Let’s face it, relying on clinical trial participants to self-report their medication intake isn’t ideal. Lots of things can go wrong. Patients can administer medication improperly, avoid taking the medication altogether, or even claim they’ve taken the medication when, in actuality, they haven’t. While there are other means of checking whether patients are taking their medication correctly, such as through various lab tests or breath analysis, they are time-consuming, expensive, and still rely on the subject to participate.
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.
Medication adherence in clinical trials is a big problem for drug companies and can have a devastating effect on their clinical programs. Trials can take longer to run, costing companies significantly more money. They can even fail due to poor adherence.
What if there were a way to accurately and automatically track and report that data through your electronic data capture system (EDC), without asking patients to do anything cumbersome? Well, there is.
Proteus Digital Health and Oracle have teamed up to improve the way companies run trials, hopefully resulting in higher trial success rates. Proteus has created ingestible sensors that go into the medicine that subjects take. Once inside the stomach, the sensors send signals to an exterior patch worn by subjects, to mobile phone apps, and – most importantly – to one of Oracle’s EDC systems, InForm, allowing accurate data to be reported back to the sponsor.
The combination of these digital pills and Oracle’s EDC solution can help identify protocol deviations, improve dosage recommendations, and ultimately making trials safer for the patient population.
To read Oracle’s official press release announcing Proteus’ integration with InForm, click here.