Personalizing Digital Health

Digital Health technologies have the potential to address many clinical trial issues – including recruiting and retaining patients, and gathering richer data to drive insights for making better development decisions sooner – all while reducing repetitive manual tasks and the costs and errors that go with them. Such improvements are essential to increasing return on clinical R&D, which, for pharma, fell from 10.1 percent in 2010 to 3.2 percent in 2017, according to Deloitte.

Drug and medical device industry leaders widely regard Digital Health technologies as a way to improve the efficiency of clinical research. In a 2017 ICON-Informa Intelligence survey, pharma executives ranked big data, predictive analytics, smartphones, wearables and sensors as top technology trends likely to have the most impact on increasing clinical trial efficiency.

However, improving clinical R&D efficiency is only one part of the Digital Health revolution. Increasing the efficacy of therapies in the real world, using approaches such as continuous monitoring, telemedicine, apps and software that help patients better manage their conditions, may be even more important.

Already, connected mobile sensors and apps are reminding patients to take medicines as directed, monitoring vital signs to help adjust medicines and alerting clinicians to emergencies. Incorporating artificial intelligence (AI) into such devices could have an even greater impact on helping patients at critical times.