Technology

In this Q&A, Abraham Gutman, founder and CEO of AG Mednet, discusses why the clinical trial industry has mastered data capture but never built the execution architecture needed to act on it, how the right infrastructure changes the role of human experts, and why enthusiasm for agentic AI is outrunning what clinical trials can realistically support.

In this Q&A, Robert Hummel, chief operating officer at Suvoda, discusses how agentic AI is compressing RTSM build and deployment timelines, what safeguards are needed to maintain compliance and oversight at speed, and how intelligent automation will reshape the broader clinical trial technology stack over the next decade.

From rising costs and regulatory uncertainty to persistent vaccine hesitancy, sponsors face mounting pressure to standardize operations, build community trust, and develop the behavioral capabilities needed to run vaccine trials effectively in a rapidly shifting environment.

In this video interview, Liz Beatty, co-founder and chief strategy officer at Inato, makes the case for moving beyond trial-by-trial planning toward cross-asset site partnerships—and explains why sites are three times more likely to share patient data when sponsors make that shift.

As clinical trials grow increasingly complex and multi-modal, the pharmaceutical industry is pivoting toward AI-driven agentic orchestrators and lakehouse architectures to untangle disparate data streams, ensure regulatory compliance, and accelerate time-to-insight.

In this video interview, Liz Beatty, co-founder and chief strategy officer at Inato, explains why asking sites to use different technology for every sponsor remains a major barrier to AI adoption and what a site-first approach to technology development looks like in practice.

In this video interview, Liz Beatty, co-founder and chief strategy officer at Inato, shares results from a Sanofi COPD study where AI-enabled sites screened patients 33% faster and achieved 100% enrollment success—including one site that had been non-performing for over 100 days.

In this video interview, Liz Beatty, co-founder and chief strategy officer at Inato, explains how AI is replacing unreliable feasibility estimates with precise, real-time patient matching—and what that means for reducing non-enrolling sites and screen failure rates.

As the FDA formally recognizes real-world evidence as eligible confirmatory evidence for drug approval, sponsors face a growing imperative to build the data infrastructure, organizational alignment, and analytical capabilities needed to use RWE effectively across the development lifecycle.

In this video interview, Abraham Gutman, founder and CEO of AG Mednet, describes how AI can take on rote reasoning tasks like PHI redaction and document QA, and why offloading that work is what gives human experts the clarity to focus on genuine decision making.

In this video interview, Abraham Gutman, founder and CEO of AG Mednet, explains why decades of progress in data capture have not solved the execution problem in clinical trials, and what an operational architecture for AI actually looks like in practice.

Despite clear data quality and regulatory advantages, paper-based clinical outcome assessments persist due to cost asymmetry, trial complexity, startup timelines, and provider capability gaps, though hidden paper costs and loss of institutional knowledge often outweigh upfront electronic implementation expenses.

Clinical Trials Day is an international celebration of everyone who makes medical discoveries possible. It is also an opportunity to shine a light on the innovations helping to keep research rising.

In this video interview, Sam Hinsley, statistics manager at Phastar, explains how statisticians can ensure patient data is used responsibly and innovatively across every phase of development, from rare disease to personalized medicine to AI.

Clinical development productivity improved in 2025, but gains remain fragile as end-to-end timelines lengthened again, signaling that future success depends less on individual trial execution and more on program-level orchestration, site engagement, and adaptive operating models.

Participant adherence depends on readiness—a combination of knowledge, calibrated confidence, and real-world mastery—not simply on digital tools, reminders, or education, which are forms of exposure rather than preparation for sustained performance.

As imaging-heavy clinical trials grow more complex and globally distributed, sponsors are increasingly re-evaluating traditional infrastructure models, with cloud-native platforms showing potential to reduce operational burden, accelerate site activation, improve imaging quality oversight, and lower total trial costs.

From payment delays and feasibility misalignment to technology burden and AI adoption, clinical research sites are navigating a convergence of pressures that increasingly determine who sponsors work with and how well trials perform.

In this Q&A, Mark Freitas, managing director and life sciences practice lead at Alvarez & Marsal, discusses how clinical trial design has become a strategic business decision—and why small and midsize companies bear the greatest consequences when those decisions go wrong.

Limited evidence surrounds direct-to-patient clinical trial site models, despite growing literature showing that decentralized approaches can improve patient access, enrollment performance, and operational efficiency while reducing participant burden.

In this episode of the Applied Clinical Trials Podcast, Jonathan Andrus, co-CEO, CRIO, and Samir Jain, vice president of product management, healthcare data interoperability and EHR solutions, Medidata, discuss how their new partnership is enabling seamless data flow between eSource and enterprise platforms to reduce site burden and improve data quality across global clinical trials.

In this video interview, Hal Green, senior solution architect and life sciences vertical lead EMEA at Loftware, discusses why sponsors must now treat disruption as an expected condition and how real-time visibility and connected systems enable faster, more adaptive responses.

In this video interview, Mark Freitas, managing director and life sciences practice lead at Alvarez & Marsal, identifies governance inertia and review cycle lag as the most underappreciated risks when AI speeds up protocol development faster than organizations can act on the insights it generates.