Improved kinetic parameter estimation in pH-profile data treatment.
Statistical problems in temperature stability parameter estimation have been the subject of many papers whereas statistics in, pH-profile parameter estimation have focused little attention. However, the conventional two step method used in data treatment in both cases leads to identical statistical problems. The aim of this study is then to introduce a method that improves statistics in pH-profile parameter estimation. A one step non-linear method that takes into account the errors in drug content determination is proposed. A mathematical relationship between drug content C, pH and time t is tested. The proposed method allows the estimation of the specific kinetic constants and the dissociation constant (pK(a)) in a single run. The most likely experimental initial drug contents C(0j),. where j is the index of a given experiment, are also determined. This approach that takes into account all relevant experimental information for the estimation of kinetic parameters is more rigorous from a statistical viewpoint than the classical two step methods. Kinetic data from acetylsalicylic acid (ASA) hydrolysis was used for the tests.
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Laboratoire de Chimie bioanalytique, de Toxicologie et de Chimie physique appliquée, Institut de Pharmacie, Université Libre de Bruxelles, Campus de la Plaine, CP 205/1 Boulevard du Triomphe, B-1050, Brussels, Belgium.
Bogaerts
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P
Hanus
R
R
Hanocq
M
M
Dubois
J
J
D000465:Algorithms; D001241:Aspirin / Q000737:chemistry; D002851:Chromatography, High Pressure Liquid; D003365:Costs and Cost Analysis; D003627:Data Interpretation, Statistical; D004355:Drug Stability; D006863:Hydrogen-Ion Concentration; D007700:Kinetics; D008390:Markov Chains; D017711:Nonlinear Dynamics
D001241:Aspirin