In the final part of this three-part conversation, Liam and Ted close things out with Scott Burgher, Director of Patient Operations at Quest Diagnostics, looking ahead at where AI genuinely moves the needle in recruitment, and where the industry still gets feasibility wrong.

Scott breaks AI's near-term impact into two practical buckets. The first is administrative: compressing study startup from six to twelve months down to weeks by automating document collection, regulatory submissions, IRB correspondence, and budget negotiations, work that's repetitive by nature and ripe for automation. The second is data-driven: using EHR and lab data to flag genuinely qualified patients rather than relying on broad disease prevalence, cutting down what used to take a coordinator six weeks of manual review.

They Explore:

1. Where AI can realistically compress study startup timelines, and where it can't
2. Why mining EHR and lab data beats broad disease-prevalence estimates for site and patient feasibility
3. Why the human element becomes the differentiator as software gets commoditized
4. Why most feasibility processes are still solving the wrong problem

Scott's closing thoughts on data, predictive medicine, and the road to digital twins. The conversation closes on feasibility, which Scott calls broken at its core, working backward from protocol specifics to find the real "needle in the haystack" instead of the whole haystack. A thoughtful close to the series.

In Part 2 of this three-part conversation, Liam and Ted continue with Scott Burgher, Director of Patient Operations at Quest Diagnostics, going deeper into why recruitment keeps falling short.

Liam reframes the problem from the ground up: the industry treats recruitment as a marketing function obsessed with filling the top of the funnel, when the real work is moving patients all the way through it. Scott connects this to his experience running end-to-end mock trials years ago, testing the full patient journey, not just whether an ad worked, but whether someone could realistically sit through a four-hour infusion or navigate a handoff between site staff who'd never met them.

The conversation turns to site economics, which Scott calls structurally broken: sites invest in staff and training months before seeing payment, and when that investment doesn't pay off, they quietly stop prioritizing the study. As Scott puts it, that's not a performance problem, it's a structural one, though it shows up in the data looking exactly like one.

Ted pushes the conversation toward what actually closes that gap: a real feedback loop between sponsors and sites, where issues get surfaced, acted on, and communicated back, not just logged and forgotten.

A grounded look at what it actually takes to fix recruitment from the inside.

In Part 1 of this three-part conversation, Liam and Ted sit down with Scott Burgher, Director of Patient Operations at Quest Diagnostics, who brings over 20 years of patient recruitment experience spanning healthcare marketing, clinical trial agencies, large consulting, and big tech, to talk about the good, the bad, and the ugly of patient recruitment.

In this episode, Scott breaks down why recruitment keeps missing the mark. He argues that sponsor decision-making cycles are a massively underestimated blocker, a recruitment strategy can be fully approved by the study team and still sit untouched in legal or procurement for months while the clinical timeline keeps ticking, often defaulting back to digital and social media ads as a last resort. Liam connects this to a separate problem he's seen across budgets: an "iceberg" of recruitment costs sitting below the surface, the centralized strategy and patient-processing work that rarely gets line-itemed alongside site costs.

They Explore:

1. Why the 86% missed-enrollment-deadline statistic hasn't moved in over a decade, even as industry awareness has grown
2. How sponsor decision-making cycles quietly stall recruitment strategy for months before outreach even begins
3. The "iceberg" problem: recruitment costs that never make it into the visible budget
4. Why most patients never hear their doctor recommend a clinical trial, and what that gap costs
5. Where AI is genuinely useful in patient identification, and where it's being oversold as a fix
6. The role of primary care physicians in patient recruitment

A candid look at the structural issues behind patient recruitment.