Breaking Down Dr. Ferrer’s PharmTech Interview on How AI Is Rewriting Drug Development

Dr. Ferrer delivers a talk at CPHI Europe 2025. Image Credit: Amanda Ferrer

As the global conversation around artificial intelligence accelerates, healthcare is moving quickly to embrace the tools reshaping diagnostics, clinical research, and pharmaceutical manufacturing. That momentum was on full display at CPHI Europe this October, where Dr. Gustavo Ferrer presented his talk, “Harnessing AI in Clinical Practice to Drug Development and R&D: From the Bedside to Benches.”

Following the presentation, Dr. Ferrer sat down with PharmTech.com to expand on the ideas he introduced during his session — discussing how AI is fundamentally transforming drug development and how platforms like MoxieLink are making real-world clinical data actionable for researchers.

AI Is Redefining the Pace of Discovery

In the interview, Dr. Ferrer emphasized just how dramatically AI is reshaping early research. 

“AI is compressing timelines and reducing costs across the entire drug development lifecycle,” he told PharmTech, noting that traditional workflows are being replaced by predictive modeling, automated protocol optimization, and digitally supported clinical trials.

He described how AI now identifies promising drug candidates “thousands of times faster than before,” while simultaneously improving enrollment speed and site performance. By integrating telemedicine, remote patient monitoring, and digital documentation, decentralized and hybrid trials are becoming more inclusive, more efficient, and more reflective of real-world behavior.

Turning Everyday Care Into Research-Grade Insight

One of the central themes of the interview was the power of real-world data and how platforms like MoxieLink are reshaping the feedback loop between clinics and R&D (research and development) teams.

“AI’s true power lies in recognizing patterns across messy, real-world data,” Dr. Ferrer said. 

Today, insights that once took months of retrospective analysis can be surfaced almost instantly — extracted directly from clinical notes, patient interactions, device telemetry, and in-the-moment care.

This is where MoxieLink has taken a leading role. Built on a FHIR-compliant architecture, it integrates the clinical care environment directly into research operations, allowing every encounter to become what he described as a “regulated, research-grade signal — without adding burden to the clinician.”

From there, insights flow directly into dashboards that help refine study design, identify responder subpopulations, flag early safety signals, and streamline regulatory decision-making. This seamless connection between bedside and bench is the foundation of faster, more adaptable drug development.

What Changes When AI Enters the Workflow

When asked how to quantify the real-world impact of AI-enabled research platforms, Dr. Ferrer pointed to measurable improvements observed across more than 55 facilities where MoxieLink has been deployed.

“We’ve seen marked improvements in screening-to-randomization conversion, documentation accuracy, protocol compliance, and retention,” he said. “All of these translate directly into accelerated therapeutic timelines.”

He stressed that the ability to collect more complete, continuous data, not just snapshots during site visits, has significantly improved the fidelity of clinical information. This, in turn, increases confidence in trial outcomes while making the studies more inclusive and representative of real patient populations.

Innovation Requires Collaboration and Guardrails

From left to right Laura Santana, Amanda Ferrer, Nicole Ferrer, Dr. Gustavo Ferrer, Framir Ramirez and Alireza Pourhamid present Dr. Ferrer BioPharma at CPHI Europe 2025. Image Credit: Amanda Ferrer

Throughout the interview, Dr. Ferrer returned repeatedly to a theme that often gets overlooked in AI discussions: none of this works without cross-disciplinary teamwork and strong accountability.

“Success requires distributed expertise with centralized governance,” he emphasized.

He outlined the interconnected roles of clinicians, data scientists, regulatory experts, security teams, and human-factors engineers. Each must operate independently but with shared guardrails to ensure AI tools remain explainable, safe, and aligned with regulatory expectations across FDA, EMA, and MDR pathways.

He also underscored the importance of trust and transparency, noting that “operators must understand why a model recommends an action.” This is why The Moxie Health Group continues to use human intervention as a quality-assurance layer, ensuring that AI remains a tool — never a replacement for clinician judgment.

What Still Stands in the Way

Despite the momentum, Dr. Ferrer acknowledged the challenges that still limit widespread AI adoption in pharmaceutical settings. Regulatory ambiguity, fragmented data systems, and uneven digital fluency among teams remain significant hurdles. He described how The Moxie Health Group has responded with FHIR-compliant integration, transparency frameworks, and a dedicated academy that trains staff in digital readiness.

“We need teams who understand both the potential and the limits of AI,” he said. “That’s how we innovate responsibly.”

Looking Forward

Across the interview, one message was made clear: AI is no longer a futuristic concept. It is actively reshaping how we discover, build, test, and deliver new care strategies. With platforms like MoxieLink bridging clinical and research environments, that shift is accelerating.

“We’re entering a moment where real-world data, AI, and clinical expertise can finally operate in one ecosystem,” Dr. Ferrer said. “That’s how we accelerate innovation without compromising patient safety.”

For more information about MoxieLink, click here.