Innovating Clinical Trials

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.

In this special episode, we mark Ted Trafford's 31st year in clinical trials with a candid reflection on what three decades in this industry actually teaches you. It started with a LinkedIn post Ted wrote where is says that after 31 years, he said he'd learned nothing. Listen in to hear what he meant by this. Liam and Ted go on to discuss the more experience you accumulate, the more you realise how much you still don't know. Liam frames this through the circle of competence: as your knowledge grows, so does your awareness of everything sitting outside it. Thirty-one years in, Ted feels that more than ever, and both hosts agree that the willingness to say "I don't know, can you explain that to me" is what separates people who keep growing from people who stop. The conversation also turns to recruitment, where Ted has been quietly building a list of every factor that affects clinical trial enrollment. One item on that list stands out: story. Most sponsors, Ted argues, don't have a compelling narrative around their molecule or their trial, and that gap costs them more than they realise. Liam connects this to something much older than clinical research. Humans have always been moved by story before they're moved by data. This episode is a grounded, honest conversation about what it means to spend a career in this industry, and still be learning.

Every trial starts with a number on a slide, patients needed, months allotted, a clean straight line on a chart. Liam and Ted pull that line apart in this episode, starting with Lasagna's Law: the 1970s observation that eligible patients seem to vanish the moment a trial opens and reappear the moment it closes. They dig into why recruitment forecasts go wrong not because the math is bad, but because the assumptions underneath the math are never tested, tracked, or even written down. Liam reframes recruitment forecasting using a sat-nav analogy: the plan is your estimated arrival time, the forecast is what updates as you actually drive. Ted brings a wildlife photographer's lens, literally, arguing most sponsors are zoomed in on the wrong details and missing the bigger picture entirely. A grounded, practical conversation for anyone responsible for building a forecast around best-case, worst-case, and base-case scenarios instead of one optimistic line.

In this episode, Ted opens with a poem that captures the persistent, compounding burden on clinical trial sites: 50-page consents, non-functional tech, poached CRCs, financial holdbacks, and study designs that ask far too much from participants for far too little payoff. What follows is a candid conversation between Ted and Liam about why these problems haven't gone away and in many cases, have gotten worse. Study visits in 2026 take twice as long as a decade ago. One in three procedures collected don't support a primary or key secondary endpoint. Endpoints, procedures, and planned visits have each grown by roughly 40% over 15 years. But this episode isn't only a critique. Conversations with small biotech, mid-size sponsors, and a large pharma groups, all reached out to ask what sites actually need and what's getting in the way. Thirty years ago, that didn't happen. There is a shift and that's worth paying attention to.

In this episode, Liam and Ted explore one of the most underexamined problems in clinical trial recruitment: patient motivation is not static. Drawing on real-world experience from a late-night participant funnel audit to an insomnia study no-show Liam introduces two interconnected frameworks: the Decision Threshold Matrix and the Trial Value Equation. The matrix maps patient motivation across four quadrants defined by disease severity and perceived treatment adequacy. It breaks down how patients unconsciously calculate whether participation is worth it and why trial teams consistently inflate the denominator (burden) without strengthening the numerator (benefit). Together, these tools offer a behavioral science-grounded lens for understanding when, why, and how patients engage with research and what teams can do about it. This episode is for anyone working in patient recruitment, site management, or protocol design.

In the final episode of our three-part series with Jill Fikowski, founder and CEO of Changemark Research + Evaluation, we get into one of the most persistent problems in clinical research: retention. Jill unpacks why participants drop out and it's rarely what sponsors assume. From there, we get into the pressure that lands on research coordinators when enrollment is behind, the practices that pressure produces. We also look at what happens after the last visit particularly in psychedelic trials and whether researchers have a responsibility that doesn't end when the database closes. Retention problems, Jill argues, are almost always inception problems. And solving them starts with a question most teams never ask. Part 3 of 3.

In Part 2 of our conversation with Jill Fikowski, founder and CEO of Changemark Research + Evaluation, we get into what good community engagement actually looks like in practice not as a checkbox, but as a core design principle. Jill opens with a clear answer to what good looks like: involve community from the very beginning and not just at the consent stage, not just in an advisory board email, but in protocol design, recruitment strategy, and how findings are shared. Jill walks us through a Quebec youth cannabis and psychosis study that surpassed both its enrollment and retention targets simply by asking participants what they needed before the protocol was finalised. We also get into the tension between industry-sponsored research and genuine community care. Part 2 or 3

Jill Fikowski, founder and CEO of Changemark Research + Evaluation, brings 25+ years of lived and professional experience in substance use and mental health research. In this episode we cover her work on the SALOME trial, one of the rare studies that directly changed policy. But it wasn't just the science. It was how they centered participants from the beginning. We also explore: 1. How to design community engagement and knowledge translation into your trial from day one 2. The gap between saying participants matter and actually building research around their humanity 3. What happens when you ask participants at the end: "What could we have done better?" 4. The difference between checking the box on community input and genuinely centering stakeholder voices She challenges us to confront how our biases shape every decision: who we enroll, what data we collect, what we do with findings, and whether we ever ask participants what they actually needed. Part 1 of 3.

Clinical trials don’t become complex overnight, they get there one added process at a time. In this episode, Ted and Liam break down why the industry is so effective at adding new layers, but rarely takes the time to remove what’s no longer needed. Whether it’s protocols, systems, or workflows, each addition is often made with good intent, but the cumulative effect can be significant. They explore how this impacts sites in particular, increasing workload, creating friction, and ultimately making studies harder to execute. The discussion also highlights how relying on historical processes and “what’s worked before” can prevent teams from adapting to today’s reality. Most importantly, they challenge listeners to rethink how processes are designed, not just by optimising what exists, but by asking whether it should exist at all. A practical and thought-provoking conversation on reducing complexity and improving trial execution.

A 5 AM wake-up call. A perfectly planned setup. And a moment that never delivered. In this episode, Liam and Ted use a story about a missed “blood moon” to explore a deeper truth in clinical trials: expectations don’t always match reality. They discuss how similar frustrations show up at clinical trial sites, where small issues stack up and slowly erode motivation. They break down how friction at the site level, long trainings, broken systems, and unclear processes, gradually drains momentum. From pre-mortems to escalation paths, this conversation focuses on how to prepare for what will go wrong, even before it does.

What does it actually mean to put the patient first? In this episode, Liam and Ted explore the role of empathy and human connection in clinical trials. From rushed pre-screening calls to a powerful story of pausing a consent conversation just to connect, they highlight how small moments build lasting trust. They also discuss why trust is rarely factored into budgets, despite being critical to recruitment, retention, and patient experience. A thoughtful conversation on why clinical research needs to see the person behind the data.

What makes a truly high-performing team? Inspired by the precision of Formula One pit crews, where the difference between winning and losing is measured in milliseconds, Ted and Liam explore what clinical trial teams can learn from elite performance environments. Ted outlines six principles that drive high-performing teams: clear objectives, defined roles, mapped processes, and a culture of continuous improvement. Liam draws on his experience in professional sport to reflect on why teams that truly operate at that level are rarer than we think, and why clinical trials are no exception. The episode leaves listeners with one question: what if we did the debrief before the problem existed?

In Part 3 of 3, Liam and Ted continue their conversation with Frank Watanabe, CEO of Arcutis Biotherapeutics discussing work-life balance, building social capital, and management vs. leadership. The conversation explores leadership at a practical level, from building trust across remote teams to creating flexibility that allows individuals to balance work and life in a way that works for them. Finally, he outlines his vision for Arcutis and what “meaningful innovation” really means focusing on solving real problems that matter to patients and clinicians.

In Part 2 of 3, Liam and Ted continue their conversation with Frank Watanabe, CEO of Arcutis Biotherapeutics, focusing on what it takes to hire and build high-performing teams in high-risk environments. Frank shares how he approaches hiring beyond technical skills placing strong emphasis on cultural fit, risk tolerance, and the ability to innovate. The discussion also explores how to create a culture where people feel comfortable taking risks and learning from failure. From encouraging teams to challenge the status quo to fostering psychological safety through leadership, Frank outlines what it takes to build organizations that continuously improve. They also dive into aligning incentives, building a mission-driven culture, and ensuring that when a company succeeds, its people succeed too.

In this episode, Liam and Ted sit down with Frank Watanabe, President and CEO of Arcutis Biotherapeutics, to explore his journey from a Navy officer to a biotech executive and the leadership principles established along the way. Frank shares how his early experiences in the military and his transition into pharma and biotech influenced his approach to leadership, highlighting a key idea that defines his philosophy: leadership isn’t about authority, it’s about earning trust and loyalty. They discuss how operating principles can become the “DNA” of a company, not just words on a wall, and what it takes to embed culture into everyday decision-making.

A patient in a database is not a patient in a trial. So why do we keep treating feasibility like a headcount? Fresh from a week deep in feasibility work, Liam introduces four characters who show up and cause chaos in almost every feasibility process. There's Spreadsheet Larry, who confuses a number with a truth. The EMR Oracle, who offers psychological safety dressed up as data. Prevalence Pete, who chases the sexiest percentage instead of the biggest addressable population. And Motivation Mabel, the patient who technically qualifies but simply isn't interested. Together in this episode, Liam and Ted make the case that real feasibility isn't about being right it's about being useful. Understanding the conversion funnel, knowing how confident you actually are in your data, and recognizing that patients are humans driven by trust.

In elite sports, races are often won or lost in the transition, and Liam and Ted argue that the same is true in clinical trials. Drawing on the precision of Olympic relay racing, they make the case that the handoff points between sponsors, CROs, and sites are where trials quietly succeed or silently fall apart. From recruitment referrals that never get followed up, to sites given the green light before they're actually ready, the gaps are rarely dramatic, but the cost adds up. The culprit, more often than not, is assumption over communication. Tune in to find out why fixing the handoff might be the simplest, and most overlooked way to run better trials.

Using a David Letterman-inspired “Top 10” format, the conversation highlights common feasibility pitfalls faced by sponsors, CROs, and clinical trial sites, including overly complex questionnaires, unrealistic enrollment expectations, delayed communication, and last-minute fire drills. The discussion goes beyond surface-level frustration to explore how sponsors and CROs can rethink clinical trial site feasibility by simplifying processes, questioning legacy requirements, and focusing on identifying and supporting sites with the highest potential for success. Ted and Liam also examine how better feasibility strategy can improve enrollment outcomes, reduce operational burden, and ultimately lead to more efficient clinical trials. This episode is for professionals involved in site feasibility, trial startup, enrollment strategy, and clinical operations, and for those who want to move beyond broken processes and drive better trial performance.