Using (Quantitative) Structure-Activity Relationships in Pharmaceutical Risk Assessment
Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research › peer-review
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Pharmaceuticals in the Environment: Sources, Fate, Effects and Risks. ed. / Klaus Kümmerer. 2. ed. Berlin: Springer, 2004. p. 387-390.
Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research › peer-review
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TY - CHAP
T1 - Using (Quantitative) Structure-Activity Relationships in Pharmaceutical Risk Assessment
AU - Kümmerer, Klaus
PY - 2004/1/1
Y1 - 2004/1/1
N2 - Sound risk assessment depends on the availability of sufficient good quality data. To remove the shortcomings of experimental testing, for some time, attempts have been made to reduce the amount of money and time it requires. One option is to correlate the structure of a chemical or parts of its structure with a certain activity or with physicochemical properties (structure-activity relationship = SAR). Computer based expert systems are used for this purpose (“in silico testing”). Such an approach has a comparatively long tradition in the development of new drugs and is an important tool in the drug development process (Kellogg and Semus 2003; Cronin 2003). These systems are used for screening drugs and other chemicals for unwanted side effects (Polloth and Mangelsdorff 1997) and for predicting the physicochemical properties of new compounds such as water solubility and K ow. In the meantime, SAR has become an increasingly important tool in the regulatory process and has now reached the stage where some regulatory agencies such as the US Environmental Protection Agency routinely use QSAR-predicted toxicities as well as environmentally important properties for regulatory purposes (e.g. with the software suite EPISUITE (EPA 2001) which can be downloaded free of charge from the US EPA homepage). It is anticipated that such use will increase in future. The EU will probably accord QSARs greater prominence in the new technical guidance documents which form the basis for risk assessment. There is a good deal of literature describing the application and evaluation of QSAR software in ecotoxicology (for a overview: ECETOC 1998; ECVAM 1997; Boethling and Mackay 2000; Dearden 2002).
AB - Sound risk assessment depends on the availability of sufficient good quality data. To remove the shortcomings of experimental testing, for some time, attempts have been made to reduce the amount of money and time it requires. One option is to correlate the structure of a chemical or parts of its structure with a certain activity or with physicochemical properties (structure-activity relationship = SAR). Computer based expert systems are used for this purpose (“in silico testing”). Such an approach has a comparatively long tradition in the development of new drugs and is an important tool in the drug development process (Kellogg and Semus 2003; Cronin 2003). These systems are used for screening drugs and other chemicals for unwanted side effects (Polloth and Mangelsdorff 1997) and for predicting the physicochemical properties of new compounds such as water solubility and K ow. In the meantime, SAR has become an increasingly important tool in the regulatory process and has now reached the stage where some regulatory agencies such as the US Environmental Protection Agency routinely use QSAR-predicted toxicities as well as environmentally important properties for regulatory purposes (e.g. with the software suite EPISUITE (EPA 2001) which can be downloaded free of charge from the US EPA homepage). It is anticipated that such use will increase in future. The EU will probably accord QSARs greater prominence in the new technical guidance documents which form the basis for risk assessment. There is a good deal of literature describing the application and evaluation of QSAR software in ecotoxicology (for a overview: ECETOC 1998; ECVAM 1997; Boethling and Mackay 2000; Dearden 2002).
KW - Chemistry
KW - Quantitative Structure Activity Relationship Model
KW - Quantitative Structure Property Relationship
KW - Drug Development Process
KW - Anaerobic Biodegradation
KW - Aerobic Biodegradation
UR - https://www.mendeley.com/catalogue/50796acb-d4bc-37b6-9895-0b6223b0c7af/
U2 - 10.1007/978-3-662-09259-0_28
DO - 10.1007/978-3-662-09259-0_28
M3 - Contributions to collected editions/anthologies
SN - 3-540-21342-2
SN - 978-3-662-09261-3
SP - 387
EP - 390
BT - Pharmaceuticals in the Environment
A2 - Kümmerer, Klaus
PB - Springer
CY - Berlin
ER -