Reimagining Clinical Development in the Age of AI

Introduction

A candid roundtable hosted by Panelle and Revvity Signals brought together leaders across data management, oncology, patient engagement, and clinical analytics to explore what it truly takes to make AI useful, safe, transparent, and scalable in clinical development.

When the Hype Meets the Hard Work

The conversation opened with a shared sense of purpose. Participants, including nurses-turned-data leaders, lab scientists in product, and physicians in oversight, described why they remain committed to this work: improving patient lives, even when the path is complex and demanding. Viewed through that lens, AI is not a magic wand. It is a set of tools that must earn trust, respect regulations, and reduce burden for teams already operating under pressure.

AI Is Here to Stay — Just Not as an Oracle

Most organizations represented are in an early, experimental phase of AI adoption. Generative copilots are drafting emails, summarizing meetings, and assisting with documentation. However, when the focus shifts to clinical data, caution increases. Designing CRFs (Case Report Forms) and databases more efficiently is welcome, but never at the expense of privacy, compliance, or data integrity. For data review and decision-making, there was clear consensus: a human remains at the helm.

Build vs. Buy: Collaboration Beats Duplication

One of the liveliest debates centered on whether organizations should build capabilities in-house or partner externally. A leader in patient recruitment observed that large organizations often reinvent similar capabilities under strict governance frameworks, while specialized vendors move faster and learn more quickly. Collaboration is not a loss of control; it is often the fastest path to maturity.

Different Constraints, Shared Challenges

Large pharmaceutical companies may have scale and budget, but governance layers can slow experimentation. Small and mid-size biotechs bring urgency and innovation but may lack funding or executive champions. CROs frequently operate in people-intensive, low-margin environments where automation can disrupt traditional revenue models. Despite these differences, the pain points are remarkably similar: data volume, oversight complexity, and accountability.

Legacy Platforms: Opportunity in Plain Sight

Participants acknowledged meaningful improvements in EDC (Electronic Data Capture) platforms but expressed surprise at how slowly meaningful AI capabilities are being embedded. Newer, API-forward platforms often demonstrate greater adaptability and innovation readiness, highlighting an opportunity for modernization within existing ecosystems.

Rare Disease: When Every Signal Matters

In rare disease research, AI-enabled signal detection is not a luxury; it is a necessity. With small patient cohorts, traditional statistical thresholds can overlook emerging patterns. AI can help surface subtle signals earlier while preserving human authority and interpretive responsibility.

Trust and Accountability: The Real Guardrails

Concerns repeatedly returned to accountability, transparency, and data stewardship. Responsibility cannot be outsourced; clear ownership enables safer, more reliable systems. Trustworthy AI in clinical development requires traceability, documentation, and defined human oversight.

Culture Determines the Outcome

Technology does not implement itself. Successful adoption depends on executive alignment, domain-expert champions, and collaborative vendor relationships. Without cultural readiness, even the most sophisticated tools will underperform.

Walk Before You Run: A Two-Year Confidence Plan

Participants emphasized focusing first on high-value, repetitive workflows and expanding only after early wins are established. Measured progress builds confidence, strengthens governance frameworks, and reduces organizational resistance.

AI as a Force Multiplier — Never a Replacement

AI can reduce administrative burden, accelerate insight generation, and support clinical and data teams. However, it cannot replace human expertise, ethical judgment, or regulatory accountability. Sustainable progress demands collaboration across sponsors, CROs, vendors, regulators, and patient communities.