Abstract | OBJECTIVE: METHODS: Data on the time course of the antinociceptive and respiratory depressant effect were analyzed on the basis of population logistic regression PK-PD models using non-linear mixed effects modeling software (NONMEM). The pharmacokinetics of buprenorphine and fentanyl were described by a three- and two-compartment model, respectively. A logistic regression model (linear logit model) was used to characterize the relationship between drug exposure and the binary effectiveness and safety outcome. RESULTS: For buprenorphine, the odds ratios (OR) were 28.5 (95% CI, 6.9-50.1) and 2.10 (95% CI, 0.71-3.49) for the antinociceptive and respiratory depressant effect, respectively. For fentanyl these odds ratios were 3.03 (95% CI, 1.87-4.21) and 2.54 (95% CI, 1.26-3.82), respectively. CONCLUSION:
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Authors | Ashraf Yassen, Erik Olofsen, Jingmin Kan, Albert Dahan, Meindert Danhof |
Journal | Pharmaceutical research
(Pharm Res)
Vol. 25
Issue 1
Pg. 183-93
(Jan 2008)
ISSN: 0724-8741 [Print] United States |
PMID | 17914664
(Publication Type: Journal Article)
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Chemical References |
- Narcotic Antagonists
- Buprenorphine
- Fentanyl
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Topics |
- Algorithms
- Animals
- Buprenorphine
(adverse effects, pharmacokinetics, pharmacology)
- Depression, Chemical
- Fentanyl
(adverse effects, pharmacokinetics, pharmacology)
- Linear Models
- Logistic Models
- Male
- Models, Statistical
- Narcotic Antagonists
(adverse effects, pharmacokinetics, pharmacology)
- Odds Ratio
- Pain Measurement
(drug effects)
- Plethysmography, Whole Body
- Rats
- Rats, Wistar
- Regression Analysis
- Respiratory Function Tests
- Respiratory Mechanics
(drug effects)
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