Disruptive technology in clinical trials

I like the style of presentations, the cutting edge presentations and opening with inspirational stories. Great event, growing attendance, and more importantly increasing quality. I found the event quite inclusive. Thank you for making this a valuable learning experience. It was a pleasure working with each of you. It was a great experience. It was my first time at DPharm and prior to my attendance, I was working on innovation related to the way we design clinical trials.

I recall being absolutely amazed by the spirit of collaboration. After the conference was over, I spent my Saturday connecting with speakers and attendees on Linkedin, thinking: I want to be part of this community! Two years later, my dream came true I come back to find respected colleagues that became friends and collaborations, to exchange ideas and learn from each other! September , Boston, MA Questions? Most of the innovation occurs in the sensors used in the continuous data collection process.

As such, new and custom sensors are beginning to emerge, designed for specific purposes. Dash from Bragi , for example, is a hearing aid that also features over fifteen sensors, tracking things like heart rate, respiration, oxygen saturation, and more. Plans include the development of contact lenses with sensors capable of measuring biometric data such as glucose levels. As sensors evolve, become cheaper and more readily combinable, the range and sophistication of applications is sure to expand, allowing us to combine them in ways we never thought possible.

With this kind of data available from potentially millions of patients, what impact will this have on how data is collected and analyzed? Will we have remote clinical trials relying on both electronic patient reported information, as well as, sensor-derived data that is collected automatically 24x7, leveraging the power of a mobile platform without the need for costly infrastructure?

Can we identify adverse events remotely and in real-time by using sensors? How will the advent of data sensors impact patient recruitment in clinical trials, including concerns about data privacy? The possibilities, while exciting, carry a mind boggling number of implications for the regulatory authorities and companies conducting clinical research, such as but not limited to EDC, eTMF, study participation and follow up.

Moving beyond sensors, wearable devices go beyond passive data collection and use the information about the individual to help them make decisions or change behavior to produce a desired result.

Veristride is working on making inserts for shoes that can help stroke victims improve their walking. Quell offers an FDA-approved device that stimulates the brain to block pain receptors for patients with chronic conditions.

The device is worn around the calf in a neoprene wrap. In the future will we consider running clinical trials for pain with and without such devices?

Will we recruit new patient populations into clinical trials by targeting users of certain wearable devices and their apps? As the proliferation of big data continues, from DNA sequencing to EHRs and imaging data, multi-faceted data transformation and analysis has become the next big challenge in research and clinical development.

Bioinformatics continues to face challenges in integrating molecular biological data with patient information in the quest to accelerate the discovery of useful new therapies. Introduction 2. Framing the Problem 3. Models for Public Engagement 5. Messages and Methods for Public Engagement 6. The Media 7.