Abstract Background: Preclinical studies, the first stage of the drug development process, must always have proper planning, execution, analysis and reporting in order to preserve scientific integrity. The decision to advance to human clinical trials depends heavily on results of these studies. For To facilitateing in vivo pharmacology data analysis and interpretation, we developed a web platform (HuPharm) that automates statistical pipelines and report generation. Its intuitive and interactive interface will greatly help researchers, who more often than not are non-statisticians, on data validation, exploratory data analysis and statistical analysis. Methods: We use RStudio’s shiny package to build an interactive web application (HuPharm), and we use knitr and rmarkdown packages to generate a highly informative data analysis report. HuPharm is deployed on the web using Shinyapps.io developed by RStudio. Based on the distribution of input data, HuPharm will automatically performs parametric tests such as ANOVA and Welch’s t-test or non-parametric tests such as Kruskal-Wallis test and Mann-Whitney U test. Additionally, HuPharm is capable of conducting survival analysis, including both non-parametric Kaplan-Meier analysis and Ccox regression. Aside from classical tests, we have also implemented a number of state-of-the-art analytics on HuPharm, such as multilevel/hierarchical linear models, frailty analysis and joint modeling of longitudinal and survival data. Last by not the least, power analysis module in HuPharm can help researchers with their study design by power and sample size calculation. Results: Based upon user inputs, HuPharm will dynamically generate a series of tables and figures to facilitate preclinical data analysis, such as tumor volume summary statistic table and plots, tumor growth curves, omnibus group comparison plots, all pairwise group comparison table and post hoc analysis results table. In addition, HuPharm can generate one nicely formatted study report including all those aforementioned figures and tables in both html and pdf format. Powered by shiny server’s interactive design, users can easily adjust the parameters to explore their data in a highly flexible and responsive way. Conclusions: HuPharm is a convenient and powerful tool to aid researchers in the field of preclinical trials studies for their study design and data analysis. It will help to add rigor and improve the quality of preclinical studies. Citation Format: Binchen Mao, Sheng Guol, Qixiang Li. HuPharm: An interactive data analysis platform for preclinical studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 5111.