Simplified Aztreonam Dosing in Patients with End-Stage Renal Disease: Results of a Monte Carlo Simulation.

The manufacturer-recommended aztreonam dosing for patients with creatinine clearance values of <10 ml/min/1.73 m2 is complex. It is not known whether simpler posthemodialysis dosing administered once daily or thrice weekly can reliably achieve pharmacodynamic goals. We found that 1 or 2 g administered once daily after hemodialysis had >90% probability of target attainment up to MICs of 4 or 8 mg/liter, respectively. Thrice-weekly dosing should generally be avoided, except in nonsevere infections with MICs of ≤0.5 mg/liter.

Integrating dose estimation into a decision-making framework for model-based drug development.

Model-informed drug discovery and development offers the promise of more efficient clinical development, with increased productivity and reduced cost through scientific decision making and risk management. Go/no-go development decisions in the pharmaceutical industry are often driven by effect size estimates, with the goal of meeting commercially generated target profiles. Sufficient efficacy is critical for eventual success, but the decision to advance development phase is also dependent on adequate knowledge of appropriate dose and dose-response. Doses which are too high or low pose risk of clinical or commercial failure. This paper addresses this issue and continues the evolution of formal decision frameworks in drug development. Here, we consider the integration of both efficacy and dose-response estimation accuracy into the go/no-go decision process, using a model-based approach. Using prespecified target and lower reference values associated with both efficacy and dose accuracy, we build a decision framework to more completely characterize development risk. Given the limited knowledge of dose response in early development, our approach incorporates a set of dose-response models and uses model averaging. The approach and its operating characteristics are illustrated through simulation. Finally, we demonstrate the decision approach on a post hoc analysis of the phase 2 data for naloxegol (a drug approved for opioid-induced constipation).

Population exposure-safety analysis of cediranib for Phase I and II studies in patients with cancer.

AIMS: A multistudy analysis of cediranib, a potent, selective inhibitor of all three vascular endothelial growth factor receptors (VEGFR-1, -2 and -3), was conducted to establish population exposure-safety models for the relationship of cediranib exposure to the safety endpoints, diastolic and systolic blood pressure (DBP and SBP) and diarrhoea in cancer patients. These models were applied to predict safety outcomes for different cediranib dose regimens. METHODS: Models for hypertension and diarrhoea were constructed based on data from 10 Phase I and three Phase II studies comprising 631 cancer patients following cediranib once-daily oral dosing. Daily DBP and SBP were simultaneously characterized using indirect response models for predicted cediranib concentration-time courses, while daily diarrhoea events were modelled as ordered categorical variables with a proportional odds model with a Markov element for predicted average cediranib concentrations. RESULTS: For 20 mg cediranib once-daily oral administration, the mean increase in DBP and SBP was predicted to be 7 (95% CI 3-13) and 8 mmHg (95% CI 3-16), respectively, while the probability of mild diarrhoea, but not the severity, was predicted to increase over time. Severe diarrhoea was predicted to be resolved rapidly upon discontinuation of cediranib treatment. CONCLUSIONS: Maximum blood pressure increase was observed within the first few days of cediranib treatment, consistent with the pharmacokinetic profile of cediranib reaching steady state in about 5 days. The probability of diarrhoea increased with cediranib concentration but was far more dependent on the status of diarrhoea predicted on the previous day.

Drug-disease modeling in the pharmaceutical industry - where mechanistic systems pharmacology and statistical pharmacometrics meet.

Modeling & simulation (M&S) methodologies are established quantitative tools, which have proven to be useful in supporting the research, development (R&D), regulatory approval, and marketing of novel therapeutics. Applications of M&S help design efficient studies and interpret their results in context of all available data and knowledge to enable effective decision-making during the R&D process. In this mini-review, we focus on two sets of modeling approaches: population-based models, which are well-established within the pharmaceutical industry today, and fall under the discipline of clinical pharmacometrics (PMX); and systems dynamics models, which encompass a range of models of (patho-)physiology amenable to pharmacological intervention, of signaling pathways in biology, and of substance distribution in the body (today known as physiologically-based pharmacokinetic models) - which today may be collectively referred to as quantitative systems pharmacology models (QSP). We next describe the convergence - or rather selected integration - of PMX and QSP approaches into 'middle-out' drug-disease models, which retain selected mechanistic aspects, while remaining parsimonious, fit-for-purpose, and able to address variability and the testing of covariates. We further propose development opportunities for drug-disease systems models, to increase their utility and applicability throughout the preclinical and clinical spectrum of pharmaceutical R&D.

Evaluation of Aztreonam Dosing Regimens in Patients With Normal and Impaired Renal Function: A Population Pharmacokinetic Modeling and Monte Carlo Simulation Analysis.

Aztreonam is a monocyclic ß-lactam antibiotic often used to treat infections caused by Enterobacteriaceae or Pseudomonas aeruginosa. Despite the long history of clinical use, population pharmacokinetic modeling of aztreonam in renally impaired patients is not yet available. The aims of this study were to assess the impact of renal impairment on aztreonam exposure and to evaluate dosing regimens for patients with renal impairment. A population model describing aztreonam pharmacokinetics following intravenous administration was developed using plasma concentrations from 42 healthy volunteers and renally impaired patients from 2 clinical studies. The final pharmacokinetic model was used to predict aztreonam plasma concentrations and evaluate the probability of pharmacodynamic target attainment (PTA) in patients with different levels of renal function. A 2-compartment model with first-order elimination adequately described aztreonam pharmacokinetics. The population mean estimates of aztreonam clearance, intercompartmental clearance, volume of distribution of the central compartment, and volume of distribution of the peripheral compartment were 4.93 L/h, 9.26 L/h, 7.43 L, and 6.44 L, respectively. Creatinine clearance and body weight were the most significant variables to explain patient variability in aztreonam clearance and volume of distribution, respectively. Simulations using the final pharmacokinetic model resulted in a clinical susceptibility break point of 4 and 8 mg/L, respectively, based on the clinical use of 1- and 2-g loading doses with the same or reduced maintenance dose every 8 hours for various renal deficiency patients. The population pharmacokinetic modeling and PTA estimation support adequate PTAs (>90% PTA) from the aztreonam label for dose adjustment of aztreonam in patients with moderate and severe renal impairment.

Reporting guidelines for population pharmacokinetic analyses.

The purpose of this work was to develop a consolidated set of guiding principles for reporting of population pharmacokinetic (PK) analyses based on input from a survey of practitioners as well as discussions between industry, consulting and regulatory scientists. The survey found that identification of population covariate effects on drug exposure and support for dose selection (where population PK frequently serves as preparatory analysis to exposure-response modeling) are the main areas of influence for population PK analysis. The proposed guidelines consider two main purposes of population PK reports (1) to present key analysis findings and their impact on drug development decisions, and (2) as documentation of the analysis methods for the dual purpose of enabling review of the analysis and facilitating future use of the models. This work also identified two main audiences for the reports: (1) a technically competent group responsible for in-depth review of the data, methodology, and results, and (2) a scientifically literate, but not technically adept group, whose main interest is in the implications of the analysis for the broader drug development program. We recommend a generalized question-based approach with six questions that need to be addressed throughout the report. We recommend eight sections (Synopsis, Introduction, Data, Methods, Results, Discussion, Conclusions, Appendix) with suggestions for the target audience and level of detail for each section. A section providing general expectations regarding population PK reporting from a regulatory perspective is also included. We consider this an important step towards industrialization of the field of pharmacometrics such that non-technical audience also understands the role of pharmacometrics analyses in decision making. Population PK reports were chosen as representative reports to derive these recommendations; however, the guiding principles presented here are applicable for all pharmacometric reports including PKPD and simulation reports.