Sentence examples for methodology and multiple from inspiring English sources

Response surface methodology and multiple response optimization were used to search for an optimized formula.

It was concluded that response surface methodology and multiple response optimization could be successfully used to design and optimize extended release formulations with desired preplanned release profile.

Applying response surface methodology and multiple linear regressions enabled us to build phenomenological models relating PI to water and salt content, and to temperature.

In vitro studies, the response surface methodology and multiple response optimization utilizing the polynomial equation were used to search for the optimal formulation with specific release rate at different time intervals.

The purpose of the present study was to apply response surface methodology and multiple response optimization utilizing superimposed contour diagrams to design extended release formulations with a preplanned release profile.

The second part consists of the use of response surface methodology and multiple regression to develop an experimental design modeland to assess the individual and interactive effects of pH, power (Po), ZVI dose and H2O2.

The response surface methodology (RS M and multiple response optimization utilizing the polynomial equation were used to search for the optimal coating formulation with a specific release rate at different time intervals.

A crossed mixture design coupled with data analysis by means of response surface methodology (RS M and multiple response optimization through a Desirability function (D) was applied for the first time to the area of development and optimization of culture media for the production of recombinant proteins in mammalian cells.

The response surface methodology (RSM) and multiple response optimization utilizing the polynomial equation were used to search for the optimal formulation with specific release rate at different time intervals and to quantify the effect of each formulation variables.

All these aforementioned factors make data interpretation difficult, reinforcing the need for meta-analytic studies in this area using homogeneous morphometric methodologies and including multiple samples of patients.

Ptolemy II advocates a component-based design methodology, and hierarchically integrates multiple models of computation, which can be used to capture different design perspectives.