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Kakhi M.,U.S. Food and Drug Administration | Chittenden J.,Pharsight
Journal of Pharmaceutical Sciences | Year: 2013

In environments where complete mechanistic knowledge of the system dynamics is not available, a synergy of first-principle concepts, stochastic methods and statistical approaches can provide an efficient, accurate, and insightful strategy for model development. In this work, a system of ordinary differential equations describing system pharmacokinetics (PK) was coupled to a Wiener process for tracking the absorption rate coefficient, and was embedded in a nonlinear mixed effects population PK formalism. The procedure is referred to as "stochastic deconvolution" and it is proposed as a diagnostic tool to inform on a mapping function between the fraction of the drug absorbed and the fraction of the drug dissolved when applying one-stage methods to in vitro-in vivo correlation modeling. The goal of this work was to show that stochastic deconvolution can infer an a priori specified absorption profile given dense observational (simulated) data. The results demonstrate that the mathematical model is able to accurately reproduce the simulated data in scenarios where solution strategies for linear, time-invariant systems would assuredly fail. To this end, PK systems that are representative of Michaelis-Menten kinetics and enterohepatic circulation were investigated. Furthermore, the solution times are manageable using a modest computer hardware platform. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

Kakhi M.,U.S. Food and Drug Administration | Marroum P.,Marroum Pharmaceutical Consulting | Chittenden J.,Pharsight
Biopharmaceutics and Drug Disposition | Year: 2013

A two-stage, numerical deconvolution approach was employed to develop level A in vitro-in vivo correlations using data for three formulations of an extended-release oral dosage form. The in vitro dissolution data for all formulations exhibited near-complete dissolution within the time frame of the test. The pharmacokinetic concentration-time profiles for 16 subjects in a cross-over study demonstrated notably limited bioavailability for the slowest formulation. These data were used as the basis for the IVIVC model development. Two models were identified that satisfied the nominal requirements for a conclusive internal predictability of the IVIVC, provided that all three formulations were used as internal datasets. These were a simple linear model with absorption cut-off and a piecewise-linear variable absorption scale model. A subsequent cross-validation of the models' robustness indicated that neither model predicted satisfactorily the pharmacokinetic characteristics of all formulations in a conclusive manner. The piecewise-linear variable absorption scale model provided the most accurate results, particularly with respect to the prediction of the slowest formulation's pharmacokinetic metrics. But this latter model also involved additional free parameters compared with the simple linear model with absorption cut-off. It is argued that more complex IVIVC models with extra parameterization require comprehensive validation to ascertain the accuracy and robustness of the model. In order to achieve this, it is necessary to ensure a complete suite of supporting datasets for internal and external validation, irrespective of the mathematical approach used subsequently to develop the IVIVC. Copyright © 2013 John Wiley & Sons, Ltd. Copyright © 2013 John Wiley & Sons, Ltd.

Marier J.-F.,Pharsight | Trinh M.,Pharsight | Pheng L.H.,Pharsight | Palleja S.M.,Tobira Therapeutics | Martin D.E.,Tobira Therapeutics
Antimicrobial Agents and Chemotherapy | Year: 2011

TBR-652 is a novel CCR5 antagonist with potent in vitro anti-HIV activity. The objective of this study was to determine the pharmacokinetics (PK) and pharmacodynamics (PD) of TBR-652 in HIV-1-infected, antiretroviral treatment-experienced, CCR5 antagonist-naïve patients. A double-blind, placebo-controlled, randomized, dose-escalating study of TBR-652 monotherapy given once daily orally for 10 days was performed, followed by a 40-day follow-up period. Approximately 10 patients/dose level received 25, 50, 75, 100, and 150 mg TBR-652 or placebo (4:1). Blood was collected at different intervals for PK and HIV-1 RNA assessments. PK analysis of TBR-652 was performed using noncompartmental methods. PK/PD was modeled using a maximum inhibitory effect model (E max) and 50% inhibitory concentrations (IC 50). TBR-652 was well absorbed in the systemic circulation. TBR-652 concentration levels declined slowly, with mean elimination half-lives ranging from 22.5 to 47.62 h across dose levels. TBR-652 treatment resulted in potent, dose-dependent decreases in viral load, with statistically significant decreases in nadir HIV-1 RNA compared to baseline for all dose levels. Suppression of HIV-1 RNA persisted over the 40-day follow-up period. A steep exposure-effect relationship was observed, with an E max of -1.43 log 10 copies/ml and IC 50 of 13.1 ng/ml. TBR-652 was generally safe and well tolerated at all dose levels studied. Short-term monotherapy treatments of TBR-652 in HIV-1-infected patients resulted in promising PK and PD results, with a clear exposure-response relationship at the current dose levels studied. Data from this study support further development of TBR-652 in HIV-infected patients. Copyright © 2011, American Society for Microbiology. All Rights Reserved.

Miller B.,Cubist Pharmaceuticals Inc. | Hershberger E.,Cubist Pharmaceuticals Inc. | Benziger D.,Cubist Pharmaceuticals Inc. | Trinh M.,Pharsight | Friedland I.,Cubist Pharmaceuticals Inc.
Antimicrobial Agents and Chemotherapy | Year: 2012

The pharmacokinetics and safety of ceftolozane, a novel cephalosporin, and tazobactam, a β-lactamase inhibitor, alone and in combination as a 2:1 ratio in single doses of up to 2,000 and 1,000 mg of ceftolozane and tazobactam, respectively, and multiple doses of up to 3,000 and 1,500 mg of ceftolozane and tazobactam, respectively, per day were evaluated in healthy adult subjects. In part 1, groups of six subjects each received single ascending doses of ceftolozane, tazobactam, and ceftolozane-tazobactam in a within-cohort crossover design. In part 2, groups of 5 or 10 subjects each received multiple doses of ceftolozane, tazobactam, or ceftolozane-tazobactam for 10 days. After a single dose of ceftolozane alone, the ranges of mean values for half-life (2.48 to 2.64 h), the total clearance (4.35 to 6.01 liters/h), and the volume of distribution at steady state (11.0 to 14.1 liters) were consistent across dose levels and similar to those observed when ceftolozane was coadministered with tazobactam. Mean values after multiple doses for ceftolozane alone and ceftolozane- tazobactam were similar to those seen following a single dose. The pharmacokinetics of the dosing regimens evaluated were dose proportional and linear. Ceftolozane-tazobactam was well tolerated and systemic adverse events were uncommon. Mild infusion-related adverse events were the most commonly observed following multiple-dose administration. Adverse events were not dose related, and no dose-limiting toxicity was identified. Copyright © 2012, American Society for Microbiology. All Rights Reserved.

Bruno R.,Pharsight | Mercier F.,Pharsight | Claret L.,Pharsight
Clinical Pharmacology and Therapeutics | Year: 2014

Model-based drug development in oncology is still lagging despite a good momentum in the clinical pharmacology and pharmacometry community in the past few years. The failure rate of late-stage oncology studies is one of the highest across therapeutic areas. The modeling of the relationship between longitudinal tumor size and overall survival has been proposed to enhance learning in early clinical studies, to predict overall survival, and to simulate clinical trials. This approach has the potential to support proof of concept, early clinical decisions, and design of late-stage trials, but it is not yet widely integrated into the oncology drug development process. In this article, we review the state of these modeling efforts and discuss several key applications of these models. We conclude by suggesting a few paths forward.

The purpose of bioanalysis in the pharmaceutical industry is to provide 'raw' data about the concentration of a drug candidate and its metabolites as input for studies of drug properties such as pharmacokinetic (PK), toxicokinetic, bioavailability/bioequivalence and other studies. Building a seamless workflow from the laboratory to final reports is an ongoing challenge for IT groups and users alike. In such a workflow, PK automation can provide companies with the means to vastly increase the productivity of their scientific staff while improving the quality and consistency of their reports on PK analyses. This report presents the concept and benefits of PK automation and discuss which features of an automated reporting workflow should be translated into software requirements that pharmaceutical companies can use to select or build an efficient and effective PK automation solution that best meets their needs. © 2011 Future Science Ltd.

Gabrielsson J.,Swedish University of Agricultural Sciences | Weiner D.,Pharsight
Methods in Molecular Biology | Year: 2012

When analyzing pharmacokinetic data, one generally employs either model fitting using nonlinear regression analysis or non-compartmental analysis techniques (NCA). The method one actually employs depends on what is required from the analysis. If the primary requirement is to determine the degree of exposure following administration of a drug (such as AUC), and perhaps the drug's associated pharmacokinetic parameters, such as clearance, elimination half-life, T max, C max, etc., then NCA is generally the preferred methodology to use in that it requires fewer assumptions than model-based approaches. In this chapter we cover NCA methodologies, which utilize application of the trapezoidal rule for measurements of the area under the plasma concentration-time curve. This method, which generally applies to first-order (linear) models (although it is often used to assess if a drug's pharmacokinetics are nonlinear when several dose levels are administered), has few underlying assumptions and can readily be automated. In addition, because sparse data sampling methods are often utilized in toxicokinetic (TK) studies, NCA methodology appropriate for sparse data is also discussed. © 2012 Springer Science+Business Media, LLC.

Claret L.,Pharsight
Journal of clinical oncology : official journal of the American Society of Clinical Oncology | Year: 2013

To assess new metrics of tumor-size response to predict overall survival (OS) in colorectal cancer (CRC) in Western and Chinese patients. Various metrics of tumor-size response were estimated using longitudinal tumor size models and data from two phase III studies that compared bevacizumab plus chemotherapy versus chemotherapy as first-line therapy in Western (n = 923) and Chinese (n = 203) patients with CRC. Baseline prognostic factors and tumor-size metrics estimates were assessed in multivariate models to predict OS. Predictive performances of the models were assessed by simulating multiple replicas of the phase III studies. Time to tumor growth (TTG) was the best metric to predict OS. TTG fully captured bevacizumab effect. Chinese ethnicity had no impact on OS or on the TTG-OS relationships. The model correctly predicted OS distributions in each arm as well as bevacizumab hazard ratio (model prediction, 0.75 v 0.68 observed in Western patients; 95% prediction interval, 0.62 to 0.91). TTG captured therapeutic benefit with bevacizumab in first-line CRC patients. Chinese ethnicity had no impact. Longitudinal tumor size data coupled with model-based approaches may offer a powerful alternative in the design and analysis of early clinical studies.

PRINCETON, N.J.--(BUSINESS WIRE)--Certara®, the leading provider of decision support technology and consulting services for optimizing drug development and improving health outcomes, today announced that the Standards Council of Canada (SCC) has awarded Good Laboratory Practices (GLP) certification to its Certara Strategic Consulting (CSC) Montreal facility. CSC Montreal has passed the requisite inspection and study audits and is now recognized as a GLP compliant Toxicokinetic Test Site by SCC. “To derive the greatest value from modeling and simulation (M&S), sponsors need to incorporate these quantitative methods into their drug discovery and development process as early as possible,” said Dr. Martin Beliveau, director of CSC. “By attaining GLP accreditation, we underscore the high quality of our toxicology analysis services, demonstrate the SCC compliance of our processes and procedures, and underscore to sponsor companies the many benefits of incorporating M&S into their pre-clinical programs.” CSC Montreal performs toxicokinetic analyses to support the pivotal toxicology programs required for new drug regulatory submissions. Drug concentrations observed in animals and the appearance of toxic adverse effects are routinely incorporated into M&S workflows to derive safer initial and escalation doses for first-in-human trials. These M&S workflows can also provide insight into the minimum anticipated biological effect level (MABEL) of a drug and efficacious outcomes. Formed from the merger of Pharsight Consulting Services, Quantitative Solutions, and d3 Medicine, CSC is the largest global pharmacometrics consultancy. CSC is comprised of more than 100 scientists, most with PhDs, using a wide range of M&S methods and technologies to support global sponsors in bringing new therapies to patients. Regulatory agencies are increasingly promoting the use of M&S in drug programs to inform key decisions. M&S has been highlighted in more than a dozen regulatory guidance documents over the past few years and is used by those agencies to review drug submittals. Certara is a leading decision support technology and consulting organization committed to optimizing drug development and improving health outcomes. Certara’s solutions, which span drug discovery through patient care, use the most scientifically-advanced modeling and simulation technologies and regulatory strategies to increase the probability of regulatory and commercial success. Its clients include hundreds of global biopharmaceutical companies, leading academic institutions, and key regulatory agencies. For more information, visit

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