Analyzing -omics requires a wide range of expertise, from bioinformatics to statistical experimental design and data analysis. Having experts in multi-omics and clinical data statistical analysis on your team is critical to a project’s success. With BioRankings® you get collaborative, specialized biostatistical consultants with a focus on -omics analytics and methods.
Moving a product through the FDA requires a high level of statistical rigor to prove your hypothesis. The FDA will not accept ad hoc analyses as evidence of clinical utility. A statistical analysis plan designed before the first sample is collected that specifies statistical tests to be performed is essential to convince the FDA of trial success. At BioRankings, we do -omics based study design and formal hypothesis testing with FDA approval in mind.
Since the beginning of the Human Microbiome Project, BioRankings® statisticians and software engineers have been at the forefront for developing statistical methods, analyzing data, and developing software. This includes the first paper formally exploring sample size and power calculations for microbiome studies.
> STATISTICAL ANALYSIS PLANS AND STUDY DESIGN
A statistical analysis plan helps your team define the goals of your study. A good statistical analysis plan has clear, testable hypotheses with defined statistical tests and sample size calculations. With a strong statistical analysis plan at the start of your study, you can be sure you are sufficiently powered to discover the true signal in the data while avoiding wasting time and money on underpowered or overpowered studies. We help clients design and optimize clinical trials based on budget, required sample sizes, and goals.
> DATA ANALYSIS
When it is time to move forward into statistical analysis, it helps to have a partner that understands the nuances of -omics data analytics. BioRankings uses multidisciplinary approaches, drawing from a wide range of fields including statistics, machine learning, graph theory, mathematics, and computer science. In analyzing data, our toolbox includes biostatistical methods, probability theory, decision theory, and distributional assumptions.
> STATISTICAL METHODS DEVELOPMENT
When no methods exist for your data analysis it takes an expert to define the problem and find a solution, while avoiding false results. BioRankings staff has extensive expertise and excellent track record in inventing, testing, and implementing novel statistical methods. By applying rigorous statistical testing of algorithms before they are used with your data, you are guaranteed only validated analytical tools will be used in analysis. As an open-source company, BioRankings also provides all custom R code used.
> CLINICAL TRIAL PIPELINE STRATEGY
Making decisions on which products or treatments to devote time and resources to can be a challenge, especially without a clear picture of the possible limitations of past and current clinical trials. BioRankings uses your current trial data and the publicly available data from comparable studies to design and run Monte Carlo simulations to help with decision making.