Alen Hadzic- Predictive Enrollment Engineering: Can Clinical Trial Recruitment Become Predictable?

<p>In this episode of <em>The Clinical Research Coach</em>, host <strong>Leanne Woehlke</strong> sits down with <strong>Alen Hadzic</strong>, Founder and CEO of <strong>CT Scan</strong>, to explore how data, digital advertising, and AI are reshaping the way patients are enrolled into clinical trials.</p><p>Coming from a background in consulting, marketing strategy, and lead generation, Alen brings a fresh lens to one of the industry’s most persistent challenges—<strong>patient recruitment and enrollment</strong>. Rather than relying on traditional recruitment models, his company has developed a methodology called <strong>Predictive Enrollment Engineering</strong>, designed to calculate and optimize <strong>cost-per-enrollment</strong> using real-world advertising data.</p><p>Alen shares how CT Scan’s patent-pending AI platform, <strong>Dyno AI</strong>, analyzes millions of dollars in digital advertising performance across dozens of clinical research projects to model enrollment funnels—from ad engagement and qualification to phone contact, eligibility, and final enrollment.</p><p>During the conversation, Leanne and Alen discuss:</p><ul><li><p>Why traditional patient recruitment models often fail to deliver results</p></li><li><p>The hidden friction points that cause patients to drop out of the enrollment funnel</p></li><li><p>How digital advertising can be used to measure and optimize patient interest</p></li><li><p>The importance of rapid follow-up and human engagement in improving response rates</p></li><li><p>How CT Scan achieves a <strong>65% phone answer rate</strong> through immediate outreach and optimized workflows</p></li><li><p>Why focusing on <strong>cost per enrollment—not cost per lead—changes the entire recruitment strategy</strong></p></li></ul><p>Alen also shares his unconventional journey into the clinical trials industry—from early exposure to research through his physician father to a career in consulting and entrepreneurship that ultimately led him to rethink how clinical trials approach patient enrollment.</p><p>If clinical trial recruitment has ever felt unpredictable, inefficient, or frustrating, this episode offers a data-driven perspective on how <strong>AI, marketing science, and operational discipline could transform enrollment into a measurable and predictable process.</strong></p><p><strong>Tune in to learn how predictive modeling and digital marketing principles may help bring new optimism to clinical trial enrollment.</strong></p><p><br></p><p><strong>Alen Hadzic</strong> is a healthcare technology entrepreneur focused on bringing predictability and operational rigor to clinical trial enrollment. He is the Founder and CEO of CT SCAN™, a company developing systems to remove uncertainty from patient recruitment by engineering enrollment as a measurable process rather than a marketing outcome. His work centers on Predictive Enrollment Engineering™, a methodology that models each stage of the patient journey, from initial awareness through screening and enrollment, using probability-based performance metrics. The company’s patent-pending enrollment technology, DYNO Ai™, analyzes operational and advertising data to forecast cost-per-enrollment and reduce study timelines.</p><p>Hadzic holds a graduate degree from Columbia University and completed a Master’s in Innovation and Entrepreneurship at Vlerick Business School, a top-ranked European program in the field. His background combines business strategy, systems thinking, and applied analytics in clinical research operations.</p><p>Outside of his professional work, he is an active musician who records and performs his own material, playing guitar, drums, and vocals. He approaches both technology and music with a similar philosophy: structured systems can create reliable outcomes, but creativity determines how far those outcomes can be pushed.</p>