RPEM: Randomized Monte Carlo parametric expectation maximization algorithm.

Inspired from quantum Monte Carlo, by sampling discrete and continuous variables at the same time using the Metropolis-Hastings algorithm, we present a novel, fast, and accurate high performance Monte Carlo Parametric Expectation Maximization (MCPEM) algorithm. We named it Randomized Parametric Expectation Maximization (RPEM). We compared RPEM with NONMEM's Importance Sampling Method (IMP), Monolix's Stochastic Approximation Expectation Maximization (SAEM), and Certara's Quasi-Random Parametric Expectation Maximization (QRPEM) for a realistic two-compartment voriconazole model with ordinary differential equations using simulated data. We show that RPEM is as fast and as accurate as the algorithms IMP, QRPEM, and SAEM for the voriconazole model in reconstructing the population parameters, for the normal and log-normal cases.

Interdisciplinary pharmacometrics linking oseltamivir pharmacology, influenza epidemiology and health economics to inform antiviral use in pandemics.

AIMS: A modular interdisciplinary platform was developed to investigate the economic impact of oseltamivir treatment by dosage regimen under simulated influenza pandemic scenarios. METHODS: The pharmacology module consisted of a pharmacokinetic distribution of oseltamivir carboxylate daily area under the concentration-time curve at steady state (simulated for 75 mg and 150 mg twice daily regimens for 5 days) and a pharmacodynamic distribution of viral shedding duration obtained from phase II influenza inoculation data. The epidemiological module comprised a susceptible, exposed, infected, recovered (SEIR) model to which drug effect on the basic reproductive number (R0 ), a measure of transmissibility, was linked by reduction of viral shedding duration. The number of infected patients per population of 100 000 susceptible individuals was simulated for a series of pandemic scenarios, varying oseltamivir dose, R0 (1.9 vs. 2.7), and drug uptake (25%, 50%, and 80%). The number of infected patients for each scenario was entered into the health economics module, a decision analytic model populated with branch probabilities, disease utility, costs of hospitalized patients developing complications, and case-fatality rates. Change in quality-adjusted life years was determined relative to base case. RESULTS: Oseltamivir 75 mg relative to no treatment reduced the median number of infected patients, increased change in quality-adjusted life years by deaths averted, and was cost-saving under all scenarios; 150 mg relative to 75 mg was not cost effective in low transmissibility scenarios but was cost saving in high transmissibility scenarios. CONCLUSION: This methodological study demonstrates proof of concept that the disciplines of pharmacology, disease epidemiology and health economics can be linked in a single quantitative framework.