Showing papers by "Ivanka Tsakovska published in 2005"

The Characterisation of (Quantitative) Structure-Activity Relationships: Preliminary Guidance

Abstract: In November 2004, the OECD Member Countries and the European Commission adopted five principles for the validation of (quantitative) structure-activity relationships ([Q]SARs) intended for use in the regulatory assessment of chemicals. International agreement on a set of valdation principles was important, not only to provide regulatory bodies with a scientific basis for making decisions on the acceptability of data generated by (Q)SARs, but also to promote the mutual acceptance of (Q)SAR models by improving the transparency and consistency of (Q)SAR reporting. According to the OECD Principles for (Q)SAR validation, a (Q)SAR model that is proposed for regulatory use should be associated with five types of information: 1) a defined endpoint; 2) an unambiguous algorithm; 3) a defined domain of applicability; 4) appropriate measures of goodness-of-fit, robustness and predictivity; and 5) a mechanistic interpretation, if possible. Taken together, these five principles form the basis of a conceptual framework for characterising (Q)SAR models, and of reporting formats for describing the model characteristics in a transparent manner. Under the proposed REACH legislation in the EU, there are provisions for the use of estimated data generated by (Q)SARs, both as a substitute for experimental data, and as a supplement to experimental data in weight-of-evidence approaches. It is foreseen that (Q)SARs will be used for the three main regulatory goals of hazard assessment, risk assessment and PBT/vPvB assessment. In the Registration process under REACH, the registrant will be able to use (Q)SAR data in the registration dossier provided that adequate documentation is provided to argue for the validity of the model(s) used. This report provides preliminary guidance on how to characterise (Q)SARs according to the OECD validation principles. It is emphasised that the understanding of how to characterise (Q)SAR models is evolving, and that the content of the current report reflects the understanding and perspectives of the authors at the time of writing (November 2005). It is therefore likely that an update will be produced in the future for the benefit of those who need to submit (Industry) or evaluate (Authorities) chemical information based (partly) on (Q)SARs. It is also noted that this document does not provide guidance on the use of (Q)SAR reporting formats, or on criteria for the acceptance of (Q)SAR estimates, since EU guidance on these topics stills need to be developed.

Interactions of poly(vinylpyrrolidone) with ibuprofen and naproxen: experimental and modeling studies.

Abstract: Purpose. To elucidate the differences in the interaction of chiralic ibuprofen (IBP) and naproxen (NAP) with poly(vinylpyrrolidone) (PVP) in a solid state.

Molecular Modeling of P-Glycoprotein and Related Drugs

Abstract: This paper summarizes the results from molecular modeling of various multidrug resistance (MDR) modulators and the MDR protein P-glycoprotein (P-gp). Highly predictive 3D-QSAR models are obtained that can be used for anti-MDR activity prediction. The pharmacophore patterns of various drugs are identified. Models of P-gp are developed and a hypothesis for P-gp functioning is proposed.