Model-based drug development: strengths, weaknesses, opportunities, and threats for broad application of pharmacometrics in drug development.

Systematic implementation of model-based drug development (MBDD) to drug discovery and development has the potential to significantly increase the rate of medical breakthroughs and make available new and better treatments to patients. An analysis of the strengths, weaknesses, opportunities, and threats (ie, SWOT) was conducted through focus group discussions that included 24 members representing 8 pharmaceutical companies to systematically assess the challenges to implementing MBDD into the drug development decision-making process. The application of the SWOT analysis to the successful implementation of MBDD yielded 19 strengths, 27 weaknesses, 34 opportunities, and 22 threats, which support the following conclusions. The shift from empirical drug development to MBDD requires a question-based mentality; early, proactive planning; dynamic access to multisource data; quantitative knowledge integration; multidisciplinary collaboration; effective communication and leadership skills; and innovative, impactful application of pharmacometrics focused on enhancing quantitative decision making. The ultimate goal of MBDD is to streamline discovery and development of innovative medicines to benefit patients.

Model-based drug development survey finds pharmacometrics impacting decision making in the pharmaceutical industry.

During the past decade, the pharmaceutical industry has seen the increasing application of pharmacometrics approaches in drug development. However, the full potential of incorporating model-based approaches in drug development and its impact on decision making has not been fully realized to date. In 2009, a survey on model-based drug development (MBDD) was conducted (1) to further understand the current state of MBDD in the pharmaceutical industry and (2) to identify opportunities to realize the full potential of MBDD. Ten large and mid-sized pharmaceutical companies provided responses to this survey. The results indicate that MBDD is achieving broad application in early and late development and is positively affecting both internal and regulatory decisions. Senior leadership (vice president and higher) within the companies indicated widely accepted utility for dose selection and gaining acceptance for study design and regulatory interactions but limited acceptance in discovery and commercial/pipeline decisions. Mounting appreciation for the impact of MBDD on internal and regulatory decision-making bodes well for the future of the pharmacometric discipline and the growth of opportunities to realize the full potential of MBDD.

Population pharmacokinetic model for gatifloxacin in pediatric patients.

The broad spectrum of antimicrobial activity, oral bioavailability, extensive tissue distribution, and once-daily intravenous or oral dosing of gatifloxacin, an expanded-spectrum 8-methoxy fluoroquinolone, make it a potentially useful agent for the treatment of pediatric infections. A population pharmacokinetic model was developed to describe the pharmacokinetics of gatifloxacin in children. Data for analysis were obtained from a single-dose safety/pharmacokinetic study utilizing intensive blood sampling in patients aged 6 months to 16 years. Each subject received a single oral dose of gatifloxacin as a suspension, at doses of 5, 10, or 15 mg/kg of body weight. A total of 845 samples were obtained from 82 patients. A one-compartment model with first-order absorption and elimination was the most appropriate to describe the gatifloxacin concentrations. Covariate analysis using forward selection and backward elimination found that apparent clearance was related to body surface area, and apparent volume of distribution was related to body weight. No effect of age on drug clearance could be identified once clearance was corrected for body surface area. Based on pharmacokinetic simulations, the 10-mg/kg (maximum, 400 mg) once-daily dose of gatifloxacin is expected to provide drug exposure similar to that in healthy adults. The population pharmacokinetic model described herein will be used for Bayesian analyses of sparse pharmacokinetic sampling in phase II/III clinical trials and for Monte Carlo simulation experiments. The success of this strategy provides a model for future pediatric drug development programs.