Wednesday, April 22nd, 2026: Day OneWednesday, 22 April 2026 - US/Eastern

AI is rewriting the future of clinical innovation—faster, smarter, more precise. But with this incredible computing power comes a new kind of responsibility. This opening keynote challenges leaders to see trust not as a compliance checkbox, but as the currency of progress.

Key Themes:

• Why transparency and accountability are the foundation of credible innovation

• Balancing ambition with ethical stewardship in patient-facing technologies

• How organizations earn—and keep—the world’s trust in the age of AI

The pandemic compressed years of development into months, permanently resetting expectations for speed and adaptability. This session unpacks how AI can institutionalize that pace without compromising rigor or safety.

Key Themes:

• Designing AI-powered systems that accelerate cycles while preserving safety

• Embedding decentralized, hybrid, and remote trial models for the long term

• What “pandemic velocity” taught us about risk tolerance and coordination

• Future-proofing operations for the next disruption

Before regulators define the rules, should companies build their own guardrails? This session explores how leading organizations could formalize internal frameworks that ensure AI is deployed safely, transparently, and ethically across the enterprise.

Key Themes:

• Designing internal AI review committees and governance councils

• Integrating cybersecurity, data privacy, and bias-mitigation protocols

• Building cross-department accountability for algorithmic decision-making

• Aligning SOPs and documentation with evolving FDA and EMA guidance

• Turning compliance into culture—embedding responsibility into every workflow

The regulatory map is evolving fast. This candid dialogue with global regulators and industry veterans examines how agencies are adapting oversight for AI-enabled trials—and what true harmonization might look like.

Key Themes:

• Emerging frameworks from the FDA, EMA, MHRA, and beyond

• Managing cross-border data flow, validation, and privacy requirements

• Preparing for next-generation audits and AI documentation standards

• The path toward mutual recognition and international collaboration

• How sponsors can stay compliant amid rapidly changing expectations

How leaders turn bold ideas into measurable impact. This session bridges strategy and execution—showing how to make the business case for AI while choosing the smartest path to scale.

Key Themes:

• Building internal momentum through AI councils and cross-functional alignment

• Defining KPIs that matter—recruitment, retention, adherence, cycle-time, data lock

• The build–buy–partner dilemma: evaluating cost, readiness, and long-term ROI

• Making innovation make sense to boards, investors, and regulators

A rapid-fire showcase of the innovators pushing trial technology forward. Leading AI platforms demonstrate how they’re redefining trial design, patient engagement, and data integrity—from first enrollment to final submission.

Format Highlights:

• 7-minute lightning demos from emerging solution providers

• Real-world use cases of automation, analytics, and patient-centric design

• Live audience feedback and Q&A with innovation sponsors

Purpose: Spotlight cutting-edge tools that bridge concept to clinic

AI is reshaping not just workflows—but the very definition of leadership. This session explores how senior executives are reimagining accountability, governance, and collaboration in an era where human intuition meets algorithmic precision.

Key Themes:

• Redefining executive roles in the age of automation and abundance

• Governance, incentives, and long-term accountability for AI-led decisions

• What high-performing clinical organizations look like with AI in the driver’s seat

• Lessons from early adopters who turned data fluency into enterprise advantage

Pipeline decisions no longer need to be made by a slow stage-gate process only using science, commercial and regulatory data. We now have access to AI-driven insight that is rewriting early development strategy—helping organizations say “go” or “no-go” faster, smarter, and with greater confidence.

Key Themes:

• How predictive modeling reduces false positives in Phase I/II studies

• Real-world case study: AI-optimized decision frameworks in action

• Interactive walk-through of a redefined portfolio review process

• Balancing data-driven precision with human judgment in R&D strategy

As clinical AI evolves, so does corporate risk. This session unpacks the emerging legal, ethical, and operational exposures that come with automation—and how today’s leaders can build proactive safeguards before regulators catch up.

Key Themes:

• Identifying new forms of liability in algorithmic decision-making

• Managing explainability, hallucinations, and patient safety concerns

• Designing internal AI oversight boards and clear accountability systems

True transformation doesn’t stop at leadership—it starts with the people closest to the data. This session highlights how organizations are cultivating AI fluency across clinical and operational teams to drive trust, adoption, and sustainable change.

Key Themes:

• Designing training frameworks that translate technical knowledge into practice

• Building cross-functional collaboration between clinical, data, and regulatory teams

• Overcoming fear of automation and fostering human–machine partnership

• Case studies of culture change that empowered innovation from lab to leadership

• CRO–pharma collaboration models that effectively support AI integration and clinical innovation