Faiola B.,Rti International |
Faiola B.,Glaxosmithkline |
Peterson R.A.,Glaxosmithkline |
Kimbrough C.L.,Statistical Science |
And 2 more authors.
The innate immune response is known to modify hepatocellular injury induced by toxicants. To assess the role of IL-10, a component of the innate immune response, in toxicant-induced injury of biliary epithelium, wild-type (WT) and IL-10 knockout mice (KO) were given a single toxic dose (50 mg/kg) of ±-napthylisothiocyanate (ANIT) and assessed at twenty-four-hour intervals for four days following treatment. Clinical signs of toxicity were greater in WT mice. Unexpectedly, over the course of the study, there was a consistent tendency for ANIT-treated IL-10 KO mice to have less hepatocellular injury than WT mice. However, changes in the biliary epithelium differed in that there was more histologic evidence of inflammation and necrosis on days 2 and 3, respectively, in ANIT-treated IL-10 KO mice compared with WT mice. Proliferation of biliary epithelium and hepatocytes was greater and/or occurred earlier in the ANIT-treated IL-10 KO mice compared with the ANIT-treated WT mice, suggesting a greater reparative response was needed for recovery after toxicant injury in the IL-10 KO mice. Overall, our data suggest that IL-10 KO mice have less hepatocellular injury than WT mice following a toxic dose of ANIT and that biliary epithelial injury is accentuated in the KO mice. Copyright © 2010 by The Author(s). Source
Uryniak T.,Astrazeneca |
Chan I.S.F.,Merck And Co. |
Fedorov V.V.,Glaxosmithkline |
Jiang Q.,Amgen |
And 4 more authors.
Statistics in Biopharmaceutical Research
Ideally, a clinical trial should be able to demonstrate not only a statistically significant improvement in the primary efficacy endpoint, but also that the magnitude of the effect is clinically relevant. One approach to address this question, often proposed by clinical societies and regulatory guidance, is a responder analysis, in which a continuous primary efficacy measure is dichotomized into "responders" and "nonresponders." This article represents a Pharmaceutical Research and Manufacturers of America (PhRMA) position on responder analyses. With respect to demonstration of the existence of a treatment effect, we find that the well-known loss of statistical power associated with a responder analysis outweighs any real or perceived benefits of this approach. However, between-group comparisons of the percentages of "responders" can play a role in the assessment and reporting of the clinical meaningfulness of the treatment effect. © American Statistical Association Statistics in Biopharmaceutical Research. Source
Ellens H.,Glaxosmithkline |
Deng S.,Drug Metabolism and Pharmacokinetics |
Coleman J.,Statistical Science |
Bentz J.,Eli Lilly and Company |
And 32 more authors.
Drug Metabolism and Disposition
In the 2012 Food and Drug Administration (FDA) draft guidance on drug-drug interactions (DDIs), a new molecular entity that inhibits Pglycoprotein (P-gp) may need a clinical DDI study with a P-gp substrate such as digoxin when themaximumconcentration of inhibitor at steady state divided by IC50 ([I1]/IC50) is0.1 or concentration of inhibitor based on highest approved dose dissolved in 250 ml divide by IC50 ([I2]/IC 50) is10. In this article, refined criteria are presented, determined by receiver operating characteristic analysis, using IC50 values generated by 23 laboratories. P-gp probe substrates were digoxin for polarized cell-lines and N-methyl quinidine or vinblastine for P-gp overexpressed vesicles. Inhibition of probe substrate transport was evaluated using 15 known P-gp inhibitors. Importantly, the criteria derived in this article take into account variability in IC50 values. Moreover, they are statistically derived based on the highest degree of accuracy in predicting true positive and true negative digoxin DDI results. The refined criteria of [I1]/IC50 0.03 and [I2]/IC50 45 and FDA criteria were applied to a test set of 101 in vitro-in vivo digoxin DDI pairs collated from the literature. The number of false negatives (none predicted but DDI observed) were similar, 10 and 12%, whereas the number of false positives (DDI predicted but not observed) substantially decreased from 51 to 40%, relative to the FDA criteria. On the basis of estimated overall variability in IC50 values, a theoretical 95%confidence interval calculation was developed for single laboratory IC 50 values, translating into a range of [I1]/IC50 and [I2]/IC50 values. The extent by which this range falls above the criteria is a measure of risk associated with the decision, attributable to variability in IC50 values. © 2013 by The American Society for Pharmacology. Source