In clinical research, time isn’t just money – it’s hope. And in many cases, it’s survival. Every delay in getting a clinical trial off the ground means patients wait longer for potentially life-saving treatments. One of the biggest culprits behind these delays? Contracts.

Florence Healthcare recently hosted a powerful webinar featuring Catherine Gregor, Chief Clinical Trial Officer at Florence; Tara Rabe, Research Administrator at Mayo Clinic; and Jim Wagner, CEO and Co-Founder of The Contract Network. Their conversation revealed how AI is not just streamlining contracts – but transforming clinical trial timelines and, by extension, patient outcomes.

The Contract Bottleneck: A Known Villain

Clinical trial agreements (CTAs) are infamous for dragging down startup timelines. “Besides IRB and regulatory approvals, contracts were always a major contributor to delays,” Catherine shared. With manual processes and backlogs exacerbated by workforce constraints, the industry average negotiation time now tops 90 days – second only to nuclear energy agreements, according to recent reports.

For Tara at Mayo Clinic, the situation was even more dire. “There was a time where it would take us six to nine months to negotiate a CTA,” she admitted. “That’s embarrassing.” With over 6,500 agreements per year and a lean team, something had to give.

Fixing the Foundation First

Before jumping into automation or AI, Tara’s team had to overhaul their entire process. “You cannot automate a broken process,” she stressed. The team realigned their workflows so that IRB, budget, and contracts began simultaneously rather than sequentially. They fostered collaboration across departments, improved visibility into bottlenecks, and leveraged master agreements and ACTA templates where possible.

Only once their processes were optimized did they bring in AI.

“Humans plus AI deliver better results.” – Tara Rabe, Research Administrator at Mayo Clinic

Enter AI: A Game-Changer for Clinical Contracts

With The Contract Network, Tara’s team set bold goals: reduce CTA review times by 25% by mid-2025, and hit a 50% reduction by the end of that year. They achieved the latter in just four months.

Using AI, Mayo now automates redlines, identifies past precedent agreements in seconds, and provides new staff with guided learning based on real-world examples. Negotiators no longer start from scratch; they start from insight.

And it’s working. “We went from six to nine months per CTA to 25 days,” Tara shared. “And I still think we can do better.”

It’s Not About Replacing Humans – It’s About Empowering Them

The fear that AI might replace jobs surfaced early in the process. “There was a lot of concern: ‘Is this going to take over my job?’” Tara recalled. But the results proved otherwise. AI took care of the repetitive, low-value tasks, allowing experts to focus on what really matters: critical clauses like subject injury and indemnification.

As Jim noted, “Humans plus AI deliver better results.” And better still, staff embraced the change. In a recent internal survey, 71% reported saving one to three hours per agreement.

“There’s a patient on the end of these agreements.” Tara Rabe, Research Administrator at Mayo Clinic

The Emotional Payoff: Saving Time, Saving Lives

While speed and efficiency are great KPIs, the real impact is measured in lives. Tara shared a moving email from a principal investigator who was able to enroll a patient in a critical trial thanks to the faster contracting timeline. “This is really my why,” she said, visibly emotional. “There’s a patient on the other end of these agreements.”

That patient would have missed their opportunity in a six-month contract cycle. In a 25-day one? They got their chance.

The Takeaway: Process First, Then Technology, Then Transformation

For organizations eyeing AI for clinical trial operations, the message is clear: fix your processes first. Then invest in the right tools. And don’t forget the human side—both the teams using the tech and the patients waiting for the results.

As Catherine summed it up, “Even if you never touch a patient, the work that you do will touch a patient. That’s what keeps us going.”