Efficacy of Amorolfine in Onychomycosis Treatment: A Mixed-Effects Models and Multivariate Logistic Regression Analysis.

BACKGROUND: Onychomycosis (OM) is a common nail infection treated with amorolfine hydrochloride nail lacquer in China. Monitoring drug concentrations and using dermoscopy to evaluate treatment efficacy may provide new insights. OBJECTIVE: The study aims to analyse amorolfine concentrations in nails with mild to moderate OM, assess treatment outcomes using dermoscopy and explore factors influencing drug concentrations and efficacy. METHODS: Patients with mild to moderate OM confirmed by fungal microscopy were enrolled. Amorolfine nail lacquer was applied twice weekly for 36 weeks. Monthly nail samples measured amorolfine concentrations using liquid chromatography. Dermoscopy was performed before and after treatment to evaluate responses. Mixed-effects models and logistic regression analysed factors affecting drug concentrations and outcomes. RESULTS: Ninety-seven nails were included. Amorolfine concentrations increased over time, with higher levels in females, fingernails, 2nd-5th digits and superficial white OM (p < 0.05). Age was a risk factor, while drug concentration and OM type were protective for clinical efficacy (p < 0.05). Peak concentration correlated with clinical (r = 0.487, p = 0.000) and mycological (r = 0.433, p = 0.000) responses. Dermoscopic features improved significantly in successful cases (p < 0.05). LIMITATIONS: In the assessment of fungal efficacy, only fungal microscopy was used, and fungal cultures were not performed. The study was limited by a small sample size and the lack of a longer follow-up to assess relapse. CONCLUSION: Amorolfine concentrations vary with patient and nail characteristics, influencing efficacy. Dermoscopy is valuable for monitoring OM treatment.

Evaluation of adherence to abiraterone therapy in prostate cancer patients based on a population pharmacokinetic model.

AIMS: Abiraterone treatment requires regular drug intake under fasting conditions due to pronounced food effect, which may impact patient adherence. The aim of this prospective study was to evaluate adherence to abiraterone treatment in patients with prostate cancer. To achieve this aim, an abiraterone population pharmacokinetic model was developed and patients' adherence has been estimated by comparison of measured levels of abiraterone with population model-based simulations. METHODS: A total of 1469 abiraterone plasma levels from 83 healthy volunteers collected in a bioequivalence study were analysed using a nonlinear mixed-effects model. Monte Carlo simulation was used to describe the theoretical distribution of abiraterone pharmacokinetic profiles at a dose of 1000 mg once daily. Adherence of 36 prostate cancer patients treated with abiraterone was then evaluated by comparing the real abiraterone concentration measured in each patient during follow-up visit with the theoretical distribution of profiles based on simulations. Patients whose abiraterone levels were ˂5th or ˃95th percentile of the distribution of simulated profiles were considered to be non-adherent. RESULTS: Based on this evaluation, 13 patients (36%) have been classified as non-adherent. We observed significant association (P = .0361) between richness of the breakfast and rate of non-adherence. Adherent patients reported significantly better overall condition in self-assessments (P = .0384). A trend towards a higher occurrence of adverse effects in non-adherent patients was observed. CONCLUSIONS: We developed an abiraterone population pharmacokinetic model and proposed an advanced approach to medical adherence evaluation. Due to the need for administration under fasting conditions, abiraterone therapy is associated with a relatively high rate of non-adherence.

Vancomycin loading dose individualization in a population of obese patients undergoing haemodialysis based on population pharmacokinetic model.

This study aimed to develop a vancomycin population pharmacokinetic model in obese adult patients treated with intermittent haemodialysis and propose a model-based loading dose strategy ensuring attainment of newly recommended AUC-based PK/PD target. Retrospective cross-sectional analysis was performed among obese haemodialysis dependent adult patients treated with intravenous vancomycin. A pharmacokinetic population model was developed using a nonlinear mixed-effects modelling approach and Monte Carlo simulations were used to identify the optimal loading dose for PK/PD target attainment during the first 48 h of treatment. Therapeutic drug monitoring data from 27 patients with a BMI of 30.2-52.9 kg/m2 were analysed. Among all tested variables, only LBM as a covariate of vancomycin Vd significantly improved the model, while vancomycin CL did not correlate with any of the tested variables. The median (IQR) value from the conditional mean of individual estimates of Vd and CL was 68.4 (56.6-84.2) L and 0.86 (0.79-0.90) L/h, respectively. To ensure optimal vancomycin exposure during the first 48 h of therapy, the vancomycin loading dose of 1500, 1750, 2000, 2250, 2500 and 2750 mg should be administered to obese patients with a lean body mass of ˂50, 50-60, 60-70, 70-80, 80-85 and >85 kg, respectively.

Applying taper function models for black locust plantations in Greek post-mining areas.

A key process in forest management planning is the estimation of tree volume and, more specifically, merchantable volume. The ability to predict the cumulative stem volume relative to any upper stem diameter on standing trees or stands is essential for forest inventories and the management of forest resources. In the 1980s, the Hellenic Public Power Corporation (HPPC) started the rehabilitation of lignite post-mining areas in Greece by planting mainly black locust (Robinia pseudoacacia, L.). Today, these plantations occupy an area of approximately 2570 ha, but the stem volume has not yet been estimated. Therefore, we aimed to estimate the over- and under-bark stem volume using taper function models for 30 destructively sampled trees. Of the nineteen calibrated fixed-effects models, Kozak's (2004) equation performed best for both the over-bark and under-bark datasets, followed by Lee's (2003) and Muhairwe's (1999) equations. Two fixed effect models were compared with fitted coefficients from Poland and the United States confirming that the local model fits were better suited, as the foreign model coefficients caused an increase in root mean square error (RMSE) for stem diameter predictions of 13% and 218%, respectively. The addition of random effects on a single-stem basis for two coefficients of Kozak's (2004) equation improved the model fit significantly at 86% of the over-bark fixed effect RMSE and 69% for the under-bark model. Integrated taper functions were found to slightly outperform three volume equations for predictions of single stem volume over and under bark. Ultimately it was shown that these models can be used to precisely predict stem diameters and total stem volume for the population average as well as for specific trees of the black locust plantations in the study area.

Identification of non-adherence to adjuvant letrozole using a population pharmacokinetics approach in hormone receptor-positive breast cancer patients.

BACKGROUND: Letrozole, an aromatase inhibitor metabolised via CYP2A6 and CYP3A4/5 enzymes, is used as adjuvant therapy for women with hormone receptor (HR)-positive early breast cancer. The objective of this study was to quantify the impact of CYP2A6 genotype on letrozole pharmacokinetics (PK), to identify non-adherent patients using a population approach and explore the possibility of a relationship between non-adherence and early relapse. METHODS: Breast cancer patients enrolled in the prospective PHACS study (ClinicalTrials.gov NCT01127295) and treated with adjuvant letrozole 2.5 mg/day were included. Trough letrozole concentrations (Css,trough) were measured every 6 months for 3 years by a validated LC-MS/MS method. Concentration-time data were analysed using non-linear mixed effects modelling. Three methods were evaluated for identification of non-adherent subjects using the base PK model. RESULTS: 617 patients contributing 2534 plasma concentrations were included and led to a one-compartment PK model with linear absorption and elimination. Model-based methods identified 28 % of patients as non-adherent based on high fluctuations of their Css,trough compared to 3 % based on patient declarations. The covariate analysis performed in adherent subjects revealed that CYP2A6 intermediate (IM) and slow metabolisers (SM) had 21 % (CI95 % = 12 - 30 %) and 46 % (CI95 % = 41 - 51 %) lower apparent clearance, respectively, compared to normal and ultrarapid metabolisers (NM+UM). Early relapse (19 patients) was not associated with model-estimated, concentration-based or declared adherence in the total population (p = 0.41, p = 0.37 and p = 0.45, respectively). CONCLUSIONS: These findings will help future investigations focusing on the exposure-efficacy relationship for letrozole in adjuvant setting.

Population pharmacokinetics and covariate-based dosing individualization of voriconazole in lung transplant recipients.

This study aimed to explore pharmacokinetics of voriconazole and its covariates in lung transplant recipients using population approach in order to propose dosing individualization. Data from routine therapeutic drug monitoring in adult lung transplant recipients treated with oral voriconazole were analysed with a three-stage population pharmacokinetic model using nonlinear mixed-effects modelling. Monte Carlo simulations based on final voriconazole pharmacokinetic model were used to generate the theoretical distribution of pharmacokinetic profiles at various dosing regimens. A total of 78 voriconazole serum concentrations collected from 40 patients were included in pharmacokinetic analysis. The only significant covariate was age for voriconazole clearance. Population voriconazole apparent clearance started at 32.26 L/h and decreased by 0.021 L/h with each year of patient's age, while population apparent volume of distribution was 964.46 L. Based on this model, we have proposed an easy-to-use dosing regimen consisting of a loading dose of 400 mg every 12 h for the first 48 h of treatment followed by maintenance dose of 300 mg every 12 h in patients aged up to 59 years, or by maintenance dose of 200 mg every 12 h in patients aged above 59 years.

An automated respiratory data pipeline for waveform characteristic analysis.

Comprehensive and accurate analysis of respiratory and metabolic data is crucial to modelling congenital, pathogenic and degenerative diseases converging on autonomic control failure. A lack of tools for high-throughput analysis of respiratory datasets remains a major challenge. We present Breathe Easy, a novel open-source pipeline for processing raw recordings and associated metadata into operative outcomes, publication-worthy graphs and robust statistical analyses including QQ and residual plots for assumption queries and data transformations. This pipeline uses a facile graphical user interface for uploading data files, setting waveform feature thresholds and defining experimental variables. Breathe Easy was validated against manual selection by experts, which represents the current standard in the field. We demonstrate Breathe Easy's utility by examining a 2-year longitudinal study of an Alzheimer's disease mouse model to assess contributions of forebrain pathology in disordered breathing. Whole body plethysmography has become an important experimental outcome measure for a variety of diseases with primary and secondary respiratory indications. Respiratory dysfunction, while not an initial symptom in many of these disorders, often drives disability or death in patient outcomes. Breathe Easy provides an open-source respiratory analysis tool for all respiratory datasets and represents a necessary improvement upon current analytical methods in the field. KEY POINTS: Respiratory dysfunction is a common endpoint for disability and mortality in many disorders throughout life. Whole body plethysmography in rodents represents a high face-value method for measuring respiratory outcomes in rodent models of these diseases and disorders. Analysis of key respiratory variables remains hindered by manual annotation and analysis that leads to low throughput results that often exclude a majority of the recorded data. Here we present a software suite, Breathe Easy, that automates the process of data selection from raw recordings derived from plethysmography experiments and the analysis of these data into operative outcomes and publication-worthy graphs with statistics. We validate Breathe Easy with a terabyte-scale Alzheimer's dataset that examines the effects of forebrain pathology on respiratory function over 2 years of degeneration.

Stimulus-specific random effects inflate false-positive classification accuracy in multivariate-voxel-pattern-analysis: A solution with generalized mixed-effects modelling.

When conducting multivariate-voxel pattern analysis (MVPA), researchers typically compute the average accuracy for each subject and statistically test if the average accuracy is different from the chance level across subjects (by-subject analysis). We argue that this traditional by-subject analysis leads to inflated Type-1 error rates, regardless of the type of machine learning method used (e.g., support vector machine). This is because by-subject analysis does not consider the variance attributed to the idiosyncratic features of the stimuli that have a common influence on all subjects (i.e., the random stimulus effect). As a solution, we proposed the use of generalized linear mixed-effects modelling to evaluate average accuracy. This method only requires post-classification data (i.e., it does not consider the type of classification methods used) and is easily implemented in the analysis pipeline with common statistical software (SPSS, R, Python, etc.). Using both statistical simulation and real fMRI data analysis, we demonstrated that the traditional by-subject method indeed increases Type-1 error rates to a considerable degree, while generalized mixed-effects modelling that incorporates random stimulus effects can indeed maintain the nominal Type-1 error rates.

Population pharmacokinetic model-based dosing proposal for ampicillin prophylaxis in cardiac surgery patients with cardiopulmonary bypass.

The aim of this study was to describe and quantify pharmacokinetics of ampicillin used prophylactically in cardiac surgery both with and without cardiopulmonary bypass (CPB) using population pharmacokinetic analysis in order to propose an optimal dosing strategy. Adult patients undergoing cardiac surgery and treated with prophylactic dose of 2 g ampicillin were enrolled to this prospective study. Blood samples were collected according to the study protocol and ampicillin plasma concentrations were measured using HPLC/UV system. A three-stage population pharmacokinetic model using nonlinear mixed-effects modelling approach was developed. Totally 273 blood samples obtained from 20 patients undergoing cardiac surgery with the use of the CPB and 20 patients without CPB use were analyzed. Two-comparmental model best fits ampicillin concentration-time data. Mean ± SD body weight-normalized ampicillin central and peripheral volume of distribution was 0.12 ± 0.02 L/kg and 0.15 ± 0.03 L/kg, respectively, while mean ± SD ampicillin clearance in typical patient with eGFR of 1.5 mL/s/1.73 m2 was 1.17 ± 0.05 L/h. The use of CPB did not significantly affect the pharmacokinetics of ampicillin. When administering 2 g of ampicillin before surgery, an additional dose should be administered to reach the PK/PD target of fT > MIC = 50% if the operation lasts longer than 430 min in patients with moderate to severe renal impairment, 320 min in patients with mild renal impairment, 220 min in patients with normal renal function status or 140 min in patients with an augmented renal clearance.

Superiority of ceftazidime off-label high-dose regimen in PK/PD target attainment during treatment of extensively drug-resistant Pseudomonas aeruginosa infections in cancer patients.

AIM: The objective of this study was to evaluate off-label high-dose ceftazidime population pharmacokinetics in cancer patients with suspected or proven extensively drug-resistant (XDR) Pseudomonas aeruginosa infections and then to compare the achievement of the pharmacokinetic/pharmacodynamic (PK/PD) target after standard and off-label high-dose regimens using population model-based simulations. A further aim was to clinically observe the occurrence of adverse effects during the off-label high-dose ceftazidime treatment. METHODS: In patients treated with off-label high-dose ceftazidime (3 g every 6 h), blood samples were collected and ceftazidime serum levels measured using LC-MS/MS. A pharmacokinetic population model was developed using a nonlinear mixed-effects modelling approach and Monte Carlo simulations were then used to compare standard and high-dose regimens for PK/PD target attainment. RESULTS: A total of 14 cancer patients with serious infection suspected of XDR P. aeruginosa aetiology were eligible for PK analysis. XDR P. aeruginosa was confirmed in 10 patients as the causative pathogen. Population ceftazidime volume of distribution was 13.23 L, while clearance started at the baseline of 1.48 L/h and increased by 0.0076 L/h with each 1 mL/min/1.73 m2 of eGFR. High-dose regimen showed significantly higher probability of target attainment (i.e., 86% vs. 56% at MIC of 32 mg/L). This was translated into a very low mortality rate of 20%. Only one case of reversible neurological impairment was observed. CONCLUSION: We proved the superiority of the ceftazidime off-label high-dose regimen in PK/PD target attainment with very low occurrence of adverse effects. The off-label high-dose regimen should be used to optimize treatment of XDR P. aeruginosa infections.

Validation of the Alzheimer's disease-resemblance atrophy index in classifying and predicting progression in Alzheimer's disease.

Background: Automated tools for characterising dementia risk have the potential to aid in the diagnosis, prognosis, and treatment of Alzheimer's disease (AD). Here, we examined a novel machine learning-based brain atrophy marker, the AD-resemblance atrophy index (AD-RAI), to assess its test-retest reliability and further validate its use in disease classification and prediction. Methods: Age- and sex-matched 44 probable AD (Age: 69.13 ± 7.13; MMSE: 27-30) and 22 non-demented control (Age: 69.38 ± 7.21; MMSE: 27-30) participants were obtained from the Minimal Interval Resonance Imaging in Alzheimer's Disease (MIRIAD) dataset. Serial T1-weighted images (n = 678) from up to nine time points over a 2-year period, including 179 pairs of back-to-back scans acquired on same participants on the same day and 40 pairs of scans acquired at 2-week intervals were included. All images were automatically processed with AccuBrain® to calculate the AD-RAI. Its same-day repeatability and 2-week reproducibility were first assessed. The discriminative performance of AD-RAI was evaluated using the receiver operating characteristic curve, where DeLong's test was used to evaluate its performance against quantitative medial temporal lobe atrophy (QMTA) and hippocampal volume adjusted by intracranial volume (ICV)-proportions and ICV-residuals methods, respectively (HVR and HRV). Linear mixed-effects modelling was used to investigate longitudinal trajectories of AD-RAI and baseline AD-RAI prediction of cognitive decline. Finally, the longitudinal associations between AD-RAI and MMSE scores were assessed. Results: AD-RAI had excellent same-day repeatability and excellent 2-week reproducibility. AD-RAI's AUC (99.8%; 95%CI = [99.3%, 100%]) was equivalent to that of QMTA (96.8%; 95%CI = [92.9%, 100%]), and better than that of HVR (86.8%; 95%CI = [78.2%, 95.4%]) or HRV (90.3%; 95%CI = [83.0%, 97.6%]). While baseline AD-RAI was significantly higher in the AD group, it did not show detectable changes over 2 years. Baseline AD-RAI was negatively associated with MMSE scores and the rate of the change in MMSE scores over time. A negative longitudinal association was also found between AD-RAI values and the MMSE scores among AD patients. Conclusions: The AD-RAI represents a potential biomarker that may support AD diagnosis and be used to predict the rate of future cognitive decline in AD patients.

Before/after Bayes: A comparison of frequentist and Bayesian mixed-effects models in applied psychological research.

Bayesian methods are becoming increasingly used in applied psychological research. Previous researchers have thoroughly written about much of the details already, including the philosophy underlying Bayesian methods, computational issues associated with Bayesian model estimation, Bayesian model development and summary, and the role of Bayesian methods in the so-called replication crisis. In this paper, we seek to provide case studies comparing the use of frequentist methods to the use of Bayesian methods in applied psychological research. These case studies are intended to 'illustrate by example' the ways that Bayesian modelling differs from frequentist modelling and the differing conclusions that one may arrive at using the two methods. The intended audience is applied psychological researchers who have been trained in the traditional frequentist framework, who are familiar with mixed-effects models and who are curious about how statistical results might look in a Bayesian context. Along with our case studies, we provide general opinions and guidance on the use of Bayesian methods in applied psychological research.

Pharmacogenetic Analysis of Voriconazole Treatment in Children.

Voriconazole is among the first-line antifungal drugs to treat invasive fungal infections in children and known for its pronounced inter- and intraindividual pharmacokinetic variability. Polymorphisms in genes involved in the metabolism and transport of voriconazole are thought to influence serum concentrations and eventually the therapeutic outcome. To investigate the impact of these genetic variants and other covariates on voriconazole trough concentrations, we performed a retrospective data analysis, where we used medication data from 36 children suffering from invasive fungal infections treated with voriconazole. Data were extracted from clinical information systems with the new infrastructure SwissPKcdw, and linear mixed effects modelling was performed using R. Samples from 23 children were available for DNA extraction, from which 12 selected polymorphism were genotyped by real-time PCR. 192 (49.1%) of 391 trough serum concentrations measured were outside the recommended range. Voriconazole trough concentrations were influenced by polymorphisms within the metabolizing enzymes CYP2C19 and CYP3A4, and within the drug transporters ABCC2 and ABCG2, as well as by the co-medications ciprofloxacin, levetiracetam, and propranolol. In order to prescribe an optimal drug dosage, pre-emptive pharmacogenetic testing and careful consideration of co-medications in addition to therapeutic drug monitoring might improve voriconazole treatment outcome of children with invasive fungal infections.

An integrative pharmacokinetic-cardiovascular physiology modelling approach based on in vivo dog studies including five reference compounds.

Cardiovascular (CV) effects represent a major safety issue during drug development. Typically, this risk is mitigated by preclinical in vivo CV studies, based on which measured CV readouts are analyzed independently. Here, we apply a regression approach to simultaneously integrate CV readouts, i.e., heart rate (HR), mean arterial pressure (MAP) and QT from five dog telemetry studies. These CV studies comprise data on verapamil, captopril, dofetilide, pimobendan, and formoterol, and are combined with the respective dog pharmacokinetic (PK) profiles. A published PK/CV model structure for rats is extended by a semi-mechanistic parameterization of the interaction between HR and QT specific to dogs. This semi-mechanistic modelling approach allows differentiation between compound-independent system-specific parameters (e.g., HR baseline) and compound-specific parameters (e.g., EC50). Compared to previous results in rodents, estimated parameters for dogs indicate stronger dependency of stroke volume on HR, slower HR response, faster QT response and steeper concentration-response relationships. In addition, we illustrate how to practically apply the PK/CV model to derive concentration-response relationships for CV readouts. This approach allows a more detailed quantitative evaluation based on the maximum effect on CV effects (Emax), the EC50, and the steepness of this relation (Hill coefficient) especially for HR-independent effects on QT interval duration (QTc) while taking the systemic feedback into account. This approach also allows to derive plasma concentrations associated with relevant CV effects ("threshold concentration"; CTHRESH). The presented modelling analysis highlights the potential of an integrative evaluation of CV data and provides a framework for obtaining quantitative insights from safety pharmacology evaluations.

Associations between perceived quantitative work demands at different organisational levels and pain and sickness absence in eldercare workers: a multi-level longitudinal analysis.

PURPOSE: Eldercare work is characterised by high quantitative work demands and high occurrence of musculoskeletal pain and sickness absence. Our aim was to investigate the association between quantitative demands aggregated at the different organizational levels of eldercare and low back pain (LBP) and sickness absence due to pain among workers. METHODS: This study was conducted in 527 eldercare workers from 105 wards across 20 nursing homes in Denmark. We collected workers' perceived quantitative demands at baseline and workers' LBP and sickness absence repeatedly over the following year. We aggregated worker-level quantitative demands to the ward and nursing home-levels, and used mixed-effects regression models to investigate the associations between quantitative demands at different organizational levels and LBP and sickness absence over 1 year. RESULTS: Across all models, increased quantitative demands (0-100 scale) at the worker-level was associated with an increased likelihood (OR 1.02) and intensity of LBP (ß = 0.01). We did not identify any associations between quantitative demands at the ward-level and either of our outcomes. Across all models, increased quantitative demands at the nursing home-level was associated with increased days with sickness absence due to pain (ß = 0.03 to 0.06). CONCLUSION: In eldercare, workers' perceived quantitative demands are associated with the presence and intensity of LBP. Further, quantitative demands across the overall nursing home-level are associated with sickness absence due to pain among eldercare workers. These results are of relevance to developing organisational interventions targeting quantitative demands to reduce sickness absence in eldercare.

Insights in the maturational processes influencing hydrocortisone pharmacokinetics in congenital adrenal hyperplasia patients using a middle-out approach.

Introduction: Hydrocortisone is the standard of care in cortisol replacement therapy for congenital adrenal hyperplasia patients. Challenges in mimicking cortisol circadian rhythm and dosing individualization can be overcome by the support of mathematical modelling. Previously, a non-linear mixed-effects (NLME) model was developed based on clinical hydrocortisone pharmacokinetic (PK) pediatric and adult data. Additionally, a physiologically-based pharmacokinetic (PBPK) model was developed for adults and a pediatric model was obtained using maturation functions for relevant processes. In this work, a middle-out approach was applied. The aim was to investigate whether PBPK-derived maturation functions could provide a better description of hydrocortisone PK inter-individual variability when implemented in the NLME framework, with the goal of providing better individual predictions towards precision dosing at the patient level. Methods: Hydrocortisone PK data from 24 adrenal insufficiency pediatric patients and 30 adult healthy volunteers were used for NLME model development, while the PBPK model and maturation functions of clearance and cortisol binding globulin (CBG) were developed based on previous studies published in the literature. Results: Clearance (CL) estimates from both approaches were similar for children older than 1 year (CL/F increasing from around 150 L/h to 500 L/h), while CBG concentrations differed across the whole age range (CBGNLME stable around 0.5 µM vs. steady increase from 0.35 to 0.8 µM for CBG PBPK). PBPK-derived maturation functions were subsequently included in the NLME model. After inclusion of the maturation functions, none, a part of, or all parameters were re-estimated. However, the inclusion of CL and/or CBG maturation functions in the NLME model did not result in improved model performance for the CL maturation function (ΔOFV > -15.36) and the re-estimation of parameters using the CBG maturation function most often led to unstable models or individual CL prediction bias. Discussion: Three explanations for the observed discrepancies could be postulated, i) non-considered maturation of processes such as absorption or first-pass effect, ii) lack of patients between 1 and 12 months, iii) lack of correction of PBPK CL maturation functions derived from urinary concentration ratio data for the renal function relative to adults. These should be investigated in the future to determine how NLME and PBPK methods can work towards deriving insights into pediatric hydrocortisone PK.

In vivo pharmacokinetic evaluation of carprofen delivery from intra-articular nanoparticles in rabbits: A population modelling approach.

Osteoarthritis is treated with COX or fosfolipase A2 inhibitors such as carprofen, a propionic acid NSAID. The enhancement of its action over the articular cartilage is mandatory to facilitate its therapeutic application. Drug uptake into the cartilage requires high synovial fluid concentrations, anticipating its rapid distribution towards bloodstream. Thus, intraarticular administration improves local targeting of the drug, lining with the site of action. A pharmacokinetic study in rabbits has been performed to evaluate carprofen nanoparticles after intraarticular administration. Pharmacokinetic analysis of plasma profiles through a modelling approach, has demonstrated the rapid distribution of drug outside of synovial chamber but mainly remaining in plasma. The data modelling has demonstrated the existence of two release-absorption processes when the nanoparticles are administered in the synovial space. Additionally, results are predictive of the PK profile of some other species such as cat, dogs or humans.

Use of population PK/PD approach to model the thrombin generation assay: assessment in haemophilia A plasma samples spiked by a TFPI antibody.

The thrombin generation (TG) assay is a well-established tool to capture the clotting potential of any healthy or haemophiliac subject. It measures ex vivo the kinetics of thrombin activation throughout the coagulation. Clinical studies allowed to create two databases gathering the coagulation factor levels and the thrombin generation profile of 40 healthy and 40 haemophiliac A (HA) subjects. Besides, portions of all HA samples were spiked with increasing levels of a TFPI antibody (considered as a possible therapeutic target) and corresponding TG profiles were determined. The non-linear mixed-effect (NLME) modelling aims at describing and explaining the experimentally observed important variability of the TG curves between subjects and the individual effects of spiking with a TFPI antibody. The models consist of an empirical description of the TG kinetics, accounting for an additive residual error and between-subject variability on its parameters. Factor VIII and TFPI were found to significantly explain and reduce the variability of the TG of haemophilia A samples. Besides, the model is shown to correctly reproduce the variability in the response to the ex vivo spiking with the TFPI antibody, by combining the empirical description of TG to a simple Hill equation that accounts for the binding between TFPI and different doses of its antibody. Such models can be useful for clinical practice, with the analysis and comparison of the distributions of TG profiles in healthy and haemophilia populations; and also for research, with the analysis of the effect of TFPI and its neutralization on individual TG profiles.

Which Analysis Approach Is Adequate to Leverage Clinical Microdialysis Data? A Quantitative Comparison to Investigate Exposure and Reponse Exemplified by Levofloxacin.

PURPOSE: Systematic comparison of analysis methods of clinical microdialysis data for impact on target-site drug exposure and response. METHODS: 39 individuals received a 500 mg levofloxacin short-term infusion followed by 24-h dense sampling in plasma and microdialysate collection in interstitial space fluid (ISF). ISF concentrations were leveraged using non-compartmental (NCA) and compartmental analysis (CA) via (ii) relative recovery correction at midpoint of the collection interval (midpoint-NCA, midpoint-CA) and (ii) dialysate-based integrals of time (integral-CA). Exposure and adequacy of community-acquired pneumonia (CAP) therapy via pharmacokinetic/pharmacodynamic target-attainment (PTA) analysis were compared between approaches. RESULTS: Individual AUCISF estimates strongly varied for midpoint-NCA and midpoint-CA (≥52.3%CV) versus integral-CA (≤32.9%CV) owing to separation of variability in PK parameters (midpoint-CA = 46.5%-143%CVPK, integral-CA = 26.4%-72.6%CVPK) from recovery-related variability only in integral-CA (41.0%-50.3%CVrecovery). This also led to increased variability of AUCplasma for midpoint-CA (56.0%CV) versus midpoint-NCA and integral-CA (≤33.0%CV), and inaccuracy of predictive model performance of midpoint-CA in plasma (visual predictive check). PTA analysis translated into 33% of evaluated patient cases being at risk of incorrectly rejecting recommended dosing regimens at CAP-related epidemiological cut-off values. CONCLUSIONS: Integral-CA proved most appropriate to characterise clinical pharmacokinetics- and microdialysis-related variability. Employing this knowledge will improve the understanding of drug target-site PK for therapeutic decision-making.

Dyslexia treatment studies: A systematic review and suggestions on testing treatment efficacy with small effects and small samples.

Poor response to treatment is a defining characteristic of reading disorder. In the present systematic review and meta-analysis, we found that the overall average effect size for treatment efficacy was modest, with a mean standardized difference of 0.38. Small true effects, combined with the difficulty to recruit large samples, seriously challenge researchers planning to test treatment efficacy in dyslexia and potentially in other learning disorders. Nonetheless, most published studies claim effectiveness, generally based on liberal use of multiple testing. This inflates the risk that most statistically significant results are associated with overestimated effect sizes. To enhance power, we propose the strategic use of repeated measurements with mixed-effects modelling. This novel approach would enable us to estimate both individual parameters and population-level effects more reliably. We suggest assessing a reading outcome not once, but three times, at pre-treatment and three times at post-treatment. Such design would require only modest additional efforts compared to current practices. Based on this, we performed ad hoc a priori design analyses via simulation studies. Results showed that using the novel design may allow one to reach adequate power even with low sample sizes of 30-40 participants (i.e., 15-20 participants per group) for a typical effect size of d = 0.38. Nonetheless, more conservative assumptions are warranted for various reasons, including a high risk of publication bias in the extant literature. Our considerations can be extended to intervention studies of other types of neurodevelopmental disorders.