Clinical trials are expensive. If study costs continue to rise at the current pace, clinical trials to establish efficacy and tolerability will become impossible to conduct, with these potential consequences: making drugs unavailable for areas of unmet need, stifling innovation in established treatment areas, or placing an extreme price burden on consumers and health care systems.
People have suggested many innovations and ways to streamline the development process and improve the likelihood of clinical and regulatory success. For example, adaptive design methodologies allow you to stop a clinical trial early if there is overwhelming efficacy or excess toxicity, or when the novel compound has little chance to distinguish itself from control. Extensive modeling and simulation exercises can suggest the most successful path forward in a clinical program based on the available data and reasonable assumptions based on past development. Patient enrichment based on genomic markers can help select a study population more likely to receive benefit from the drug, resulting in smaller clinical trials.
Other innovations have more to do with the operational aspects of clinical trials. These include electronic case report forms (eCRFs), new technologies for collecting diary data or obtaining laboratory samples, or new software that enables the efficient review of data for quality and safety purposes. And still other innovations involve the regulatory submission and review process through electronic submissions and data standards.
Despite these many advances and innovations, costs continue to rise in many instances. One area for obvious improvement involves how sponsors review trial data. Traditional interpretation of international guidance documents has led to extensive on-site monitoring, including 100 percent source data verification. The cost of these activities is estimated at up to a third of the entire study! This substantial expense has led the industry and numerous regulatory authorities to question the value of traditional approaches.
This book shows how you can use the combination of statistics, graphics and data standards to take a proactive approach to data quality. Numerous examples illustrate the various techniques available within JMP Clinical. Further, I show how you can use JMP add-ins to extend and customize the present capabilities. It will be available in July as a black-and-white print book or full-color e-book. Makes a great gift for everyone on the trial team.