Artificial Intelligence (AI) technology, combined with big data, hold the potential to solve many key clinical trial challenges.
In our industry survey and whitepaper, 'Improving Pharma R&D Efficiency' when asked what technologies would have the most impact improving clinical trial efficiency, the top answer from survey respondents was leveraging big data and AI at 36 percent.
Indeed Big Data and AI technologies are complimentary as AI can help to synthesize and analyse ever-expanding data. AI-enabled measures include data integration, data management and interpretation.
They make possible innovations that are fundamental for transforming clinical trials, such as seamlessly combining phase I and II of clinical trials, developing novel patient-centered endpoints, and collecting and analysing Real World Data.
In the United States outcomes-based contracting (OBC) has long been proposed as a measure to reward innovation, based on actual performance of treatments and interventions in patient populations. However, the perceived and actual challenges in implementation have prevented many innovative contracts from leaving the drafting table.
Recently, the potential use of artificial intelligence (AI) to predict suitable outcomes for patients to mitigate potential challenges has been discussed. ICON is conducting original research with formulary decision makers and with manufacturers, with the following objectives in mind:
The AI transformation of clinical trials starts with protocol development, reducing or replacing outcome assessments that may be more responsive to change than traditional methods and utilising remote connected technologies that reduce the need for patients to travel long distances for sites visits.
Data-driven protocols and strategies powered by advanced AI algorithms processing data collected from mobile sensors and apps, electronic medical and administrative records, and other sources have the potential to reduce trial costs. They achieve this by improving data quality, increasing patient compliance & retention, and identifying treatment efficacy more efficiently and reliably than ever before.
As the availability of big data continues to grow exponentially, new technologies to process these data sets have become available. These include Artificial Intelligence (AI), Machine Learning and Natural Language Processing (NLP).
What are their differences, what operational processes do they perform and what are the advantages of implementing these innovative technologies in a centralized and secure RWE technology platform? Read our blog to learn more.Read blog
ICON and Intel Corporation have formed an agreement to enable ICON to offer the Intel® Pharma Analytics Platform for use in clinical trials. The Intel platform is an edge-to-cloud artificial intelligence (AI) solution that enables remote monitoring and continuous capture of clinical data from study subjects using sensors and wearable devices, and can apply machine learning techniques to objectively measure symptoms and quantify the impact of therapies.
ICON and Intel have collaborated on thought leadership on the use of AI and wearables in clinical trials:
On-demand webinar: The template for a successful digital trial
In addition to the rise in mobile and wearable solutions, AI powered digital voice assistants are becoming ubiquitous, with every smartphone today now shipping with either Siri or Google Assistant, while smart speakers like the Amazon Echo with Alexa and Google Home are becoming the hubs for smart homes.
Voice Assistant technologies provide an opportunity to create a different level of engagement and interaction with patients in comparison to regular apps and web pages. ICON have developed a proof-of-concept application operating on the Amazon Echo platform that leverages a Voice Assistant to deliver a patient-reported outcome instrument and collect patient responses.