A new algorithm for the kinetic data analysis

In this paper, a new algorithm for the kinetic data analysis is presented. The main objective of the algorithm is to retrieve the maximum information concerned with a multi-response complex chemical system evolving in time, in order to retrieve the rate constants (calibration problem) or the initial concentration of species. As a difference with other data treatments found in the literature, the algorithm is able to estimate the uniqueness and reliability of the calculated rate constants. This task is carried out by analyzing of the principal components of the sensitivity coefficients with regard to the rate constants. The analysis allows understanding whether the located stationary points consist of a single point, or a surface relating a set of rate constants on which the least-squares (LS) function takes a constant value. In the latter case, the rate constants will not be uniquely determined for the chosen experimental design. gorithm has been materialized in the opkine 2 software, which has been provided with a wide range of mathematical resources related to the minima location, and to the integration of stiff ordinary differential equations (ODE) systems. Finally, the statistical criteria used to compare the experimental data with a model are not only restricted to the LS method, and it is possible to use the determinant criterion, or to fit the principal components of the experimental responses. The application of the algorithm to first-order networks allows saving up a great quantity of calculation time compared to classical numerical integration.