMS and intracellular degradation of colistin. Lastly, to illustrate the usefulness of the PBPK model, an estimation of the withdrawal periods after veterinary use of CMS in pigs was made. The WB-PBPK model gives an insight into the renal distribution and elimination of CMS and colistin in pigs; it may be further developed to explore the colistin induced-nephrotoxicity in humans.

Mathematical modeling and simulation in animal health. Part III: Using nonlinear mixed-effects to characterize and quantify variability in drug pharmacokinetics.

A common feature of human and veterinary pharmacokinetics is the importance of identifying and quantifying the key determinants of between-patient variability in drug disposition and effects. Some of these attributes are already well known to the field of human pharmacology such as bodyweight, age, or sex, while others are more specific to veterinary medicine, such as species, breed, and social behavior. Identification of these attributes has the potential to allow a better and more tailored use of therapeutic drugs both in companion and food-producing animals. Nonlinear mixed effects (NLME) have been purposely designed to characterize the sources of variability in drug disposition and response. The NLME approach can be used to explore the impact of population-associated variables on the relationship between drug administration, systemic exposure, and the levels of drug residues in tissues. The latter, while different from the method used by the US Food and Drug Administration for setting official withdrawal times (WT) can also be beneficial for estimating WT of approved animal drug products when used in an extralabel manner. Finally, NLME can also prove useful to optimize dosing schedules, or to analyze sparse data collected in situations where intensive blood collection is technically challenging, as in small animal species presenting limited blood volume such as poultry and fish.

Comparative population pharmacokinetics and absolute oral bioavailability of COX-2 selective inhibitors celecoxib, mavacoxib and meloxicam in cockatiels (Nymphicus hollandicus)

Selective COX-2 inhibitors are non-steroidal anti-inflammatory drugs which directly target cyclooxygenase-2 (COX-2), an enzyme mainly responsible for induction of inflammation, pyresis and pain. Although commonly used in avian medicine, limited pharmacokinetic (PK) data in domestic and companion birds are available. In this study, PK parameters and absolute oral bioavailability expressed as percentage (F%) of celecoxib (10 mg/kg BW), mavacoxib (4 mg/kg BW) and meloxicam (1 mg/kg BW) were determined following single oral (PO) and intravenous (IV) administration to cockatiels (Nymphicus hollandicus). The drugs were quantified in plasma by liquid chromatography-tandem mass spectrometry. Data were processed using the nonlinear mixed effects (NLME) approach. In contrast to celecoxib (T1/2el = 0.88 h) and meloxicam (T1/2el = 0.90 h), mavacoxib has a prolonged elimination half-life (T1/2el = 135 h) following oral administration of a commercial formulation (CF). High to complete oral absorption was observed following oral administration of celecoxib (F% = 56–110%) and mavacoxib (F% = 111–113%), CF and standard solutions, respectively. In contrast, the F% of meloxicam was low (F% = 11%). Based on the presented results, a less frequent dosing of mavacoxib is proposed compared to celecoxib and meloxicam. However, pharmacodynamic and safety studies are necessary to further investigate the use of these NSAIDs in cockatiels.

Population pharmacokinetics of the MEK inhibitor selumetinib and its active N-desmethyl metabolite: data from 10 phase I trials.

The aims of the study were to characterize the pharmacokinetics (PK) of selumetinib (AZD6244; ARRY-142886), a mitogen-activated protein kinase kinase (MEK) 1/2 inhibitor in clinical development for various indications, and its N-desmethyl metabolite in healthy volunteers, and evaluate clinically important covariates. A pooled-population PK analysis was performed using a nonlinear mixed-effects approach with plasma concentration data from 346 subjects who received single oral doses of selumetinib 20-75mg across 10 phase I studies. Absolute bioavailability was determined using intravenous [14 C] selumetinib. A two-compartment linear model with sequential zero-first order absorption and a lag time for the zero-order process was described for selumetinib PK. N-desmethyl metabolite disposition was described by a single compartment with linear elimination, without back transformation. The parent-only and joint models generally described pooled data adequately. For the median subject, not taking interacting drugs, estimates for clearance (CL) and central volume of distribution (V2) for selumetinib in the final joint model were 12.7l h-1 and 35.6l, respectively. Food effects, comedication with itraconazole [a cytochrome P450 (CYP) 3A4 inhibitor], fluconazole (a CYP2C19 inhibitor) and rifampicin (a CYP3A4 inducer) and formulation effects were incorporated into the base model a priori. Race and hepatic function were also influential in the PK model. Additional covariates affecting selumetinib disposition identified from covariate analysis were age on V2, bilirubin on CL, and weight on CL and V2. Analysis confirmed previous clinical pharmacology study findings of drug-drug interactions and food effects, with additional covariates that influence selumetinib and N-desmethyl selumetinib PK identified. Dose modifications based on these additional covariates were not considered necessary.

A population pharmacokinetic meta-analysis of custirsen, an antisense oligonucleotide, in oncology patients and healthy subjects.

Custirsen (OGX-011/TV-1011), a second-generation antisense oligonucleotide that reduces clusterin production, is under investigation with chemotherapy in prostate and lung cancer. This meta-analysis evaluated the population pharmacokinetics (PK) of custirsen in cancer patients and healthy subjects. The population PK analysis used custirsen plasma concentrations from five Phase 1 studies, one Phase 1/2 study, and one Phase 3 study in two stages. Cancer patients received multiple doses of custirsen (40-640mg intravenously over 120min) with chemotherapy; healthy subjects received single or multiple doses (320-640mg). An interim population PK model was developed using a nonlinear mixed-effect approach incorporating data from four Phase 1 or 1/2 studies, followed by model refinement and inclusion of two Phase 1 and one Phase 3 studies. The final model was developed with 5588 concentrations from 631 subjects with doses of 160-640mg. Custirsen PK was adequately described by a three-compartment model with first-order elimination. For a representative 66-year-old individual with body weight 82kg and serum creatinine level 0.933mgdl-1 , the estimated typical (95% CI) parameter values were clearance (CL) = 2.36 (2.30-2.42) lh-1 , central volume of distribution (V1 ) = 6.08 (5.93-6.23) l, peripheral volume of distribution (V2 ) = 1.13 (1.01-1.25) l, volume of the second peripheral compartment (V3 ) = 15.8 (14.6-17.0) l, inter-compartmental clearance Q2 = 0.0755 (0.0689-0.0821) lh-1 , and Q3 = 0.0573 (0.0532-0.0614) lh-1 . Age, weight and serum creatinine were predictors of CL; age was a predictor of Q3 . A population PK model for custirsen was successfully developed in cancer patients and healthy subjects, including covariates contributing to variability in custirsen PK.

Population Pharmacokinetics and Pharmacodynamics of AG-519, a Pyruvate Kinase Activator for the Treatment of Pyruvate Kinase Deficiency, in Human Healthy Volunteers

INTRODUCTIONPyruvate kinase (PK) deficiency is a life-long chronic hemolytic anemia with a variable clinical presentation, ranging from mild to life-threatening, and is associated with severe, debilitating co-morbidities. PK deficiency is caused by mutations in the PKLR gene, which in the red blood cell (RBC) results in defective pyruvate kinase isoform R (PK-R). PK-R catalyzes the final and irreversible step in glycolysis, the process on which mature RBCs rely almost exclusively to generate the energy carrier molecule, adenosine triphosphate (ATP). PK-R is thus a key enzyme for maintaining RBC energy levels, and it has been proposed that ATP levels are critical for optimally maintaining RBC membrane integrity. PK-deficient RBCs and their progenitors are characterized by changes in metabolism associated with defective glycolysis, including a build-up of phosphoenolpyruvate (PEP) and 2,3-diphosphoglycerate (2,3-DPG), and lowered ATP levels.AG-519 is a potent, highly selective and orally bioavailable PK-R activator shown preclinically to have none of the aromatase inhibitory effects that were observed with AG-348, the first small molecule PK-R activator to enter clinical trials. It is hypothesized that intervention with AG-519 restores glycolytic pathway activity and normalizes RBC metabolism. Treatment of PK-deficient patient RBCs ex vivo with AG-519 results in increased ATP levels, and reductions in 2,3-DPG, consistent with pharmacological activation of PK-R enzyme activity. This analysis integrates the pharmacokinetic and pharmacodynamic (PK/PD) properties of AG-519 in healthy volunteers using population PK/PD modeling and simulation.METHODSPK/PD modeling using a non-linear mixed effects approach was performed to understand the pharmacokinetics of AG-519 and PK/PD relationship of AG-519 to 2,3-DPG, ATP and PK-R enzyme activity in humans. The PK/PD model integrated data from a phase 1, single-center, randomized, double-blind, placebo-controlled study. Data in single and multiple ascending dose escalation arms were included in the analysis, which comprises a total of 88 human volunteers. AG-519 dose levels ranged from 10-1250 mg. Blood was collected from all patients to assess AG-519 pharmacokinetics and levels of ATP and 2,3-DPG in blood, as well as PK-R activity. Population simulations using the final model were performed to examine the dose-exposure-biomarkers relationship.RESULTSAG-519 showed rapid absorption kinetics following oral administration. Area under the concentration-time curve of plasma AG-519 increased in a dose-proportional manner following single and multiple dosing. A three-compartment model with non-linear absorption compartment and linear elimination best described the pharmacokinetics of AG-519. Systemic clearance appeared to be time-invariant and no auto-induction was observed with multiple dosing. The PK/PD relationship between plasma AG-519 and ATP or 2,3-DPG in human volunteers was best fitted by a turnover model where the drug effect was described by an Emax model. A direct Emax model best described the relationship between plasma AG-519 and PK-R enzyme activity. Evaluation of ATP and 2,3-DPG levels and PK-R activity confirmed the potent effect of AG-519 on PK-R. A direct comparison of AG-519 target engagement and biomarker response to AG-348 will also be presented. Population PK/PD model simulations suggested that the doses selected in the phase 1 study covered a large exposure-response range of the three biomarkers, and provided a systematic and integrated framework for the understanding of AG-519 pharmacokinetics and pharmacodynamics, as well as a rationale for dose selection in future trials.CONCLUSIONSThis study represents a comprehensive longitudinal PK/PD analysis of AG-519 in humans. This integrated PK/PD model formed the basis for understanding the exposure-response relationship of the ongoing phase 1 study and provided guidance on dose selection to inform the future development of AG-519. DisclosuresLe:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Cohen:Agios Pharmaceuticals, Inc.: Consultancy. Barbier:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Merica:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Kung:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Kosinski:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Biller:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Yang:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership.

Optimization of the strength of the efavirenz/lamivudine/abacavir fixed-dose combination for paediatric patients.

Child-friendly, low-cost, solid, oral fixed-dose combinations (FDCs) of efavirenz with lamivudine and abacavir are urgently needed to improve clinical management and drug adherence for children. Data were pooled from several clinical trials and therapeutic drug monitoring datasets from different countries. The number of children/observations was 505/3667 for efavirenz. Population pharmacokinetic analyses were performed using a non-linear mixed-effects approach. For abacavir and lamivudine, data from 187 and 920 subjects were available (population pharmacokinetic models previously published). Efavirenz/lamivudine/abacavir FDC strength options assessed were (I) 150/75/150, (II) 120/60/120 and (III) 200/100/200 mg. Monte Carlo simulations of the different FDC strengths were performed to determine the optimal dose within each of the WHO weight bands based on drug efficacy/safety targets. The probability of being within the target efavirenz concentration range 12 h post-dose (1-4 mg/L) varied between 56% and 60%, regardless of FDC option. Option I provided a best possible balance between efavirenz treatment failure and toxicity risks. For abacavir and lamivudine, simulations showed that for option I >75% of subjects were above the efficacy target. According to simulations, a paediatric efavirenz/lamivudine/abacavir fixed-dose formulation of 150 mg efavirenz, 75 mg lamivudine and 150 mg abacavir provided the most effective and safe concentrations across WHO weight bands, with the flexibility of dosage required across the paediatric population.

A whole-body physiologically based pharmacokinetic (WB-PBPK) model of ciprofloxacin: a step towards predicting bacterial killing at sites of infection

The purpose of this study was to develop a whole-body physiologically based pharmacokinetic (WB-PBPK) model for ciprofloxacin for ICU patients, based on only plasma concentration data. In a next step, tissue and organ concentration time profiles in patients were predicted using the developed model. The WB-PBPK model was built using a non-linear mixed effects approach based on data from 102 adult intensive care unit patients. Tissue to plasma distribution coefficients (Kp) were available from the literature and used as informative priors. The developed WB-PBPK model successfully characterized both the typical trends and variability of the available ciprofloxacin plasma concentration data. The WB-PBPK model was thereafter combined with a pharmacokinetic–pharmacodynamic (PKPD) model, developed based on in vitro time-kill data of ciprofloxacin and Escherichia coli to illustrate the potential of this type of approach to predict the time-course of bacterial killing at different sites of infection. The predicted unbound concentration–time profile in extracellular tissue was driving the bacterial killing in the PKPD model and the rate and extent of take-over of mutant bacteria in different tissues were explored. The bacterial killing was predicted to be most efficient in lung and kidney, which correspond well to ciprofloxacin’s indications pneumonia and urinary tract infections. Furthermore, a function based on available information on bacterial killing by the immune system in vivo was incorporated. This work demonstrates the development and application of a WB-PBPK–PD model to compare killing of bacteria with different antibiotic susceptibility, of value for drug development and the optimal use of antibiotics .

Real-Time 3D Imaging at the Single Molecule Level of Signal Transduction in Saccharomyces CerevisiÆ Responding to Environmental Changes

Recent progress(1) has shown how Saccharomyces cerevisiae adapts to varying environmental glucose concentrations. Focussing on the Snf1/Mig1 pathway we have shown the reversibility and flux of signalling kinases and suppressor proteins over the nuclear membrane.The signalling protein Snf1 and suppressors have been tagged with fluorescent proteins in colour pairs, using eGFP and mCherry. After confirmation that the proteins are still active and not hindered by the tag, this allows wavelength selective imaging of protein-protein interactions to be shown.Astigmatic microscopy gives high three-dimensional resolution with precisions of some tens of nanometres on the three spatial axes. High-speed imaging at the few millisecond scale allows resolving of diffusing single protein locations.A sample chamber consisting of a microfluidic flow channel with multiple inlets allows us to within seconds switch between two different environments, e.g. high and low glucose conditions or the introduction of inhibitors. Yeast responds to a glucose concentration change over a period in the order of a few minutes(2). The fluorescent proteins used photobleach after a few tens of milliseconds illumination so short 5-frame bursts of data were recorded at selected time points and singular molecules tracked within these windows.Preliminary data analysis shows migration of Mig1 in both directions in response to environment change.1. Wollman AJM, Shashkova S, Hedlund E, Hohmann S, Leake MC. Observing Signal Transduction Directly at the Single-Molecule Level in Live Eukaryotic Cells. Biophys J [Internet]. Biophysical Society; 2015;108(2):570a. Available from: http://linkinghub.elsevier.com/retrieve/pii/S00063495140433312. Almquist J, Bendrioua L, Adiels CB, Goksor M, Hohmann S, Jirstrand M. A Nonlinear Mixed Effects Approach for Modeling the Cell-To-Cell Variability of Mig1 Dynamics in Yeast. PLoS One. 2015;