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Titolo:
Case studies of categorical data-derived adjustment factors
Autore:
Naumann, BD; Silverman, KC; Dixit, R; Faria, EC; Sargent, EV;
Indirizzi:
Merck & Co Inc, Whitehouse Stn, NJ 08889 USA Merck & Co Inc Whitehouse Stn NJ USA 08889 , Whitehouse Stn, NJ 08889 USA Merck Res Labs, W Point, PA 19486 USA Merck Res Labs W Point PA USA 19486Merck Res Labs, W Point, PA 19486 USA
Titolo Testata:
HUMAN AND ECOLOGICAL RISK ASSESSMENT
fascicolo: 1, volume: 7, anno: 2001,
pagine: 61 - 105
SICI:
1080-7039(200102)7:1<61:CSOCDA>2.0.ZU;2-J
Fonte:
ISI
Lingua:
ENG
Soggetto:
CONVERTING-ENZYME-INHIBITORS; NONSTEROIDAL ANTIINFLAMMATORY DRUGS; COA REDUCTASE INHIBITORS; CHRONIC-RENAL-FAILURE; AMBULATORY PERITONEAL-DIALYSIS; STEADY-STATE PHARMACOKINETICS; SEROTONIN REUPTAKE INHIBITORS; OCCUPATIONAL EXPOSURE LIMITS; CONGESTIVE-HEART-FAILURE; ANTI-INFLAMMATORY DRUGS;
Keywords:
acceptable daily intake; occupational exposure limit; reference dose; tolerable intake; toxicokinetics; toxicodynamics; risk assessment; safety factors; uncertainty factors;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Agriculture,Biology & Environmental Sciences
Citazioni:
155
Recensione:
Indirizzi per estratti:
Indirizzo: Naumann, BD Merck & Co Inc, Whitehouse Stn, NJ 08889 USA Merck & Co Inc Whitehouse Stn NJ USA 08889 Stn, NJ 08889 USA
Citazione:
B.D. Naumann et al., "Case studies of categorical data-derived adjustment factors", HUM ECOL R, 7(1), 2001, pp. 61-105

Abstract

Investigations were performed on representative compounds from five different therapeutic classes to evaluate the use of categorical data-derived adjustment factors to account for interindividual variability. The five classes included antidepressants, angiotensin converting enzyme (ACE) inhibitors,nonsteroidal anti-inflammatory drugs (NSAIDS), cholesterol lowering agents, and antibiotics. Each of the case studies summarized the mode of action of the class responsible for both the therapeutic and adverse effects and the key pharmacodynamic (PD) and pharmacokinetic (PK) parameters that determine the likelihood of these responses for individual compounds in the class. For each class, an attempt was made to identify the key factors that determine interindividual variability and whether there was a common basis to establish a categorical default adjustment factor that could be applied across the class (or at least across specific subclasses within the class). Linking the PI( and PD parameters to the critical endpoint used to establish a safe level of exposure was an important underlying theme throughout the investigations. Despite the wealth of PK and PD information in the published literature on the surrogate compounds representing these classes, it was difficult to derive a categorical adjustment factor that could be applied broadly within each class. The amount of information available may have hindered rather than helped the evaluations. Derivation of categorical defaults for different classes of "common" chemicals may be more straightforward if sufficient data are available. In a few cases (e.g., tricyclic antibiotics, ACE inhibitors and selected antiinflammatory agents) categorical defaults could be proposed, although it is unclear whether the reduction in uncertainty resulting from their application would be offset by the additional uncertainties that may have resulted from their application. Residual uncertainties may remain depending on the level of confidence in the underlying assumptions used to support the categorical defaults. Regardless of the conclusions on the utility of categorical defaults, these investigations provided further support for the use of data-derived adjustment factors on a compound-specific basis.

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Documento generato il 21/10/20 alle ore 10:47:45