Getting informed consent from patients is one of the most critical aspects of a clinical trial. The objective is simple: provide patients with information about the study plan (doctor visits, tests, etc.) and risks/benefits, make sure they understand the information, and get their (legally effective) consent to participate. The faster this is done, the faster the patient can enroll in the trial.
This guide analyzes how artificial intelligence – including machine learning – can be used by pharmaceutical and medical device companies to improve the clinical data review and cleansing process.
Historically speaking, this process was always completed in person. You’d hand someone paper literature to read, answer any questions he or she might have, and get their handwritten signature. Now that clinical trials are carried out all over the globe (some are even conducted 100% remotely!), companies are looking for new ways to leverage technology to streamline the informed consent process without compromising compliance.
Thankfully, the FDA is sympathetic to the industry’s plight, so, earlier this month, they published a new draft guidance document on the topic: Use of Electronic Informed Consent in Clinical Investigations. The guidance aims to help companies leverage technologies, such as websites, video conferencing (e.g., Skype), text messaging, and even electronic signatures in support of informed consent, while still complying with the existing regulations (which have not changed).
Guidance documents are not legally binding; they contain “nonbinding recommendations” that are simply meant to help us understand how to adapt new circumstances to existing regulations. As a bonus, this new draft guidance document is open for public comments until May 8, 2015. If you want to influence its content, you can provide your feedback here.
If you have questions about the new guidance document or the existing regulations, feel free to contact us.