Clinical trials are complex projects, whether it is a late phase study involving hundreds of individuals and spanning multiple years and centres, or a smaller early phase study. To ensure a successful trial, Sponsors need to carefully and precisely define all aspects of their trial, and this is where Datapharm’s expertise is vital.
Before the trial starts, a significant amount of statistical work is required, such as selecting a scientifically defensible study design. Datapharm has experience with many designs, including parallel, Bayesian adaptive, crossover and factorial designs. We include this information in your study protocol, a document we write in close collaboration with your pharmaceutical and clinical experts.
Also included in the protocol is the sample size of your study, which needs to be carefully determined and justified. Datapharm’s expertise is invaluable in calculating the sample size, to consider the competing interests of detecting a significant outcome against the research time, patient effort, and study costs that are required for a larger trial.
Another document written early in the clinical trial timeline is the statistical analysis plan (SAP), and Datapharm writes this to ensure as smooth a clinical trial experience as possible and compliance with ICH guidelines, with minimisation of bias. The SAP details analysis populations, primary and secondary endpoints, interim analyses, statistical tests, tables, figures, and more.
Finally, before a study can proceed, randomisation lists must be generated. Randomisation can be as simple or complex as the study requires, but if any sentinel groups, subgroup analyses, covariates, confounding subject factors, or expected recruitment biases exist, your randomisation must account for this to minimise their impact on the analysis. Our experienced statisticians and programmers are well-versed in this area, including using electronic data capture systems to automatically assign randomisation IDs based on the screening characteristics of a subject for complex randomisations.
