Enoval - Features

Features

The objective of enoval is to allow the user to apply easily the statistical methodology for the validation of an analytical method, an bio-analytical method or an immuno-assay. These statistical technics have been developed by an SFSTP commission in 1997 and are currently spread to the whole bunch of dosing methods by a new SFSTP commission. The main features of enoval are:

Calibration Curve Fitting: Fitting of models supposed to be the calibration curve as well as providing help to select the best model to use as the calibration curve among a pre-determined list of models, based on data realised for a calibration. Fitting consists in estimating model parameters using the classical statistical fitting technics. Clear indications (graphs and/or indeces) allowing the user to jugde the goodness-of-fit will be reported.
Inverse Predictions: For a selected model, the application allows the user to obtain and to calculate the inverse prediction (back-calculated concentrations) for any observation obtained within the same conditions as the ones for the calibration curve.
Accuracy Profile: For every fitted model, the corresponding accuracy profile is calculated (graphical representation) and serves as decision tool.
Evaluation of the effect of the matrix: It is possible to input two different datasets (within and without the matrix) for which the accuracy profiles will be compared.
Estimation of validation criteria: The optimal estimation of the main criteria required for the validation of analytical methods such as indicated in the regulatory documents as ICH (Q2A & Q2B) and ISO. These criteria are calculated based on the inverse predictions obtained or not with the help of enoval.
Diagnostics: Diagnostics are available to allow the user to identify the lacks of fit.
Recommendations on experimental design: The quality of the estimation of these criteria depends on a large measure of the experiments which are realized and are under the responsability of the user. However, these recommendations on the nature and the number of the experiments to be realized will be accessible in the enoval application.
Reporting: A validation report containing whole the information required and necessary to judge the validity of an analytical method could be edited as required by the user.



		Features The objective of enoval is to allow the user to apply easily the statistical methodology for the validation of an analytical method, an bio-analytical method or an immuno-assay. These statistical technics have been developed by an SFSTP commission in 1997 and are currently spread to the whole bunch of dosing methods by a new SFSTP commission. The main features of enoval are: Calibration Curve Fitting: Fitting of models supposed to be the calibration curve as well as providing help to select the best model to use as the calibration curve among a pre-determined list of models, based on data realised for a calibration. Fitting consists in estimating model parameters using the classical statistical fitting technics. Clear indications (graphs and/or indeces) allowing the user to jugde the goodness-of-fit will be reported. Inverse Predictions: For a selected model, the application allows the user to obtain and to calculate the inverse prediction (back-calculated concentrations) for any observation obtained within the same conditions as the ones for the calibration curve. Accuracy Profile: For every fitted model, the corresponding accuracy profile is calculated (graphical representation) and serves as decision tool. Evaluation of the effect of the matrix: It is possible to input two different datasets (within and without the matrix) for which the accuracy profiles will be compared. Estimation of validation criteria: The optimal estimation of the main criteria required for the validation of analytical methods such as indicated in the regulatory documents as ICH (Q2A & Q2B) and ISO. These criteria are calculated based on the inverse predictions obtained or not with the help of enoval. Diagnostics: Diagnostics are available to allow the user to identify the lacks of fit. Recommendations on experimental design: The quality of the estimation of these criteria depends on a large measure of the experiments which are realized and are under the responsability of the user. However, these recommendations on the nature and the number of the experiments to be realized will be accessible in the enoval application. Reporting: A validation report containing whole the information required and necessary to judge the validity of an analytical method could be edited as required by the user. Login - About - Minimal Requirements - References.
	ENOV-4.1d PROD Last Update: January 9 2024 © Pharmalex 2024.