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AI-Driven Automation: Understanding Its Power to Transform Clinical Research

Recently, THREAD announced its collaboration with Amazon Web Services (AWS) and their combined work to introduce AI-powered enterprise-scale automation into THREAD’s decentralized clinical trial (DCT) platform. There are so many announcements made every day about different corporate collaborations, that it may not immediately be clear what it means that THREAD will be working with AWS. For those involved in conducting clinical trials, it means a significant step forward in efficiency and data quality. Leveraging the power of artificial intelligence, the industry can now take an evolutionary leap in terms of how we run studies, ultimately allowing us to help you run more studies, help more patients gain access to clinical trials as a care option, and speed the journey for new therapies.

How It Works

THREAD and the experts at AWS Professional Services are working together to design a new and advanced machine learning architecture and AI models. These will serve to automate key processes for customers, helping them to quickly build study protocols based on the scope of work agreement, allowing studies to begin faster. Once the study has begun, AI models can be used to auto-populate many data workflows that, previously, would need to be entered manually today. These features can help you improve data accuracy by eliminating opportunities for human error. Overall, you’ll be able to reduce inefficiencies by more than 30% and realize cost savings up to 25%.

Better Experiences Mean Better Data

The most important stakeholders in clinical research will (and should) always be the participants. When we consider any technology or approach, we must first think of how it will impact participants, and when it comes to implementing AI-powered automation, there is nothing but upside in terms of improving our patients’ clinical trial experiences. Specifically, AI and/or machine learning are powerful tools for reducing software or application interface difficulties for participants. Keep in mind, that all participants are different and have widely varying levels of experience with technology. AI and machine learning can help. Similar to the auto-suggest function when you’re typing on your smartphone, THREAD and AWS are developing solutions that help to auto-populate some participant (or caregiver) data entry based on their behaviors and preferences. This alleviates much of the burden on sick patients to constantly log into a system to enter data. For participants with debilitating conditions, these kinds of tasks can be too much work, leading to poor compliance and dropouts.

The Time is Now

Clinical researchers face a long list of pressures. Market pressures, pressure to contain costs, and a wide range of regulatory pressures mean we are all looking for ways to accomplish more with less. For THREAD, this means doing everything in our power to make running clinical trials more efficient and productive for our customers. Working with AWS allows us to give you the power to automate your data collection, storage, and analysis in ways that help you run more studies, more efficiently.

For more information on how to leverage the AWS-powered solution from THREAD for your decentralized clinical trial, contact your THREAD representative to arrange a demo or visit threadresearch.com

Scott Pearson

Chief Product and Technology Officer, THREAD

As THREAD’s Chief Product Officer, Scott is driven to change how clinical research is conducted to accelerate the mature development of lifesaving and life-changing therapies. In his role, Scott helps THREAD to deliver on its 1/5/30 mission to modernize clinical research by offering biopharma and CRO customers one (1) comprehensive platform that is five (5) times more inclusive and makes research 30% more efficient.