Why Payment Performance Has Become an Operational Brand for Sponsors: Q&A with Patrick Mizer, Ledger Run

As experienced investigative sites gain more study opportunities than they can realistically support, sponsors are discovering that the quality of their financial operations has become as important as the science behind their programs.

To explore this further, Applied Clinical Trials recently chatted with Patrick Mizer, chief technology officer at Ledger Run, about what is driving payment inconsistency across the clinical trial ecosystem, how agentic artificial intelligence (AI) is beginning to reduce the manual burden of invoice processing, and why with 80% of sites operating on six months or less of cash, fixing the payment infrastructure is no longer optional.

ACT: How has the payment experience become a competitive differentiator for sponsors in an environment where qualified sites are becoming more scarce?

Mizer: Clinical research has shifted from a world where sponsors competed primarily for patients to one where competing for high-performing investigative sites has become a competitive advantage. Experienced sites have more study opportunities than they can realistically support, and that gives them greater influence over which sponsors they prioritize.

What we've found—and what's helped Ledger Run find a niche in this space—is that delayed and inaccurate payments create cash flow challenges for sites, increase administrative overhead, and erode confidence in the sponsor relationship. What I've been told time and time again is that sites remember where they had good experiences and are more likely to prioritize studies from sponsors with a reputation for predictable financial operations. In that sense, payment performance has become something of an operational brand for larger sponsors and CROs. Startup speed, lack of payment delays, and operational excellence are increasingly a way to compete on the ease of doing business with clinical sites.

ACT: What are the real drivers behind payment inconsistency, and why have challenges like fragmented contracts, outdated benchmarks, and opaque reconciliation persisted for so long?

Mizer: This area of clinical operations—specifically site payments—has not had the investment that other areas have had. The payment process today reflects decades of incremental growth rather than intentional design. Organizations are still managing study budgets, contracts, CTMS platforms, EDC systems, and financial systems as separate, disjointed workflows, each introducing its own assumptions, manual processes, and disconnected teams.

The results are that budget negotiations are frequently based on historical precedent rather than current market data, contract language varies substantially across studies and sponsors, and amendments add additional complexity into the study life cycle. Being relatively new to this space—though not to technology—what strikes me is that the industry has historically accepted this level of complexity because the operational pain was distributed across sponsors, CROs, and sites rather than concentrated in one specific place.

ACT: Where is AI being applied to the high-friction parts of trial payments, and what does meaningful improvement actually look like?

Mizer: I've been applying technology to hard problems for the better part of 25 years, and I've been somewhat of a skeptic about how AI is going to change things. I've said before that I'm old enough to remember the .com boom—I think we're in something like the pets.com era of AI, where it's certainly going to change everything, but we're not exactly sure how yet.

That said, AI does have specific places where, in its current state, it can drive real value. And somewhat fortunately, a lot of the workflows within clinical ops and site payments fit really well in what AI is actually good at—what I'd call feigning reasoning, somewhat low-level reasoning that human beings can do, but with an expert able to oversee and QC the process, which mitigates hallucinations.

At Ledger Run, we looked for arduous, labor-intensive processes that take up a lot of time from skilled clinical operations professionals but still have QC built in. The first place we identified real value is invoice processing. Our whole business model is taking the exhaust from EDC and invoicables, matching those to a budget, and making sure payments go out. We found that 60% of our customers' time was spent literally reading, translating invoices, matching them to budget protocol activities, and entering them into a system.

We built—and are GA-ing later this year—an agentic AI flow that meets sites where they are. If they're going to email invoices to an email address, don't change that. Have an agentic AI flow pick it up almost as if it's a human being: check the email, identify whether the PDF looks like an invoice, make sure there's no PHI, decompose the components, and validate whether the protocol activities match what's in the system. The accuracy has been remarkable. We tested it by giving AI agents human-sounding logins, and the experts QC-ing the work couldn't tell the difference between the AI and a human doing the matching.

That's where the real value of AI is right now—reducing low-value work and creating a higher concentration of value for the experts. Even with AI workflows, you still find escalations and edge cases that don't quite make sense. That's where clinical operations specialists should be spending their time. Beyond invoice processing, we see opportunities in contract negotiation, fallback language, budget decomposition, and EDC classification—anything where today a human being has to read something and type it into a system for the system to do something.

ACT: What do sponsors stand to lose—in site relationships, timelines, and patient access—if the payment infrastructure challenges don't get fixed?

Mizer: There's operational efficiency and margin lost. Sponsors are getting pushed to do more, faster, at lower cost. But beyond that, it's about site reputation as a brand. When payments become unpredictable, sites have to devote more administrative time to tracking invoices and resolving issues—and that makes them less willing to work with certain sponsors over time. What I've heard anecdotally is that it leads to lower investigator satisfaction and reduced willingness among top-performing sites to participate in future studies.

This is an increasingly competitive research environment, and that's how Ledger Run goes to market—we can make these things easier for you in ways that not only improve your own operations and margins, but also improve your brand with the sites, which is becoming continually more important.

ACT: With 80% of sites operating on six months or less of cash in hand, how urgent is this problem, and how close is the industry to treating it as a real priority?

Mizer: Companies like Ledger Run focusing specifically on this niche problem—where before, a lot of sponsors were solving it internally—speaks to that urgency. You also see other large players in the space starting to pay more attention to site payments. That's all a reflection of the fact that having a good reputation and brand with sites is incredibly important.

To answer more succinctly: the industry is recognizing the challenge. Sponsors, CROs, and tech providers are all starting to invest more in workflow modernization, particularly around AI. We're doing it at Ledger Run, and I know competitors in the space are as well—several focused on bottoms-up agentic AI flows. That's all in service of what that statistic reflects. If 80% of sites are operating on six months or less of cash, that's going to drive the importance of reliability—not just getting paid on time, but also improving the site's own internal operational efficiency. And that's how sponsors and CROs are going to land the best sites.