How AI Impacts Clinical Trials Today (And Who's Doing It)

AI tools optimizing healthcare workflows

Last updated: October 10, 2019 5:02AM

It’s easy to get lost in questions concerning the future of AI in clinical trials. How should we be using it? How could it change the healthcare industry? But plenty of applications are already live in the R&D process. Contract research organizations and pharmaceutical companies alike have gone on an AI buying frenzy for years. The birth of AI startups seems to outpace even those acquisitions, with new advances emerging regularly.

The truth is: AI isn’t just coming to disrupt healthcare; it’s already here. Here are some places AI is already stepping into the clinical trial equation.

Using Predictive AI Software For Medical Research

The Internet provides access to virtually endless knowledge. All that information at your fingertips can be both a blessing and a curse—it means many more needles exist in a nearly infinite haystack.

In response to information overload, several healthcare companies have developed versions of AI “study buddies” to help sort through the data. Some of these systems, like the ones from H1 Insights, help with background research.

H1 products examine broad swathes of research divided by therapeutic area, product, or even researcher or thought leader to aggregate useful information. Other companies leverage data mining tools to help predict the likelihood that a patient will have an illness or complication. This is helpful for both preventative medicine and patient stratification for clinical trials.

Using AI For Screening and Connecting Patients

Global connectivity has greatly expanded the potential patient base for research studies and clinical trials. With AI-powered screening tools, researchers and medical professionals can select more ideally-suited individuals for their studies. Stratifying patients and matching patients with doctors and studies is one of the more prominent areas in which AI supports clinical trials.

For example, through its cancer-focused solution, Belong.life provides a series of personalized benefits for cancer patients. It:

Offers patients personalized news streams

Matches potential patients with clinical trials

Helps patients manage documents and connect with peer groups.

Likewise, TrialJectory also matches cancer patients with potential clinical trials, using self-reported medical data. MassiveBio, another cancer-focused AI business, matches patients and clinical trials. It also helps enterprises seeking more patient data.

These are just a few of the many companies that are leveraging AI tools to help support clinical trial matching. Tools like these help everyone: they make the clinical trial process more effective and efficient, help patients receive the right care, and create more specialized, high-quality datasets that can fuel further research.

AI Tools For Workflow Optimization

One company is taking the optimization trend to the clinical trial world. Medable has designed a suite of tools specifically for the clinical trial workflow. These tools help smooth insight-sharing to eliminate data siloes.

In some ways, any operations-focused AI-powered SaaS platform could provide support for clinical trials. Spreadsheet management, site visitor interactions, and similar tools that users can leverage in any industry can find particular resonance in the clinical trial world. Basic productivity tools can benefit operations across medical and scientific fields.

In short: the clinical trial sphere is ripe for AI disruption, across myriad use cases.

Drug Design Using Cloud Computing Technology

At the molecular level, AI can even help propose and test molecules to defend against certain illnesses. Cloud Pharmaceuticals uses cloud based computing to help propose new drug candidates and has already moved some candidates to pre-clinical stages. BioXcel focuses on neurological and immuno-oncological medicines and works similarly, using AI to propose and model ideas. Atomwise focuses on pediatric patients and can virtually test drugs to predict their success in trials.

Each of these advances could have incredibly positive effects for patients.