07/23/2026  |  Marianne Kolbasuk McGee   |  Bank Info Security

https://www.bankinfosecurity.com/how-purpose-built-ai-speed-up-clinical-trials-a-32312 

Amber Hill, CEO of Research Grid, on Safely Overcoming Clinical Trial Bottlenecks

Clinical trial teams lose time to patient sourcing, site selection, manual data entry and other back-office tasks. But purpose-built artificial intelligence tools can automate administrative work, improve data quality and help promising treatments reach patients faster, said Amber Hill, founder and CEO of Research Grid.

Safe clinical AI requires purpose-built models, full traceability and checkpoints that keep humans in the loop. Research Grid, which provides AI-powered automation tools, develops its models in house to address specific clinical trial bottlenecks, rather than trying to "retrofit" or put a "wrapper" around more generalized AI, such as OpenAI models, she said.

Its systems also check patient anonymization, missing answers and inconsistent data before auditors review the results.

"Something that would take six months to a year for a research team to accomplish, we can do it in a matter of seconds," Hill said.

Research Grid applies natural language processing, optical character recognition, computer vision and large language models across the end-to-end clinical trial life cycle. Its tools and services support site feasibility, patient sourcing, data capture and study closeout, she said.

"Oftentimes these are small research clinical trial teams that have quite a huge load on them, and they are manually or via tablet, putting in very critical information and data from patients," she said.

"Each thing needs to be connected, in a way that it's not currently in legacy systems. So, a unified system, end-to-end, is able to speed up clinical trials quite significantly and ultimately bring medicine to patients and the people that need it the most - faster."

In this video interview with ISMG, Hill also discussed:

• How AI can automate patient sourcing, site selection and clinical data capture;
• Why traceable, auditable models reduce the risks associated with black-box AI;
• How access controls, anonymization and encryption protect patient information and intellectual property.

Hill is founder and CEO of Research Grid, an AI clinical trial automation company serving pharmaceutical firms, biotechnology companies, contract research organizations and research sites. Hill, who holds a doctorate and has a background in biomedical neuroscience and AI, has led clinical trials and research engagement at institutions including Harvard and MIT. Prior to founding Research Grid, she also established a global nonprofit supporting patient involvement in research.