Agenda

Registration & Networking Breakfast

Start the day with check-in, light breakfast, tea, coffee, and informal networking with attendees, speakers, and sponsors.

• Check-in
• Light breakfast / tea / coffee
• Informal networking

Welcome & Opening Remarks

Opening remarks from the host to welcome attendees and introduce the conference theme.

• Welcome address
• Brief overview of conference theme
• Acknowledgment of sponsors and dignitaries

AI, Biology and Research

The Data Delusion, and a path to Computable Biology

Bill has spent the last 15 years focused squarely on the ultimate compute problem: Human Biology. After leading technology as the CIO of the Broad Institute of MIT and Harvard and serving as SVP of Research Technology at Bristol Myers Squibb, Bill founded Wellfleet Advisors to help the industry move past the R&D lottery and start resolving biological truths. He is the architect of "The Resolution Paradigm," a framework built on his deep conviction that "Biology is Compute." Bill is an advocate for grounded world models that solve for disease at the level of first principles. When he isn’t helping companies re-engineer their research model, Bill is learning to play the Irish fiddle, enjoying being a new grandfather, and, working on his book, Being Curious, which explores the mindset needed to navigate the intersection of disciplines targeting this problem.

Who Should Attend / Practitioner Relevance

This session is built specifically for hands-on technical practitioners—including AI Engineers, Data Analysts, and Software Engineers. Some of the area covers like

Moving past high-level leadership talk and abstract theory, this talk focuses on the concrete architecture of treating biology as a pure compute problem.

Whether you are building data pipelines for complex systems, training world models, or engineering scalable software, you will gain practical insights into how first-principles engineering and grounded data models are being used to solve real-world biological truths.

Key Takeaways From Talk:

Understand the impossibility of the current drug discovery paradigm and a proposal for a different path. Explore specific grounded examples. Come away with a new language for discussing.

• Computable Biology: Using "The Resolution Paradigm" to treat human biology as a computer problem.
• Grounded World Models: Building first-principles AI architectures to resolve true biological data.
• Replacing Legacy R&D: Moving past traditional trial-and-error to fix structural drug discovery flaws.
• Agentic Automation: Deploying self-directed AI workflows to re-engineer early stage laboratory research.
• Multidisciplinary Integration: Unifying multi-omics datasets by bridging data science and biological fields.
• Scientific Innovation Mindset: Cultivating cross-discipline curiosity to lead modern digital health transformations.

Ideal for healthcare leaders, pharmaceutical background, technology professionals, and anyone interested in the possible AI adoption in drug manufacturing.

Secure and Safe AI

Topic: Secure and Safe AI — Building Trust in the Age of Intelligent Systems

As Artificial Intelligence becomes deeply integrated into businesses, healthcare, finance, government, and everyday digital experiences, ensuring that AI systems are secure, trustworthy, and responsibly governed has become a critical priority. Organizations today face growing concerns around data privacy, cyber threats, model manipulation, regulatory compliance, misinformation, and ethical AI deployment.

This session will explore the evolving landscape of AI security, governance, and risk management, with practical guidance on how enterprises can safely adopt AI technologies while protecting sensitive data, maintaining transparency, and reducing vulnerabilities across AI-driven systems.

Key topics include:

• Securing AI models and enterprise AI platforms
• Protecting sensitive data and ensuring privacy compliance
• Preventing AI misuse, adversarial attacks, and deepfake threats
• Responsible and ethical AI governance frameworks
• AI risk assessment and regulatory preparedness
• Cybersecurity implications of generative AI and autonomous systems
• Building trustworthy AI for healthcare, finance, and enterprise environments
• Balancing innovation with safety, compliance, and operational resilience

Who Should Attend / Practitioner Relevance

This session is built specifically for hands-on technical practitioners—including Security Engineers, AI Engineers, Data Analysts, and Software Engineers.

Moving past high-level leadership talk and abstract ethics theory, this talk focuses on the concrete technical architecture required to defend against adversarial attacks, model manipulation, and data leaks.

Whether you are hardening production APIs, building secure pipeline architectures, implementing privacy-preserving data compliance, or engineering guardrails for generative models, you will gain practical, code-level and data-level insights to build resilient, trustworthy systems.

Key takeaways from talk:

Attendees will gain insights into how organizations can create robust AI security strategies while fostering innovation and maintaining public trust in intelligent technologies.

Networking Break

Short morning break for refreshments and networking.

• AM refreshments
• Informal conversations
• Networking with attendees and speakers

AI in Healthcare Experience

Topic: AI in Healthcare Experience — From Hospitals to the Doctor’s Clinic

Artificial Intelligence is reshaping healthcare at every level — from large hospital systems and pharmaceutical enterprises to neighborhood doctor’s clinics and virtual care platforms. This session explores how AI is transforming the complete patient journey and redefining the healthcare experience across care settings.

The discussion will include real-world examples of how AI technologies are improving operational efficiency, reducing administrative burden, and enabling more proactive, preventive, and personalized care.

Key topics include:

• AI-powered virtual assistants for appointment scheduling and patient follow-up
• Intelligent clinical documentation and automated medical note generation
• Predictive analytics to identify high-risk patients earlier
• AI-assisted diagnostics and imaging support
• Personalized treatment recommendations and care plans
• Remote patient monitoring and telehealth integration
• Chatbots and digital tools improving patient communication and engagement
• Automation of billing, claims, and administrative workflows

Who Should Attend / Practitioner & Leader Relevance

This session is built for both hands-on technical practitioners—including AI Engineers, Data Analysts, and Software Engineers—and the strategic decision-makers leading them, such as Healthcare CIOs, Clinical IT Directors, and Product Managers.

Moving past abstract concepts, this talk bridges the gap between engineering execution and leadership strategy. Technical practitioners will gain insights into the data pipelines, compliance architectures, and model integration required for automated documentation and predictive diagnostics.

Concurrently, technology leaders and decision-makers will learn how to evaluate AI vendors, justify ROI, mitigate deployment risks in clinical settings, and effectively scale smart workflows across hospital networks and clinics.

Key takeaways from talk:

Attendees will gain insights into how AI is helping create smarter clinics, more connected healthcare systems, and better patient experiences while empowering healthcare professionals to focus more on care and less on manual processes.

Lunch & Networking

Lunch and networking opportunity with speakers, sponsors, and attendees.

Agentic AI for Unified Health Benefit Management

Topic: Agentic AI in Unified Health Benefit Management

Join Amit Srivastava for an engaging discussion on how Agentic AI is reshaping the healthcare and health benefits landscape. This session will provide a broad industry perspective on the rapid evolution of AI-driven healthcare operations, intelligent automation, and connected benefit ecosystems.

The talk will explore how organizations across healthcare, insurance, and employer benefits are using advanced AI agents to streamline complex processes, improve member experiences, enhance care coordination, and drive more informed decision-making.

Key topics include:

• The rise of Agentic AI in healthcare and insurance
• Intelligent automation in benefits administration
• Personalized healthcare navigation and engagement
• AI-driven claims, authorization, and care management workflows
• Data interoperability and unified member experiences
• Emerging trends, opportunities, and challenges in digital health transformation

Key takeaways from talk:

Attendees will gain valuable insights into the future direction of AI-powered healthcare ecosystems and how intelligent technologies are helping create more efficient, connected, and patient-centric benefit experiences.

Ideal for healthcare leaders, employers, payers, providers, technology professionals, and anyone interested in the future of AI in healthcare and benefits management.

From Pilot to Production: Engineering Safe & Scalable AI in Healthcare

Topic: From Pilot to Production: Engineering Safe & Scalable AI in Healthcare

Healthcare organizations across the industry are rapidly experimenting with Artificial Intelligence to improve clinical outcomes, streamline operations, and enhance patient experiences. However, moving from successful pilot programs to production-ready, enterprise-scale AI adoption remains one of the biggest challenges in healthcare transformation.

This session provides a practical and strategic perspective on how organizations can successfully scale AI initiatives across complex healthcare environments. The discussion will address the operational realities of scaling AI, including governance, interoperability, infrastructure readiness, compliance, cybersecurity, workflow integration, and organizational adoption.

Key discussion areas include:

• Privacy, security, and AI governance
• Operationalizing AI in healthcare environments
• Moving from pilots and proofs of concept to production
• Workflow integration and change management
• Interoperability and enterprise-scale AI implementation
• Building safe, scalable, and measurable AI solutions

Who Should Attend / Practitioner & Leader Relevance

This session is built for hands-on technical practitioners—including AI Engineers, Data Analysts, and Software Engineers—alongside strategic decision-makers like Healthcare CIOs, CTOs, Enterprise Architects, and Clinical Operations Leaders.

Moving past theoretical talking points, this talk delivers the concrete blueprint needed to transition medical AI out of the sandbox and into production. Technical teams will learn how to tackle tough engineering realities like FHIR/HL7 interoperability, low-latency clinical workflow integrations, data privacy pipelines, and model monitoring infrastructure.

At the same time, technology leaders and decision-makers will walk away with actionable governance frameworks, risk management strategies for compliance, and operational change management playbooks required to successfully scale AI solutions across complex enterprise environments.

Key takeaways from talk:

Attendees will gain insights into the technical, operational, and leadership strategies needed to transform AI innovation into scalable healthcare solutions that deliver measurable business value and improved patient outcomes.

Measuring ROI, Driving Adoption, and Building Executive Buy-In

Topic: AI Adoption, ROI, Governance, and Executive Buy-In

This session covers how organizations can move beyond AI experimentation and create measurable business value with the right governance, adoption, and leadership alignment frameworks.

As organizations accelerate their investment in Artificial Intelligence, the focus is rapidly shifting from experimentation to measurable business outcomes. Successfully adopting AI at scale requires more than deploying technology — it demands a clear strategy for governance, operational alignment, security, compliance, and demonstrating tangible return on investment.

Key discussion areas include:

• Accelerating enterprise AI adoption and modernization
• Building scalable and secure AI infrastructure
• Measuring AI ROI and business outcomes
• Establishing AI governance and compliance frameworks
• Managing data security, privacy, and responsible AI practices
• Scaling generative AI and machine learning initiatives
• Aligning AI investments with business objectives and executive priorities
• Overcoming operational and organizational adoption challenges

Who Should Attend / Practitioner & Leader Relevance

This session is built for both technical practitioners—including AI Engineers,—and key business leaders, such as VPs of Technology, AI Product Managers, Enterprise Architects, Financial/Operations DirectorsCommercial and Procurement Leader.

Moving past high-level corporate talking points, this talk bridges the gap between technical metrics and business value. Technical teams will learn how to build cost-optimized AI infrastructure, implement automated governance frameworks, and track concrete performance data that directly maps to enterprise goals.

For decision-makers and executive leaders, this panel provides a practical playbook on how to quantify GenAI ROI, clear compliance and data security hurdles, secure executive funding, and overcome organizational resistance to ensure full-scale workforce adoption.

Key takeaways from talk:

Attendees will gain actionable insights into how enterprises can move beyond AI experimentation to create sustainable, governed, and value-driven AI ecosystems with stronger executive support.

Tea / Coffee Break

Afternoon refreshment break.

• Tea
• Coffee
• Snacks
• Networking

Reframing Pharma Commercial AI

Topic: Reframing Pharma Commercial AI

This panel explores how AI is reshaping pharmaceutical commercial strategy, customer engagement, field operations, analytics, and decision-making. The discussion will focus on moving beyond isolated AI experiments toward practical, responsible, and measurable commercial transformation.

Key discussion areas include:

• Commercial AI use cases in pharma and life sciences
• Customer engagement and field force enablement
• Data strategy, governance, privacy, and compliance
• Operationalizing AI across commercial workflows
• Scaling AI from pilots to enterprise adoption
• Measuring business value and adoption impact

Who Should Attend / Practitioner & Leader Relevance

This session is built for hands-on technical practitioners—including Data Analysts, Data Engineers, and Software Engineers—alongside commercial leaders like Pharma Marketing VPs, Commercial Operations Directors, Brand Managers, and Sales Force Effectiveness Leaders.

Moving past generic tech theory, this talk focuses on the reality of deploying commercial life sciences platforms. Technical teams will learn how to build next-best-action data pipelines, scale omni-channel recommendation engines, and integrate commercial analytics tools with strict GDPR, HIPAA, and industry-specific privacy compliance frameworks.

At the same time, commercial decision-makers and executive leaders will walk away with an actionable playbook on how to measure the direct ROI of field-force AI tools, drive internal adoption among sales representatives, and transform siloed marketing data into a scalable, compliant, and value-driven commercial strategy.

Key takeaways from talk:

Attendees will gain practical perspectives on how pharma and life sciences organizations can reframe commercial AI from a technology initiative into a strategic business capability.

The Future of AI in Healthcare: From Commercial,R&D and Regulatory

This panel brings together leaders from healthcare, life sciences, technology, academia, and regulatory strategy to explore how Artificial Intelligence is transforming the future of healthcare delivery, patient engagement, commercial operations, and compliance. As AI adoption accelerates across the healthcare ecosystem, organizations must balance innovation with governance, regulatory oversight, data privacy, and responsible implementation. This discussion will examine how healthcare leaders are navigating evolving regulations while unlocking business value and improving patient outcomes through AI-driven solutions.

Key discussion areas include:

• The future of AI in healthcare and life sciences
• Commercial AI use cases and enterprise adoption strategies
• Regulatory frameworks and AI governance
• Data privacy, security, and responsible AI deployment
• Digital health, patient engagement, and connected care
• Balancing innovation, compliance, and risk management
• Scaling AI initiatives across healthcare organizations

Who Should Attend / Practitioner & Leader Relevance

This session is designed for AI Engineers, Data Scientists, Healthcare Technology Professionals, Compliance Leaders, Regulatory Affairs Professionals, Digital Health Innovators, Clinical Operations Leaders, Healthcare Executives, and Chief Innovation Officers.

Technical practitioners will gain insights into building compliant, secure, and scalable AI solutions that meet evolving healthcare regulations while delivering measurable business value.

Business and healthcare leaders will learn practical approaches for establishing AI governance frameworks, managing risk, ensuring regulatory readiness, and driving successful AI adoption across commercial and operational functions.

Key takeaways from talk:

Attendees will gain a forward-looking perspective on how AI is reshaping healthcare from both commercial and regulatory viewpoints, and how organizations can successfully innovate while maintaining trust, compliance, and responsible governance.

Closing Ceremony

Final wrap-up of the conference with reflections, acknowledgments, and closing remarks.

• Key takeaways
• Recognition of speakers and sponsors
• Vote of thanks
• Group photo