Impact of early vs. delayed initiation of dutasteride/tamsulosin combination therapy on the risk of acute urinary retention or BPH-related surgery in LUTS/BPH patients with moderate-to-severe symptoms at risk of disease progression.

PURPOSE: To evaluate the effect of delayed start of combination therapy (CT) with dutasteride 0.5 mg and tamsulosin 0.4 mg on the risk of acute urinary retention or benign prostatic hyperplasia (BPH)-related surgery (AUR/S) in patients with moderate-to-severe lower urinary tract symptoms (LUTS) at risk of disease progression. METHODS: Using a time-to-event model based on pooled data from 10,238 patients from Phase III/IV dutasteride trials, clinical trial simulations (CTS) were performed to assess the risk of AUR/S up to 48 months in moderate-to-severe LUTS/BPH patients following immediate and delayed start of CT for those not responding to tamsulosin monotherapy. Simulation scenarios (1300 subjects/arm) were investigated, including immediate start (reference) and alternative delayed start (six scenarios 1-24 months). AUR/S incidence was described by Kaplan-Meier survival curves and analysed using log-rank test. The cumulative incidence of events as well as the relative and attributable risks were summarised stratified by treatment. RESULTS: Survival curves for patients starting CT at month 1 and 3 did not differ from those who initiated CT immediately. By contrast, significant differences (p < 0.001) were observed when switch to CT occurs ≥ 6 months from the initial treatment. At month 48, AUR/S incidence was 4.6% vs 9.5%, 11.0% and 11.3% in patients receiving immediate CT vs. switchers after 6, 12 and 24 months, respectively. CONCLUSIONS: Start of CT before month 6 appears to significantly reduce the risk of AUR/S compared with delayed start by ≥ 6 months. This has implications for the treatment algorithm for men with LUTS/BPH at risk of disease progression.

Extrapolation and dosing recommendations for raxibacumab in children from birth to age <18 years.

AIMS: The US Food and Drug Administration's Animal Rule allows for the approval of drugs when human efficacy studies are not ethical. While the therapeutic doses of raxibacumab, a monoclonal antibody for the prophylaxis and treatment of inhalational anthrax, have been based on pharmacokinetic data from adult subjects, its disposition in children has not been investigated in clinical trials. Here we evaluate the effect of demographic covariates and maturation processes on the pharmacokinetics of raxibacumab and explore opportunities for the optimisation of paediatric doses. METHODS: A population pharmacokinetic model was used as basis for the extrapolation of raxibacumab disposition from adults to children. Different extrapolation scenarios, including weight-banded dosing regimens, were considered to assess the effect of growth and maturation on the pharmacokinetic parameters of interest. Area under the concentration-time curve, maximum plasma concentration and the time of serum raxibacumab concentrations greater than or equimolar to the highest serum protective antigen concentrations observed for at least 28 days in any monkey challenged with Bacillus anthracis that died were derived and compared with the currently approved US doses. RESULTS: Based on practical considerations, a weight-banded dosing regimen consisting of 4 dose levels (75 mg/kg for individuals ≤1.5 kg, 55 mg/kg for individuals <10 kg, 45 mg/kg for individuals <50 kg, 40 mg/kg for all individuals >50 kg) was required to optimise target exposure across the paediatric population. CONCLUSIONS: Age-related maturation processes may affect raxibacumab clearance in very young patients. The proposed dosing regimens take into account effects of body weight and maturation processes on the elimination of raxibacumab.

First-Time-in-Human Study and Prediction of Early Bactericidal Activity for GSK3036656, a Potent Leucyl-tRNA Synthetase Inhibitor for Tuberculosis Treatment.

This first-time-in-human (FTIH) study evaluated the safety, tolerability, pharmacokinetics, and food effect of single and repeat oral doses of GSK3036656, a leucyl-tRNA synthetase inhibitor. In part A, GSK3036656 single doses of 5 mg (fed and fasted), 15 mg, and 25 mg and placebo were administered. In part B, repeat doses of 5 and 15 mg and placebo were administered for 14 days once daily. GSK3036656 showed dose-proportional increase following single-dose administration and after dosing for 14 days. The maximum concentration of drug in serum (Cmax) and area under the concentration-time curve from 0 h to the end of the dosing period (AUC0-τ) showed accumulation with repeated administration of approximately 2- to 3-fold. Pharmacokinetic parameters were not altered in the presence of food. Unchanged GSK3036656 was the only drug-related component detected in plasma and accounted for approximately 90% of drug-related material in urine. Based on total drug-related material detected in urine, the minimum absorbed doses after single (25 mg) and repeat (15 mg) dosing were 50 and 78%, respectively. Unchanged GSK3036656 represented at least 44% and 71% of the 25- and 15-mg doses, respectively. Clinical trial simulations were performed to guide dose escalation during the FTIH study and to predict the GSK3036656 dose range that produces the highest possible early bactericidal activity (EBA0-14) in the prospective phase II trial, with consideration of the predefined exposure limit. GSK3036656 was well tolerated after single and multiple doses, with no reports of serious adverse events. (This study has been registered at ClinicalTrials.gov under identifier NCT03075410.).

Dose rationale and pharmacokinetics of dexmedetomidine in mechanically ventilated new-borns: impact of design optimisation.

PURPOSE: There is a need for alternative analgosedatives such as dexmedetomidine in neonates. Given the ethical and practical difficulties, protocol design for clinical trials in neonates should be carefully considered before implementation. Our objective was to identify a protocol design suitable for subsequent evaluation of the dosing requirements for dexmedetomidine in mechanically ventilated neonates. METHODS: A published paediatric pharmacokinetic model was used to derive the dosing regimen for dexmedetomidine in a first-in-neonate study. Optimality criteria were applied to optimise the blood sampling schedule. The impact of sampling schedule optimisation on model parameter estimation was assessed by simulation and re-estimation procedures for different simulation scenarios. The optimised schedule was then implemented in a neonatal pilot study. RESULTS: Parameter estimates were more precise and similarly accurate in the optimised scenarios, as compared to empirical sampling (normalised root mean square error: 1673.1% vs. 13,229.4% and relative error: 46.4% vs. 9.1%). Most importantly, protocol deviations from the optimal design still allowed reasonable parameter estimation. Data analysis from the pilot group (n = 6) confirmed the adequacy of the optimised trial protocol. Dexmedetomidine pharmacokinetics in term neonates was scaled using allometry and maturation, but results showed a 20% higher clearance in this population compared to initial estimates obtained by extrapolation from a slightly older paediatric population. Clearance for a typical neonate, with a post-menstrual age (PMA) of 40 weeks and weight 3.4 kg, was 2.92 L/h. Extension of the study with 11 additional subjects showed a further increased clearance in pre-term subjects with lower PMA. CONCLUSIONS: The use of optimal design in conjunction with simulation scenarios improved the accuracy and precision of the estimates of the parameters of interest, taking into account protocol deviations, which are often unavoidable in this event-prone population.

A modeling and simulation-based assessment of the impact of confounding factors on the readout of a sildenafil survival trial in pulmonary arterial hypertension.

Sildenafil (REVATIO®) was approved for the treatment of adult Pulmonary Arterial Hypertension (PAH) in the US and the EU. A pediatric study has been performed and sildenafil was approved in the EU for pediatric PAH. The long-term extension of this study revealed good survival but also an increased mortality with the high dose of sildenafil compared to lower doses. As a consequence, FDA required Pfizer to evaluate REVATIO®'s effect on the risk of death in adults with PAH. Following FDA's rationale a survival model was developed to characterize the exposure-mortality relationship and assess its potential impact on an ongoing survival trial in adults in the context of confounding factors. Clinical trial simulations were performed to assess the design of the survival trial in adults (AFFILIATE, NCT02060487), expected to last approximately 8 years according to both assumptions: absence or presence of an exposure-mortality relationship and to quantify the impact of confounding factors on its readout. Simulations showed that the trial would be robust in most conditions. But its interpretation will depend on the number of confounding factors such as additional treatments attempting to control disease progression.Clinical trial identifier NCT00159913 for STARTS-1, NCT00159874 for STARTS-2.

Impact of Phase 1 study design on estimation of QT interval prolongation risk using exposure-response analysis.

The International Council for Harmonisation (ICH) guidelines have been revised allowing for modeling of concentration-QT (C-QT) data from Phase I dose-escalation studies to be used as primary analysis for QT prolongation risk assessment of new drugs. This work compares three commonly used Phase I dose-escalation study designs regarding their efficiency to accurately identify drug effects on QT interval through C-QT modeling. Parallel group design and 4-period crossover designs with sequential or interleaving cohorts were evaluated. Clinical trial simulations were performed for each design and across different scenarios (e.g. different magnitudes of drug effect, QT variability), assuming a pre-specified linear mixed effect (LME) model for the relationship between drug concentration and change from baseline QT (ΔQT). Analyses suggest no systematic bias in either the predictions of placebo-adjusted ΔQT (ΔΔQT) or the LME model parameter estimates across all evaluated designs. Additionally, false negative rates remained similar and adequately controlled across all evaluated designs. However, compared to the crossover designs, the parallel design had significantly less power to correctly exclude a clinically significant QT effect, especially in the presence of substantial intercept inter-individual variability. In such cases, parallel design is associated with increased uncertainty around ΔΔQT prediction, mainly attributed to the uncertainty around the estimation of the treatment-specific intercept in the model. Throughout all the evaluated scenarios, the crossover design with interleaving cohorts had consistently the best performance characteristics. The results from this investigation will further facilitate informed decision-making during Phase I study design and the interpretation of the associated C-QT modeling output.

The role of concentration-effect relationships in the assessment of QTc interval prolongation.

Population pharmacokinetic and pharmacokinetic-pharmacodynamic (PKPD) modelling has been widely used in clinical research. Yet, its application in the evaluation of cardiovascular safety remains limited, particularly in the evaluation of pro-arrhythmic effects. Here we discuss the advantages of disadvantages of population PKPD modelling and simulation, a paradigm built around the knowledge of the concentration-effect relationship as the basis for decision making in drug development and its utility as a guide to drug safety. A wide-ranging review of the literature was performed on the experimental protocols currently used to characterize the potential for QT interval prolongation, both pre-clinically and clinically. Focus was given to the role of modelling and simulation for design optimization and subsequent analysis and interpretation of the data, discriminating drug from system specific properties. Cardiovascular safety remains one of the major sources of attrition in drug development with stringent regulatory requirements. However, despite the myriad of tests, data are not integrated systematically to ensure accurate translation of the observed drug effects in clinically relevant conditions. The thorough QT study addresses a critical regulatory question but does not necessarily reflect knowledge of the underlying pharmacology and has limitations in its ability to address fundamental clinical questions. It is also prone to issues of multiplicity. Population approaches offer a paradigm for the evaluation of drug safety built around the knowledge of the concentration-effect relationship. It enables quantitative assessment of the probability of QTc interval prolongation in patients, providing better guidance to regulatory labelling and understanding of benefit/risk in specific populations.

Generating Virtual Patients by Multivariate and Discrete Re-Sampling Techniques.

PURPOSE: Clinical Trial Simulations (CTS) are a valuable tool for decision-making during drug development. However, to obtain realistic simulation scenarios, the patients included in the CTS must be representative of the target population. This is particularly important when covariate effects exist that may affect the outcome of a trial. The objective of our investigation was to evaluate and compare CTS results using re-sampling from a population pool and multivariate distributions to simulate patient covariates. METHODS: COPD was selected as paradigm disease for the purposes of our analysis, FEV1 was used as response measure and the effects of a hypothetical intervention were evaluated in different populations in order to assess the predictive performance of the two methods. RESULTS: Our results show that the multivariate distribution method produces realistic covariate correlations, comparable to the real population. Moreover, it allows simulation of patient characteristics beyond the limits of inclusion and exclusion criteria in historical protocols. CONCLUSION: Both methods, discrete resampling and multivariate distribution generate realistic pools of virtual patients. However the use of a multivariate distribution enable more flexible simulation scenarios since it is not necessarily bound to the existing covariate combinations in the available clinical data sets.

A model-based approach for the evaluation of once daily dosing of lamivudine in HIV-infected children.

AIM: Little attention has been paid to the effects of compliance and prescription practice on treatment outcome in HIV-infected children. In this context, an evaluation of the role of covariates on pharmacokinetics is required to establish the impact of differences in dosing regimens. Here we investigate whether a once daily dosing regimen of lamivudine provides comparable exposure to the currently approved paediatric regimen. METHODS: A hypothetical group of 180 patients between 3 months and 12 years old was used to evaluate the impact of body weight on systemic exposure to lamivudine. Simulation scenarios were evaluated using AUC and Cmax as parameters of interest. The analysis was performed using a population pharmacokinetic model previously implemented in nonmem v.6.2. RESULTS: The simulations show that once daily dosing of lamivudine yields comparable exposure to historical values observed in children and adults, both for liquid and solid dosage forms. Simulated steady-state AUC(0-24 h) and Cmax values after once daily doses ranged respectively from 9.9 mg l⁻¹ h and 1.9 mg l⁻¹ for children lighter than 14 kg to 13.75 mg l⁻¹ h and 3.0 mg l⁻¹ for children heavier than 30 kg. These values are comparable or higher than historical values observed after once daily dosing in children and adults. CONCLUSIONS: Our findings illustrate how dosing regimens can be evaluated taking into account the effects of developmental growth on drug disposition. Most importantly, they suggest that the reduction in dosing frequency to once daily leads to comparable lamivudine exposure, as observed after administration of a twice daily dosing regimen.

Efficacy and safety of curcumin in major depressive disorder: a randomized controlled trial.

Curcumin, an active ingredient of Curcuma longa Linn (Zingiberaceae), has shown potential antidepressant-like activity in animal studies. The objectives of this trial were to compare the efficacy and safety of curcumin with fluoxetine in patients with major depressive disorder (MDD). Herein, 60 patients diagnosed with MDD were randomized in a 1:1:1 ratio for six weeks observer-masked treatment with fluoxetine (20 mg) and curcumin (1000 mg) individually or their combination. The primary efficacy variable was response rates according to Hamilton Depression Rating Scale, 17-item version (HAM-D17 ). The secondary efficacy variable was the mean change in HAM-D17 score after six weeks. We observed that curcumin was well tolerated by all the patients. The proportion of responders as measured by the HAM-D17 scale was higher in the combination group (77.8%) than in the fluoxetine (64.7%) and the curcumin (62.5%) groups; however, these data were not statistically significant (P = 0.58). Interestingly, the mean change in HAM-D17 score at the end of six weeks was comparable in all three groups (P = 0.77). This study provides first clinical evidence that curcumin may be used as an effective and safe modality for treatment in patients with MDD without concurrent suicidal ideation or other psychotic disorders. .

Effect of APOE genotype status on targeted clinical trials outcomes and efficiency in dementia and mild cognitive impairment resulting from Alzheimer's disease.

BACKGROUND: The apolipoprotein E (APOE) ε4 genotype has been recommended as a potential inclusion or exclusion criterion in targeted clinical trials for Alzheimer's disease (AD) and mild cognitive impairment (MCI) resulting from AD, and has been implemented in trials of immunotherapeutic agents. METHODS: We tested this recommendation with clinical trial simulations using participants from a meta-database of 19 studies to create trial samples with APOE ε4 proportions ranging from 0% (all noncarriers) to 100% (all carriers). For each percentage of APOE ε4 carriers, we resampled the database randomly for 1000 trials for each trial scenario, planning for 18- or 24-month trials with samples from 50 to 400 patients per treatment or placebo group, up to 40% dropouts, and outcomes on the Alzheimer's Disease Assessment Scale, cognitive subscale (ADAS-cog) with effect sizes from 0.15 to 0.75, and calculated statistical power. RESULTS: Enrichment of clinical trial participants based on APOE ε4 carrier status resulted in minimal increases in power compared with enrolling participants with the APOE ε3 genotype only or enrolling patients without regard to APOE genotype. Increased screening requirements to enhance the sample would offset gains in power. CONCLUSIONS: Although samples enriched for APOE ε4 carriers in AD or MCI clinical trials showed slightly more cognitive impairment and greater decline using the number APOE ε4 alleles as an inclusion criterion most likely would not result in more efficient trials, and trials would take longer because fewer patients would be available. The APOE ε4/εX (where X = 2, 3 or 4) genotype could be useful, however, as an explanatory variable or covariate if warranted by a drug's action.

A Simulation Study of the Effect of Clinical Characteristics and Treatment Choice on Reliever Medication Use, Symptom Control and Exacerbation Risk in Moderate-Severe Asthma.

INTRODUCTION: The relationship between immediate symptom control, reliever medication use and exacerbation risk on treatment response and factors that modify it have not been assessed in an integrated manner. Here we apply simulation scenarios to evaluate the effect of individual baseline characteristics on treatment response in patients with moderate-severe asthma on regular maintenance dosing monotherapy with fluticasone propionate (FP) or combination therapy with fluticasone propionate/salmeterol (FP/SAL) or budesonide/formoterol (BUD/FOR). METHODS: Reduction in reliever medication use (puffs/24 h), change in symptom control scores (ACQ-5), and annualised exacerbation rate over 12 months were simulated in a cohort of patients with different baseline characteristics (e.g. time since diagnosis, asthma control questionnaire (ACQ-5) symptom score, smoking status, body mass index (BMI) and sex) using drug-disease models derived from large phase III/IV clinical studies. RESULTS: Simulation scenarios show that being a smoker, having higher baseline ACQ-5 and BMI, and long asthma history is associated with increased reliever medication use (p < 0.01). This increase correlates with a higher exacerbation risk and higher ACQ-5 scores over the course of treatment, irrespective of the underlying maintenance therapy. Switching non-responders to ICS monotherapy to combination therapy after 3 months resulted in immediate reduction in reliever medication use (i.e. 1.3 vs. 1.0 puffs/24 h for FP/SAL and BUD/FOR, respectively). In addition, switching patients with ACQ-5 > 1.5 at baseline to FP/SAL resulted in 34% less exacerbations than those receiving regular dosing BUD/FOR (p < 0.01). CONCLUSIONS: We have identified baseline characteristics of patients with moderate to severe asthma that are associated with greater reliever medication use, poor symptom control and higher exacerbation risk. Moreover, the effects of different inhaled corticosteroid (ICS)/long-acting beta agonist (LABA) combinations vary significantly when considering long-term treatment performance. These factors should be considered in clinical practice as a basis for personalised management of patients with moderate-severe asthma symptoms.

In this study we looked at how different factors affect the response to asthma treatment in people with moderate to severe asthma who are taking regular medication. Specifically, we wanted to quantify how much asthma duration, differences in the degree of symptom control and lung function, as well as smoking habit, body weight, and sex influence how well someone responds to regular maintenance therapy. Using computer simulations based on models obtained from data in a large patient population with moderate­severe asthma, we explored scenarios that reflect real-life management of patients undergoing treatment with inhaled corticosteroids alone or in combination with long-acting beta agonists over a 12-month period. We looked at how much reliever inhaler they use, how well they rate their asthma control, and how often they have asthma attacks. By considering these results together, we evaluated how well the treatments work on ongoing symptoms and/or reduce the risk of future asthma attacks. Our simulations showed that smokers, people with higher asthma symptom scores, who are obese, and have a longer history of asthma tend to use their reliever inhalers more often. This was linked to a higher risk of having asthma attacks and worse symptom control. Switching those patients who do not respond well to their initial treatment with corticosteroid to combination therapy reduced how much reliever inhaler they need. Also, the effects of fluticasone propionate/salmeterol combination therapy were greater than budesonide/formoterol. In conclusion, our study found that certain patient characteristics can predict how well someone responds to asthma treatment.

A Quantitative Clinical Pharmacology-Based Framework For Model-Informed Vaccine Development.

Historically, vaccine development and dose optimization have followed mostly empirical approaches without clinical pharmacology and model-informed approaches playing a major role, in contrast to conventional drug development. This is attributed to the complex cascade of immunobiological mechanisms associated with vaccines and a lack of quantitative frameworks for extracting dose-exposure-efficacy-toxicity relationships. However, the Covid-19 pandemic highlighted the lack of sufficient immunogenicity due to suboptimal vaccine dosing regimens and the need for well-designed, model-informed clinical trials which enhance the probability of selection of optimal vaccine dosing regimens. In this perspective, we attempt to develop a quantitative clinical pharmacology-based approach that integrates vaccine dose-efficacy-toxicity across various stages of vaccine development into a unified framework that we term as model-informed vaccine dose-optimization and development (MIVD). We highlight scenarios where the adoption of MIVD approaches may have a strategic advantage compared to conventional practices for vaccines.

Impact of Closed System Transfer Device (CSTD) Handling Procedure for Low-Transfer-Volume Dose Preparation of Biologic Drug Products.

Many challenges have been identified for ensuring compatibility of closed system transfer devices (CSTDs) with biologic drug products. One challenge is large hold-up volumes (HUVs) of CSTD components, which can be especially problematic with early-stage biologics when low transfer volumes smaller than the nominal fill volume may be used to achieve a wide range of doses with a single drug product configuration. Here, we identified possible CSTD handling techniques during dose preparation of a drug product requiring small volume transfers during reconstitution, intermediate dilution, and dilution in an IV bag, and systematically evaluated the impact of these handling procedures on the ability to deliver an accurate dose to the next step. We show that small changes to CSTD procedures can have a major impact on dose accuracy, depending on both CSTD HUVs and drug product-specific transfer volumes. We demonstrate that it is possible to craft CSTD instructions for use to mitigate these issues, and that the dose accuracy for specific drug product/CSTD combinations can be estimated using theoretical equations. Finally, we explored potential downsides of these mitigations. Our results emphasize key factors for consideration by both drug and CSTD manufacturers when assessing compatibility and providing CSTD instructions for use with biologics requiring low transfer volumes during dose preparation.

Use of Clinical Trial Simulations to Compare the Performance of Different Approaches for Population Analyses of Pediatric Pharmacokinetic Data.

The adequate characterization of the pharmacokinetics of a drug used in pediatrics is a mainstay of pediatric development programs and is critical for accurate dose selection in pediatrics. Analysis approaches can impact the estimation and characterization of pediatric pharmacokinetic parameters. Simulations were conducted to compare the performance of different approaches for analyzing pediatric pharmacokinetic data in the presence of extensive data from adult studies. Simulated clinical trial datasets were generated encompassing different scenarios that might be encountered in pediatric drug development. For each scenario, 250 clinical trials were simulated and analyzed using each of the following approaches: (1) estimating pediatric parameters using only pediatric data; (2) fixing specific parameters to adult estimates and estimating the remaining pediatric parameters using only pediatric data; (3) estimating pediatric parameters using adult parameters as informative Bayesian priors; (4) estimating pediatric parameters using combined adult and pediatric datasets with exponents for body weight effects estimated using adult and pediatric data; and (5) estimating pediatric parameters using combined adult and pediatric datasets with exponents for body weight effects estimated using pediatric data only. Each analysis approach was evaluated for its success in the estimation of true pediatric pharmacokinetic parameter values. Results demonstrated that analyzing pediatric data using a Bayesian approach generally performed best and had the lowest probability of significant bias in the estimated pediatric pharmacokinetic parameters among different scenarios evaluated. This clinical trial simulation framework can be used to inform the optimal approach for analyses of pediatric data for other pediatric drug development program scenarios beyond the cases evaluated in these analyses.

Understanding the Clinical Implications of Individual Patient Characteristics and Treatment Choice on the Risk of Exacerbation in Asthma Patients with Moderate-Severe Symptoms.

INTRODUCTION: The assessment of future risk has become an important feature in the management of patients with asthma. However, the contribution of patient-specific characteristics and treatment choices to the risk of exacerbation is poorly understood. Here we evaluated the effect of interindividual baseline differences on the risk of exacerbation and treatment performance in patients receiving regular maintenance doses of inhaled corticosteroids (ICS) or ICS/long-acting beta-agonists (LABA) combination therapy. METHODS: Exacerbations and changes to asthma symptoms 5-item Asthma Control Questionnaire (ACQ-5) were simulated over a 12-month period using a time-to-event and a longitudinal model developed from phase III/IV studies in patients with moderate-severe asthma (N = 16,282). Simulations were implemented to explore treatment performance across different scenarios, including randomised designs and real-world settings. Treatment options included regular dosing with ICS monotherapy [fluticasone propionate (FP)] and combination therapy [fluticasone propionate/salmeterol (FP/SAL) or budesonide/formoterol (BUD/FOR)]. Exacerbation rate was analysed using the log-rank test. The cumulative incidence of events was summarised stratified by treatment. RESULTS: Being a woman, smoker, having higher baseline ACQ-5 and body mass index (BMI) and lower forced expiratory volume in the first second (FEV1) are associated with increased exacerbation risk (p < 0.01). This risk is bigger in winter because of the seasonal variation effect. Across the different scenarios, the use of FP/SAL resulted in a 10% lower annual incidence of exacerbations relative to FP or regular dosing BUD/FOR, independently of baseline characteristics. Similar differences in the annual incidence of exacerbations were also observed between treatments in obese patients (BMI ≥ 25-35 kg/m2) (p < 0.01) and in patients who do not achieve symptom control on FP monotherapy. CONCLUSIONS: Individual baseline characteristics and treatment choices affect future risk. Achieving comparable levels of symptom control whilst on treatment does not imply comparable risk reduction, as shown by the lower exacerbation rates in FP/SAL vs. BUD/FOR-treated patients. These factors should be considered as a basis for personalised clinical management of patients with moderate-severe asthma.

The goal of this project was to demonstrate that individual baseline characteristics can affect the risk of exacerbation as well as the overall treatment response in patients receiving regular maintenance doses of inhaled corticosteroids, given as monotherapy or in combination with long-acting beta-agonists. Using computer simulations based on a drug­disease model previously developed from a large pool of patients with moderate­severe asthma symptoms (N = 16,282), we describe how demographic and clinical baseline patient characteristics at the time of treatment start correlate with the risk of exacerbation. Our results indicate that poor symptom control, limited lung function, obesity, smoking and sex are associated with significant increase in the incidence of asthma attacks. Such an effect is augmented in winter because of the contribution of seasonal variation. This analysis also allowed us to assess how different treatments modify or reduce the annual incidence of moderate to severe attacks. In addition, simulated scenarios showed that combination therapy with fluticasone propionate/salmeterol results in 10% fewer asthma attacks relative to budesonide/formoterol combination therapy. Such a difference may be associated with corticosteroid-specific properties, which vary between inhaled corticosteroids. Consequently, even though comparable level of immediate relief and symptom control may be achieved whilst on treatment, these effects do not imply the same long-term reduction in the risk of exacerbation. These factors should be considered as a basis for personalised clinical management of patients with moderate­severe asthma.

A Systematic Approach to Evaluating Closed System Drug-Transfer Devices During Drug Product Development.

The use of Closed System Drug-Transfer Devices (CSTDs) has increased significantly in recent years due to NIOSH and USP recommendations to use them during preparation of hazardous drugs. Mechanistic and material differences between CSTDs and traditional in-use components warrant an assessment of their impact on product quality and dosing accuracy. Using a combination of prevalent CSTDs with biologic molecules, we performed an extensive assessment of the effect of using CSTDs for dose preparation and observed no negative impact on product quality attributes. Additionally, we found that the CSTD hold-up volume is 2 to 4-fold higher than conventional in-use components and exhibited a strong dependence on the CSTD brand used. We also found that the CSTD brand and dosing volume have a major influence on dosing accuracy with suboptimal protein recovery at very low dosing volumes. We identified entrapment of product in the CSTD spike as the root cause for this sub-optimal recovery and found that flushing the CSTD spike with a brand-new syringe and not the dosing syringe aided in complete protein recovery. Taken together we present a systematic approach to evaluate the risks and impact of CSTD to drug product quality, dose preparation, and dosing accuracy.

A Model-Informed Drug Development (MIDD) Approach for a Low Dose of Empagliflozin in Patients with Type 1 Diabetes.

In clinical trials, sodium-glucose co-transporter (SGLT) inhibitor use as adjunct to insulin therapy in type 1 diabetes (T1D) provides glucometabolic benefits while diabetic ketoacidosis risk is increased. The SGLT2 inhibitor empagliflozin was evaluated in two phase III trials: EASE-2 and EASE-3. A low, 2.5-mg dose was included in EASE-3 only. As the efficacy of higher empagliflozin doses (i.e., 10 and 25 mg) in T1D has been established in EASE-2 and EASE-3, a modeling and simulation approach was used to generate additional supportive evidence on efficacy for the 2.5-mg dose. We present the methodology behind the development and validation of two modeling and simulation frameworks: M-EASE-1, a semi-mechanistic model integrating information on insulin, glucose, and glycated hemoglobin; and M-EASE-2, a descriptive model informed by prior information. Both models were developed independently of data from EASE-3. Simulations based on these models assessed efficacy in untested clinical trial scenarios. In this manner, the models provide supportive evidence for efficacy of low-dose empagliflozin 2.5 mg in patients with T1D, illustrating how pharmacometric analyses can support efficacy assessments in the context of limited data.

Evaluating the Impact of Physiological Properties of the Gastrointestinal Tract On Drug In Vivo Performance Using Physiologically Based Biopharmaceutics Modeling and Virtual Clinical Trials.

The physiological properties of the gastrointestinal tract, such as pH, fluid volume, bile salt concentration, and gastrointestinal transit time, are highly variable in vivo. These properties can affect the dissolution and absorption of a drug, depending on its properties and formulation. The effect of gastrointestinal physiology on the bioperformance of a drug was studied in silico for a delayed-release pantoprazole tablet and an immediate-release dolutegravir tablet. Physiologically based absorption models were developed and virtual clinical trials were performed. Reasons for the variability in drug bioperformance between subjects were investigated, taking into account differences in gastrointestinal tract characteristics, pharmacokinetic parameters, and additional parameters (e.g., permeability). Default software parameters describing gastrointestinal physiology in the fasted and fed states, and variation in these parameters, were altered to match variability in these parameters reported in vivo. The altered model physiologies better described the variability of gastrointestinal conditions, and therefore the results of virtual trials using these physiologies are likely to be more relevant in vivo. With such altered gastrointestinal physiologies used to develop models, it is possible to obtain additional knowledge and improve the understanding of subject-formulation interactions.

Pharmacokinetic Evaluation by Modeling and Simulation Analysis of a Donepezil Patch Formulation in Healthy Male Volunteers.

INTRODUCTION: This study characterized the pharmacokinetics (PKs) of a donepezil patch formulation currently under development, using mixed effect modeling analysis, and explored optimal patch dosing regimens in comparison with the donepezil oral formulation. METHODS: PK data used in this analysis were from 60 healthy Korean male subjects participating in two Phase I studies, where subjects received single or multiple doses of donepezil of 43.75, 87.5, and 175 mg via patches, and 12 of them received a single oral dose of 10 mg of donepezil, followed by a single dose of donepezil via a patch. Donepezil PKs were analyzed by nonlinear mixed effect modeling using NONMEM software. RESULTS: A well-stirred model with two-compartment distribution and delayed absorption was chosen as the best model for the oral formulation. The PKs of donepezil after the patch applications were best described by a two-compartment linear model with zero-order absorption (D2) and absorption delay. The relative bioavailability (BA) of donepezil after the patch application compared with oral dosing was described to be affected by the duration of patch application. CONCLUSION: PK simulations based on the chosen PK models suggested that, overall, donepezil exposure in plasma is similar whether with 10 mg of oral donepezil every 24 h or a 175 mg patch every 72 h, and likewise with 5 mg of oral donepezil every 24 h or an 87.5 mg patch every 72 h.