Safety Assessment of a Hemp Extract using Genotoxicity and Oral Repeat-Dose Toxicity Studies in Sprague-Dawley Rats

Dziwenka, Margitta; Coppock, Robert; Alexander, McCorkle; Palumbo, Eddie; Ramirez, Carlos; Lermer, Stephen

Mean and standard deviations were calculated for all quantitative data. For all in-life endpoints that were identified as multiple measurements of continuous data over time (e.g. body weight, body weight gain, food consumption, and food efficiency), treatment and control groups were compared using a two-way analysis of variance (ANOVA), testing the effects of both time and treatment, with methods accounting for repeated measures in one independent variable [17] . Significant interactions observed between treatment and time, as well as main effects, were further analyzed by a post hoc multiple comparisons test; e.g. Dunnett's test [18, 19] of the individual treated groups to control. When warranted by sufficient group sizes, all endpoints with single measurements of continuous data within groups (e.g., organ weight and relative organ weight) were evaluated for homogeneity of variances [20] and normality [21] . Where homogeneous variances and normal distribution was observed, treated and control groups were compared using a one-way ANOVA. When one-way ANOVA was significant, a comparison of the treated groups to control was performed with a multiple comparisons test, e.g., Dunnett's test [18, 19] . Where variance was considered significantly different, groups were compared using a nonparametric method, e.g., Kruskal-Wallis non-parametric analysis of variance [22] . When non-parametric analysis of variance was significant, a comparison of treated groups to control was performed, e.g., Dunn's test [23] . Significance was a probability value of p < 0.05.