The thermodynamic dissociation constants of four non-steroidal anti-inflammatory drugs by the least-squares nonlinear regression of multiwavelength spectrophotometric pH-titration data
Jazyk angličtina Země Velká Británie, Anglie Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
17825517
DOI
10.1016/j.jpba.2007.07.029
PII: S0731-7085(07)00442-6
Knihovny.cz E-zdroje
- MeSH
- antiflogistika nesteroidní chemie MeSH
- chemické modely MeSH
- koncentrace vodíkových iontů MeSH
- metoda nejmenších čtverců MeSH
- molekulární struktura MeSH
- nelineární dynamika MeSH
- rozpustnost MeSH
- spektrofotometrie metody MeSH
- termodynamika * MeSH
- titrace metody MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- antiflogistika nesteroidní MeSH
The mixed dissociation constants of four non-steroidal anti-inflammatory drugs (NSAIDs) ibuprofen, diclofenac sodium, flurbiprofen and ketoprofen at various ionic strengths I of range 0.003-0.155, and at temperatures of 25 degrees C and 37 degrees C, were determined with the use of two different multiwavelength and multivariate treatments of spectral data, SPECFIT/32 and SQUAD(84) nonlinear regression analyses and INDICES factor analysis. The factor analysis in the INDICES program predicts the correct number of components, and even the presence of minor ones, when the data quality is high and the instrumental error is known. The thermodynamic dissociation constant pK(a)(T) was estimated by nonlinear regression of (pK(a), I) data at 25 degrees C and 37 degrees C. Goodness-of-fit tests for various regression diagnostics enabled the reliability of the parameter estimates found to be proven. PALLAS, MARVIN, SPARC, ACD/pK(a) and Pharma Algorithms predict pK(a) being based on the structural formulae of drug compounds in agreement with the experimental value. The best agreement seems to be between the ACD/pK(a) program and experimentally found values and with SPARC. PALLAS and MARVIN predicted pK(a,pred) values with larger bias errors in comparison with the experimental value for all four drugs.
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