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.

The association of depression and anxiety with treatment outcomes in patients with rheumatoid arthritis - a pooled analysis of five randomised controlled trials.

Background: Rheumatoid arthritis (RA) is an inflammatory autoimmune condition associated with an increased risk of developing depression and anxiety. Depression and anxiety are associated with worse outcomes in RA, but the magnitude of the effect of each condition on RA outcomes is unclear. It is also unknown how pharmacological treatment of depression affects RA outcomes. Objective: The primary aim of this study was to investigate the association of comorbid depression and anxiety with remission in patients with RA. Secondary aims were to determine the association between comorbid depression and anxiety on patient-reported outcomes and the relationship between concomitant use of antidepressants and remission in patients with depression. Design: Data from patients with moderate to severe RA were pooled from five randomised controlled trials investigating tocilizumab and conventional synthetic disease-modifying agents. Methods: Remission was defined as a clinical disease activity index (CDAI) of ⩽2.8 and simple disease activity index (SDAI) of ⩽3.3. The association between the time to reach remission and depression and anxiety was analysed using Cox proportional hazard analysis. Results: Individual patient data were available from 5502 subjects, of whom 511 had depression, 236 had anxiety and 387 were using antidepressants. Depression was significantly associated with reduced remission [adjusted HR (95% CI): 0.62 (0.48-0.80), p < 0.001 and adjusted HR (95% CI): 0.59 (0.44-0.79), p < 0.001] using CDAI and SDAI, respectively. Depression was associated with a lower likelihood of achieving more subjective outcomes (⩽1 physician global assessment, ⩽1 patient global assessment) and ⩽1 28-swollen joint count, but not ⩽1 28-tender joint count or C-reactive protein measurement. Treatment with antidepressants did not improve outcomes for patients with depression. Anxiety was not significantly associated with RA remission. Conclusion: Comorbid depression, but not anxiety, was associated with less frequent remission. Concomitant antidepressant use was not associated with improvements in RA outcomes in patients with depression.

Population Pharmacokinetics and Pharmacodynamics of the Therapeutic and Adverse Effects of Ketamine in Patients With Treatment-Refractory Depression.

We aimed to develop population pharmacokinetic/pharmacodynamic (PK/PD) models that can effectively describe ketamine and norketamine PK/PD relationships for Montgomery-Åsberg Depression Rating Scale (MADRS) scores, blood pressure (BP), and heart rate (HR) following i.v., s.c., and i.m. ketamine administration in patients with treatment-refractory depression. Ketamine PK/PD data were collected from 21 treatment-refractory depressed participants who received ketamine (dose titration 0.1-0.5 mg/kg as single doses) by i.v., s.c., or i.m. administration. Model development used nonlinear mixed effect modeling. Ketamine and norketamine PK were best described using two-compartment models with first-order absorption after s.c. and i.m. administration. Estimated ketamine bioavailability after i.m. and s.c. was ~ 64% with indistinguishable first-order absorption rate constants. Allometric scaling of body weight on all clearance and volumes of distribution improved the model fit. The delay in the concentration-response relationship for MADRS scores was best described using a turnover model (turnover time ~ 42 hours), whereas for the BP and HR rates this was an immediate effect model. For all PD effects, ketamine alone was superior to models with norketamine concentration linked to an effect. No covariates were identified for PD effects. The estimated half-maximal effective concentration from the MADRS score, BP, and HR were 0.44, 468, and 7,580 ng/mL, respectively. The integrated population models were able to effectively describe the PK/PD relationships for MADRS scores, BP, and HR after i.v., s.c., and i.m. ketamine administration. These findings allow for a deeper understanding of the complex relationships between route of ketamine administration and clinical response and safety.

Effect of Roux-en-Y gastric bypass on the pharmacokinetic-pharmacodynamic relationships of liquid and controlled-release formulations of oxycodone.

The physiological changes following Roux-en-Y gastric bypass (RYGB) surgery may impact drug release from mechanistically different controlled-release tablets, making generic substitution inappropriate. This study aimed to characterise the pharmacokinetic-pharmacodynamic relationships of oxycodone from a lipid-based and water-swellable controlled-release tablet in RYGB patients. Twenty RYGB patients received 10-mg oral solution oxycodone or 20-mg controlled-release (water-swellable or lipid-based) oxycodone in a three-way, randomised, semiblinded and cross-over study. Blood sampling and pupillary recordings were conducted over a 24-h period. A previously established pharmacokinetic-pharmacodynamic model of these three formulations in healthy volunteers was used in the analysis as a reference model. No differences in absorption kinetics were seen between controlled-release formulations in patients. However, the absorption lag time was 11.5 min in patients vs 14 min in healthy volunteers for controlled-release tablets (P < 0.001). Furthermore, oral bioavailability was 14.4% higher in patients compared to healthy volunteers regardless of formulation type (P < 0.001). Oxycodone pharmacodynamics were not significantly affected by formulation or patient status. However, baseline pupil diameter was inversely correlated with age (P < 0.001) and plasma concentrations of oxycodone at half-maximum effect were 31% lower in males compared to females (P < 0.05). Generic substitution of monophasic lipid-based and water-swellable controlled-release oxycodone tablets may be considered safe in RYGB patients.

Concomitant beta-blocker use is associated with a reduced rate of remission in patients with rheumatoid arthritis treated with disease-modifying anti-rheumatic drugs: a post hoc multicohort analysis.

BACKGROUND: Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease associated with increased risk of cardiovascular disease (CVD). Treatment for CVD may involve pharmacological agents that antagonise beta adrenergic receptors. These receptors may play an important role in immunology, and the effects of beta-blockers (BB) in RA is unknown. The aim of this study was to investigate the association between BB use and remission in patients with RA initiating tocilizumab +/- conventional synthetic (cs-) DMARD therapy. METHODS: Data was pooled from five randomised trials investigating tocilizumab and/or csDMARD treatment in RA (primarily methotrexate). The association between BB use and remission according to the Simplified Disease Activity Index (SDAI) and Clinical Disease Activity Index (CDAI) was assessed by Cox proportional hazard analysis. Sensitivity analysis in patients with pre-existing CVD and an exploratory analysis of the impact of other CVD drugs were conducted. RESULTS: Data were available from 5502 participants, 594 (10.8%) of whom were using systemic BB. BB use was associated with less frequent SDAI remission in the total [adjusted hazard ratio (HR) 0.70, 95% confidence interval (CI) 0.57-0.87, p = 0.001] and CVD cohort [adjusted HR 0.72 (0.57-0.90, p = 0.005)]. The association was consistent between trials (interaction p = 0.44) and treatment arms (interaction p = 0.06). No significant association between remission and ß1-receptor selectivity was identified (p = 0.16), and the association was independent from other cardiovascular drug use. Similar associations between BB use and CDAI remission were observed. CONCLUSION: In a large, pooled cohort of RA patients initiating csDMARDs and/or tocilizumab, BB use was independently associated with less frequent remission.

Association between obesity and remission in rheumatoid arthritis patients treated with disease-modifying anti-rheumatic drugs.

The aim of this study was to investigate the association between body-mass index (BMI) and remission in RA patients receiving conventional synthetic (cs-) or the biological Disease-Modifying Antirheumatic Drug (DMARD), tocilizumab. Individual participant data (IPD) were pooled from five trials investigating tocilizumab and/or csDMARDs therapy (primarily methotrexate) for RA. Time to first remission was recorded according to the Simplified Disease Activity Index (SDAI) and Clinical Disease Activity Index (CDAI). BMI was classified according to WHO definitions. Associations between baseline BMI and remission were assessed by Cox-proportional hazard analysis. IPD were available from 5428 patients treated with tocilizumab ± csDMARDs (n = 4098) or csDMARDs alone (n = 1330). Of these, 1839 (33.9%) had normal BMI, 1780 (32.8%) overweight, 1652 (30.4%) obese and 157 (2.9%) were underweight. Obesity, compared to normal BMI, was associated with less frequent remission using SDAI (adjusted HR 0.80 [95% CI 0.70-0.92]) and CDAI (adjusted HR 0.77 [0.68-0.87]). As continuous variable, increased BMI was associated with less frequent SDAI (P = 0.001) and CDAI (P = 0.001) defined remission. No heterogeneity in identified associations was observed between studies (P = 0.08) or treatments (P = 0.22). Obesity was negatively associated with RA disease remission regardless of RA therapy, suggesting that baseline BMI should be considered as a stratification factor in future RA trials.

Demonstrating Contribution of Components of Fixed-Dose Drug Combinations Through Longitudinal Exposure-Response Analysis.

Exposure-response (ER) modeling for fixed-dose combinations (FDC) has previously been found to have an inflated false positive rate (FP), i.e., observing a significant effect of FDC components when no true effect exists. Longitudinal exposure-response (LER) analysis utilizes the time course of the data and is valid for several clinical endpoints for FDCs. The aim of the study was to investigate if LER is applicable for the validation of FDCs by demonstrating the contribution of each component to the overall effect without inflation of FP rates. FP and FN rates associated with ER and LER analysis were investigated using stochastic simulation and estimation. Four hundred thirty-two scenarios with varying numbers of patients, duration, sampling frequency, dose distribution, design, and drug activity were analyzed using a range of linear, log-linear, and non-linear models to asses FP and FN rates. Lastly, the impact of the clinical trial parameters was investigated. LER analyses provided well-controlled FP rates of the expected 5% or less; however, in low information clinical trials consisting of 30 patients, 4 samples, and 20 days, LER analyses lead to inflated FN rates. Parameter investigation showed that when the clinical trial includes sufficient patients, duration, samples, and an appropriate trial design, the FN rates are in general below the expected 5% for LER analysis. Based on the results, LER analysis can be used for the validation of FDCs and fixed ratio drug combinations. The method constitutes a new avenue for providing evidence that demonstrates the contribution of each component to the overall clinical effect.

Population pharmacokinetic-pharmacodynamic modelling of liquid and controlled-release formulations of oxycodone in healthy volunteers.

Oral controlled-release formulations are playing an ever-increasing role in opioid therapy; however, little is known about their influence on the relationship between pharmacokinetics and pharmacodynamics. The study aim was to characterize the pharmacokinetic-pharmacodynamics of two controlled-release tablet formulations and a liquid formulation of oxycodone in healthy, opioid-naïve volunteers, which can serve as a reference for future patient studies. A semi-double-blinded, three-way crossover study was conducted, with fifteen healthy volunteers receiving two differently designed 20 mg monophasic controlled-release oxycodone tablets and 10 mg oral solution oxycodone in a randomized order. Venous plasma concentrations and pupil diameter were determined pre-dose and 0.25, 0.5, 0.75, 1, 1.5, 2, 2.33, 2.66, 3, 3.33, 3.66, 4, 5, 6, 8, 12 and 24 hour post-dose. Oxycodone pharmacokinetics was best described by a two-compartment model with first-order absorption. The controlled-release formulations had an absorption lag of 0.23 hour and a slower absorption rate constant (kaCR  = 0.19 hour-1 ) compared to the oral solution (kaSOL  = 0.94 hour-1 ). Effects on pupil diameter were delayed relative to plasma (14 minutes half-life) for all formulations and were best described by a proportional Emax model. The plasma concentration of oxycodone at half-maximum effect was lower in males (31.1 µg/L) compared to females (52.8 µg/L; P < .001). The absorption profile of controlled-release oxycodone formulations provided a prolonged onset and offset of action compared to oral solution oxycodone. The controlled-release formulations showed no differences in pharmacokinetic and pharmacodynamic parameters suggesting that both may be used interchangeably in human beings with normal gastrointestinal function.

Development of a physiologically based pharmacokinetic model for intravenous lenalidomide in mice.

PURPOSE: Lenalidomide is used widely in B-cell malignancies for its immunomodulatory activity. It is primarily eliminated via the kidneys, with a significant proportion of renal elimination attributed to active processes. Lenalidomide is a weak substrate of P-glycoprotein (P-gp), though it is unclear whether P-gp is solely responsible for lenalidomide transport. This study aimed to determine whether the current knowledge of lenalidomide was sufficient to describe the pharmacokinetics of lenalidomide in multiple tissues. METHODS: A physiologically based pharmacokinetic model was developed using the Open Systems Pharmacology Suite to explore the pharmacokinetics of lenalidomide in a variety of tissues. Data were available for mice dosed intravenously at 0.5, 1.5, 5, and 10 mg/kg, with concentrations measured in plasma, brain, heart, kidney, liver, lung, muscle, and spleen. P-gp expression and activity were sourced from the literature. RESULTS: The model predictions in plasma, liver, and lung were representative of the observed data (median prediction error 13%, - 10%, and 30%, respectively, with 90% confidence intervals including zero), while other tissue predictions showed sufficient similarity to the observed data. Contrary to the data, model predictions for the brain showed no drug reaching brain tissue when P-gp was expressed at the blood-brain barrier. The data were better described by basolateral transporters at the intracellular wall. Local sensitivity analysis showed that transporter activity was the most sensitive parameter in these models for exposure. CONCLUSION: As P-gp transport at the blood-brain barrier did not explain the observed brain concentrations alone, there may be other transporters involved in lenalidomide disposition.

Optimising time samples for determining area under the curve of pharmacokinetic data using non-compartmental analysis.

OBJECTIVES: The selection of sample times for a pharmacokinetic study is important when trapezoidal integration (e.g. non-compartmental analysis) is used to determine the area under the concentration-time curve (AUC). The aim of this study was to develop an algorithm that determines optimal times that provide the most accurate AUC by minimising trapezoidal integration error. METHODS: The algorithm required initial single individual or mean pooled concentration data but did not specifically require a prior pharmacokinetic model. Optimal sample intervals were determined by minimising trapezoidal error using a genetic algorithm followed by a quasi-Newton method. The method was evaluated against simulated and clinical datasets to determine the method's ability to estimate the AUC. KEY FINDINGS: The sample times produced by the algorithm were able to accurately estimate the AUC of pharmacokinetic profiles, with the relative AUC having 90% confidence intervals of 0.919-1.05 for profiles with two-compartment kinetics. When comparing the algorithm with rich sampling (e.g. phase I trial), the algorithm provided equivalent or superior sample times with fewer observations. CONCLUSIONS: The creation of the algorithm and its companion web application allows users with limited pharmacometric or programming training can obtain optimal sampling times for pharmacokinetic studies.

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.

Mechanistic Assessment of the Effect of Omeprazole on the In Vivo Pharmacokinetics of Itraconazole in Healthy Volunteers.

BACKGROUND AND OBJECTIVE: SUBA-itraconazole and Sporanox are two oral formulations of itraconazole. Drug-drug interactions with omeprazole have been previously reported; however, mechanistic understanding of the pharmacological and physiological interactions of omeprazole with orally administered itraconazole within a population modeling paradigm is lacking. The objective of this analysis was to mechanistically describe and quantify the effect of omeprazole on the pharmacokinetics of itraconazole and its major metabolite, hydroxyitraconazole from the SUBA itraconazole and Sporanox formulations. METHODS: An in vitro-in vivo (IVIV) pharmacokinetic model of itraconazole and hydroxyitraconazole was developed including data from an omeprazole interaction study with SUBA itraconazole. Meta-models of gastric pH for healthy subjects and subjects receiving omeprazole were integrated into the IVIV model to capture omeprazole-mediated gastric pH changes on itraconazole dissolution and absorption. RESULTS: Omeprazole influenced the kinetics of itraconazole through altering the dissolution and absorption due to the pH-dependent solubility of itraconazole, inhibition of efflux transporters, and inhibiting the metabolism of itraconazole and hydroxyitraconazole. The model-predicted population effects of omeprazole on itraconazole from SUBA-itraconazole were to increase the area under the concentration-time curve (AUC0-24) and maximum concentration (Cmax) by 35 and 31%, respectively, and to decrease AUC0-24 and Cmax from Sporanox by 68 and 76%, respectively. CONCLUSION: Unlike SUBA itraconazole, which requires basic pH for itraconazole release, the omeprazole-induced pH-mediated reduction in Sporanox dissolution overrides any increased exposure from the drug-drug interaction at hepatic metabolizing enzymes or efflux transporters. The model presented here is the most complete quantitative description of the pharmacokinetics of itraconazole and hydroxyitraconazole currently available.

Molecular Modeling Approaches for the Prediction of Selected Pharmacokinetic Properties.

Poor profiles of potential drug candidates, including pharmacokinetic properties, have been acknowledged as a significant hindrance to the development of modern therapeutics. Contemporary drug discovery and development would be incomplete without the aid of molecular modeling (in-silico) techniques, allowing the prediction of pharmacokinetic properties such as clearance, unbound fraction, volume of distribution and bioavailability. As with all models, in-silico approaches are subject to their interpretability, a trait that must be balanced with accuracy when considering the development of new methods. The best models will always require reliable data to inform them, presenting significant challenges, particularly when appropriate in-vitro or in-vivo data may be difficult or time-consuming to obtain. This article seeks to review some of the key in-silico techniques used to predict key pharmacokinetic properties and give commentary on the current and future directions of the field.

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.

Pharmacokinetics of caspofungin acetate to guide optimal dosing in cats.

Cats are the most common mammal to develop invasive fungal rhinosinusitis caused by cryptic species in Aspergillus section Fumigati that are resistant to azoles but susceptible to caspofungin. In this study nonlinear mixed-effects pharmacokinetic modeling and simulation was used to investigate caspofungin pharmacokinetics and explore dosing regimens in cats using caspofungin minimum effective concentrations (MECs). Plasma concentrations in healthy cats were determined using HPLC-MS/MS after administration of a single and seven consecutive daily intravenous doses of 1 mg/kg caspofungin. In the final pharmacokinetic model an optimum maximum concentration (Cmax): MEC ratio of 10-20 was used to guide caspofungin efficacy. Simulations were performed for dosing regimens (doses 0.25-2 mg/kg and 6-72 h dosing intervals) with and without inclusion of a loading dose. Using a 1 mg/kg dose Cmax first dose was 14.8 µg/mL, Cmax at steady state was 19.8 µg/mL, Cmin was 5 µg/mL and Cmax: MEC was >20 in 42.6% of cats after multiple doses. An optimal Cmax: MEC ratio was achieved in caspofungin simulations using 0.75 mg/kg q 24 h or 1 mg/kg q 72h. However, at 1 mg/kg q 72h, Cmin was < MEC (<1 µg/mL) in over 95% of the population. Using a loading dose of 1 mg/kg and a daily dose of 0.75 mg/kg thereafter, the Cmax: MEC was optimal and Cmin was > 2.5 µg/mL for 98% of the population. Based on the modeling data this dosing regimen is likely to achieve target therapeutic concentrations, meet the proposed Cmax: MEC window and provide consistent exposure between doses.

Infliximab Maintenance Dosing in Inflammatory Bowel Disease: an Example for In Silico Assessment of Adaptive Dosing Strategies.

Infliximab is an anti-tumour necrosis factor alpha monoclonal antibody used to treat inflammatory diseases. Many patients fail during induction and others respond initially but relapse during maintenance therapy. Although anti-drug antibodies (ADA) are associated with some clinical failures, there is evidence that some failures may be due to subtherapeutic exposure. Adapting doses based on clinical outcomes and trough concentrations can improve response and reduce the proportion that develop ADA, but identification of appropriate doses in the presence of time-varying patient factors is complicated. Several adaptive dosing strategies (label recommendations versus therapeutic drug monitoring with an established stepwise algorithm or proportional dose adjustments or Bayesian population pharmacokinetic model-based dosing) were simulated on a virtual population (constructed with time-varying covariates and random effects on individual pharmacokinetic parameters) using R to assess their relative performance. Strategies were evaluated on their ability to maintain trough infliximab concentrations above an established target, 3 mg/L, during maintenance phase. Model-based dosing was superior in maintaining target trough concentrations, showing individuals in maintenance achieving concentrations above the target faster and a lower proportion of individuals who developed ADA. Model-based dosing results were consistent across a range of baseline covariate groups. This in silico assessment of adaptive dosing strategies demonstrated that, when challenged with dynamic covariate and random effect changes occurring in individual pharmacokinetic parameters, model-based approaches were superior to other strategies. Model-based dosing has not been tested clinically; however, the potential benefits of model-based dosing for infliximab suggest that it should be investigated to reduce subtherapeutic exposure.

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.

Rosiglitazone Metabolism in Human Liver Microsomes Using a Substrate Depletion Method.

BACKGROUND: Elimination of rosiglitazone in humans is via hepatic metabolism. The existing studies suggest that CYP2C8 is the major enzyme responsible, with a minor contribution from CYP2C9; however, other studies suggest the involvement of additional cytochrome P450 enzymes and metabolic pathways. Thus a full picture of rosiglitazone metabolism is unclear. OBJECTIVE: This study aimed to improve the current understanding of potential drug-drug interactions and implications for therapy by evaluating the kinetics of rosiglitazone metabolism and examining the impact of specific inhibitors on its metabolism using the substrate depletion method. METHODS: In vitro oxidative metabolism of rosiglitazone in human liver microsomes obtained from five donors was determined over a 0.5-500 µM substrate range including the contribution of CYP2C8, CYP2C9, CYP3A4, CYP2E1, and CYP2D6. RESULTS: The maximum reaction velocity was 1.64 ± 0.98 nmol·mg-1·min-1. The CYP2C8 (69 ± 20%), CYP2C9 (42 ± 10%), CYP3A4 (52 ± 23%), and CEP2E1 (41 ± 13%) inhibitors all significantly inhibited rosiglitazone metabolism. CONCLUSION: The results suggest that other cytochrome P450 enzymes, including CYP2C9, CYP3A4, and CEP2E1, in addition to CYP28, also play an important role in the metabolism of rosiglitazone. This example demonstrates that understanding the complete metabolism of a drug is important when evaluating the potential for drug-drug interactions and will assist to improve the current therapeutic strategies.

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.