AI in Healthcare & Pharma Summit
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About this event
AI in Healthcare & Pharma Summit
Date: November 17-18, 2026
Venue: Boston, USA
The AI in Healthcare & Pharma Summit, organized by RE•WORK, brings together senior executives, AI leaders, data scientists, healthcare innovators, pharmaceutical professionals, and technology experts. This event explores how artificial intelligence is reshaping the future of healthcare and life sciences, providing a platform for discussion on the latest advancements, challenges, and opportunities in the field.
Event Overview
This summit features keynote speakers, workshops, and panel discussions covering topics such as:
- Artificial intelligence applications in healthcare and pharmaceuticals
- Machine learning in drug discovery and development
- AI-driven patient care and treatment personalization
- Ethical considerations and regulatory challenges
- Real-world case studies and industry best practices
Who Attends
The event attracts a diverse audience, including:
- Senior executives from healthcare and pharmaceutical companies
- AI and data science professionals
- Healthcare innovators and researchers
- Technology experts and solution providers
- Academics and policymakers
Location and Reach
Hosted in Boston, a hub for biotechnology and healthcare innovation, the summit has a global reach, attracting attendees from around the world. The event provides opportunities for networking, collaboration, and knowledge-sharing among industry leaders, researchers, and innovators.
Key Focus Areas
The summit focuses on the practical applications of AI in healthcare and pharma, including:
- Improving patient outcomes through AI
- Accelerating drug development and clinical trials
- Enhancing operational efficiency in healthcare systems
- Addressing ethical and regulatory challenges
Why Attend
By attending the AI in Healthcare & Pharma Summit, participants can:
- Gain insights into the latest AI trends and innovations
- Learn from industry leaders and experts
- Network with peers and potential partners
- Discover new opportunities for collaboration and business growth
Event Details
Date: November 17-18, 2026
Location: Boston, USA
Organized by: RE•WORK
Data sheet
AI in Healthcare & Pharma Summit – Event Attendee & Buyer Profile Analysis
Event date: November 17–18, 2026
Location: The Hilton Boston Park Plaza, Boston, Massachusetts, United States
Event status: Upcoming
Research date: June 30, 2026
Event Overview
| Event Name | AI in Healthcare & Pharma Summit |
| Event Date | November 17–18, 2026 |
| Event Status | Upcoming |
| Venue | The Hilton Boston Park Plaza |
| City | Boston |
| State / Region | Massachusetts (MA) |
| Country | United States |
| Organizer | RE•WORK |
| Official Event Website | re-work.co |
| Event Type | Summit / In-person conference |
| Primary Category | Medical & Pharma |
| Secondary Applicable Categories | IT & Technology; Science & Research |
| Audience Reach | Global, with strong U.S. Northeast and life sciences corridor relevance |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Low for numerical attendance; high for event identity, dates, city, organizer, and thematic positioning based on official organizer content |
| Main Purpose of Event | Executive-level knowledge sharing, AI adoption strategy, healthcare and pharmaceutical innovation, networking, partnerships, and solution sourcing across healthcare, life sciences, data, and AI ecosystems |
About the Event
The AI in Healthcare & Pharma Summit is an in-person RE•WORK event focused on how artificial intelligence is transforming healthcare delivery, pharmaceutical research, life sciences operations, and data-driven decision-making. According to the organizer’s official description, the summit brings together senior executives, AI leaders, data scientists, healthcare innovators, pharmaceutical professionals, and technology experts.
From a commercial and lead-generation perspective, the event matters because it sits at the intersection of healthcare operations, drug development, clinical innovation, AI platforms, data infrastructure, governance, and enterprise adoption. It is especially relevant for suppliers selling AI software, data platforms, analytics, clinical technology, cloud infrastructure, compliance tools, research enablement solutions, consulting, and strategic partnerships into hospitals, health systems, biotech firms, pharmaceutical companies, and innovation-driven healthcare organizations.
1. Who Attends: Buyers / Attendees
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| Healthcare provider executives | Hospitals, integrated delivery networks, academic medical centers, specialty care groups | Budget owners and transformation sponsors for AI, digital health, workflow optimization, and patient care technology | High relevance for enterprise software, analytics, interoperability, clinical AI, and operational improvement vendors |
| Pharmaceutical and biotech innovation leaders | Large pharma, biotech firms, drug discovery companies, translational research teams | Influence over R&D tools, data science platforms, AI-enabled discovery, real-world evidence, and automation initiatives | High relevance for drug discovery AI, cloud computing, data engineering, lab automation, and consulting providers |
| Chief AI, data, and analytics leaders | Healthcare enterprises, life sciences firms, digital health platforms, research institutions | Strategic and technical evaluators of AI platforms, MLOps, governance, model deployment, and enterprise data architecture | Core buyer group for AI infrastructure, model lifecycle tools, data quality, privacy, and orchestration solutions |
| Clinical and medical innovation leaders | Health systems, clinics, medical research organizations, precision medicine programs | Evaluate clinical utility, patient impact, safety, validation, workflow fit, and regulatory implications | Important for solutions tied to diagnostics, care pathways, personalization, and clinical decision support |
| IT and digital transformation teams | Provider systems, payer organizations, pharma enterprises, research organizations | Own integration, security, deployment, procurement support, vendor qualification, and scalability decisions | High-value for cloud, cybersecurity, integration, infrastructure, and enterprise implementation services |
| Data science and machine learning teams | Healthcare analytics groups, pharma R&D, biotech data teams, AI product units | Technical recommenders and pilot champions for model development, validation, and deployment tools | Useful for bottom-up adoption, proof-of-concept sales, and technical qualification |
| Procurement and vendor management teams | Large healthcare systems, pharmaceutical companies, research networks | Commercial gatekeepers for enterprise purchasing, contracts, compliance, and onboarding | Relevant for converting pilot discussions into approved supplier relationships |
| Researchers and academic institutions | Universities, medical schools, research hospitals, translational medicine centers | Influence tool selection for research collaboration, grants, datasets, and validation studies | Good fit for research software, compute platforms, data partnerships, and innovation alliances |
| Regulatory, ethics, and governance stakeholders | Healthcare compliance teams, pharma governance groups, policy and risk functions | Influence AI deployment controls, explainability, privacy, safety, and responsible use frameworks | Relevant for governance, auditability, model risk, privacy, and compliance-focused offerings |
| Investors, accelerators, and strategic partners | Healthcare investors, venture groups, innovation partners, ecosystem builders | Influence partnerships, growth capital, alliances, and commercialization pathways | Useful for market visibility, channel partnerships, and strategic business development |
2. Event Location and Attendee Geographic Origin
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Boston | Local healthcare, biotech, pharma, research, and hospital ecosystem | Very high | Boston is a major U.S. life sciences and academic medicine hub, increasing local executive, research, and innovation attendance likelihood |
| Massachusetts | Regional attendees from Cambridge, Worcester, and broader state healthcare and biotech networks | High | Strong cluster of biotech firms, academic medical centers, and AI research institutions |
| U.S. Northeast corridor | New York, New Jersey, Pennsylvania, Connecticut, Rhode Island, Maryland | High | Dense concentration of pharma, payer, provider, and health-tech organizations with convenient travel access to Boston |
| National U.S. | Healthcare systems, pharma firms, AI teams, digital health startups, and research institutions across the U.S. | High | Official organizer positioning and summit format indicate broader national draw beyond the host region |
| International | Likely participation from global healthcare, pharma, and AI communities | Medium to high | RE•WORK markets itself as a global AI events company; international reach is likely, but country-by-country attendee data is not publicly confirmed in the provided source |
3. Audience Reach
| Reach Level | Assessment | Explanation |
|---|---|---|
| Global | Primary classification | The organizer presents RE•WORK as a global AI events company and positions the summit around internationally relevant AI and healthcare themes. Boston also supports inbound attendance from the global life sciences community. |
| National | Secondary practical reach | Most directly monetizable outreach is likely across U.S.-based healthcare, biotech, pharma, and health-tech accounts. |
| Regional | Secondary concentration zone | New England and the Northeast corridor should provide especially dense buyer concentration because of the host city’s sector profile. |
4. Sample Buyer Companies and Websites
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| The organizer content provided does not include a current-year attendee list, sponsor list, exhibitor list, speaker organization list, or prior-year participant directory for this summit. As a result, company-level attendance cannot be confirmed without introducing unsupported claims. | |||||
| For compliant prospecting, use the Apollo.io recommendations in this report to build target accounts across hospitals, health systems, pharmaceutical companies, biotech firms, medical research institutions, and healthcare AI teams in Boston, the U.S. Northeast, and national healthcare innovation hubs. | |||||
5. Job Profiles, Industries and Event Type
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | Chief AI Officer / Head of AI | AI / Innovation | C-Level / VP | Owns AI strategy, platform selection, governance, and enterprise deployment priorities |
| 2 | Chief Data Officer / VP Data & Analytics | Data / Analytics | C-Level / VP | Key stakeholder for data infrastructure, governance, interoperability, and AI-readiness |
| 3 | Chief Medical Information Officer | Clinical Informatics | C-Level / Director | Connects clinical workflows with digital and AI adoption decisions |
| 4 | Chief Information Officer / CTO | IT / Technology | C-Level | Approves architecture, security, implementation models, and enterprise vendor selection |
| 5 | Director of Data Science / ML Engineering | Data Science | Director / Head | Drives evaluation of model development tools, data pipelines, and technical partnerships |
| 6 | VP / Director, Digital Transformation | Transformation / Strategy | VP / Director | Sponsors cross-functional programs involving AI, automation, and operating model redesign |
| 7 | Head of Clinical Innovation | Clinical / Innovation | Director / VP | Assesses patient care applications, provider adoption, and measurable clinical outcomes |
| 8 | VP / Director, R&D Informatics | R&D / Informatics | VP / Director | Critical in pharma and biotech for AI-assisted discovery, lab data, and computational workflows |
| 9 | Director of Procurement / Strategic Sourcing Manager | Procurement | Director / Manager | Important for supplier onboarding, commercial terms, and procurement qualification |
| 10 | Compliance / AI Governance Lead | Risk / Compliance | Director / Head | Helps approve high-risk or regulated AI use cases in healthcare and pharma environments |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Hospital & Health Care | Core provider-side audience segment for clinical and operational AI adoption | Clinical workflows, patient engagement, operational efficiency, diagnostics |
| 2 | Pharmaceuticals | Direct relevance to pharma innovation, R&D, and AI-led drug development | Drug discovery, clinical data analysis, compliance, portfolio optimization |
| 3 | Biotechnology | Biotech firms are strong adopters of AI in research and translational science | Modeling, genomics, discovery pipelines, lab informatics |
| 4 | Medical Devices | Relevant where AI supports diagnostics, imaging, software-enabled devices, and regulated innovation | Embedded AI, decision support, workflow integration, device analytics |
| 5 | Research | Academic and translational research institutions are likely participants | Collaborative research, AI tooling, compute infrastructure, data sharing |
| 6 | Higher Education | Medical schools and universities often participate in AI-healthcare conferences | Research partnerships, clinical validation, innovation programs |
| 7 | Information Technology & Services | Covers enterprise implementation partners and healthcare technology teams | Systems integration, implementation, managed services, digital transformation |
| 8 | Computer Software | Relevant for AI platforms, clinical applications, analytics tools, and workflow software | Enterprise software, health AI, automation, analytics, SaaS solutions |
| 9 | Computer & Network Security | Healthcare AI adoption raises data privacy, cyber risk, and governance concerns | Security for patient data, model governance, access controls, protected environments |
| 10 | Management Consulting | Consultants often influence AI roadmaps, vendor selection, and implementation strategy | Transformation strategy, PMO support, governance, adoption planning |
| 11 | Government Administration | Relevant for public health, research funding, and regulated healthcare ecosystems | Public health AI, grants, policy, health innovation partnerships |
| 12 | Health, Wellness & Fitness | Relevant for preventive care, digital health engagement, and personalized care models | Consumer health AI, patient engagement, wellness analytics |
6. Estimated Attendance
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Attendance figure not publicly confirmed by the organizer. | Unconfirmed | Official organizer text provided does not list attendance | No numerical estimate included to avoid unsupported claims |
| Exhibitor count | Not publicly confirmed | Unconfirmed | No exhibitor directory or sponsor prospectus supplied | This appears to be summit-led rather than expo-led, but exhibitor format is not confirmed in provided source |
| Buyer count | Not publicly confirmed | Unconfirmed | No attendee segmentation numbers supplied by organizer in provided text | Only audience types are described, not totals |
| Speaker count | Not publicly confirmed | Unconfirmed | Official summary references keynote speakers, workshops, and panels | Speaker format confirmed; numerical count not confirmed |
| Sponsor count | Not publicly confirmed | Unconfirmed | No sponsor list supplied in the official text provided | Could be verified later from event page or prospectus if released |
| Historical attendance | Not available in supplied official content | Historical / prior-year evidence unavailable | No prior-year attendance figures included in the provided source excerpt | Further verification would require prior-year event page details not supplied here |
7. Key Focus Areas and Buyer Engagement
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| AI in healthcare operations | Reduce inefficiency, improve care coordination, automate administrative workflows | Discuss ROI, deployment speed, interoperability, and workflow integration | Operational AI, workflow automation, analytics dashboards, orchestration tools |
| Drug discovery and development | Accelerate discovery, improve candidate prioritization, manage scientific data at scale | Position technical differentiation and validation against real R&D use cases | Discovery AI, computational biology tools, cloud compute, lab data platforms |
| Patient care personalization | Use data and AI to tailor interventions, pathways, and support | Engage clinical and digital health leaders around outcomes and patient impact | Clinical decision support, patient engagement AI, predictive analytics |
| Machine learning and data science | Build, train, validate, and deploy models responsibly in regulated settings | Target technical buyers with use-case demos and architecture-fit discussions | MLOps, feature stores, model monitoring, secure data environments |
| Ethics, governance, and regulation | Ensure safe, explainable, auditable, and compliant AI adoption | Open conversations with compliance, legal, risk, and governance stakeholders | AI governance tools, audit trails, model documentation, risk frameworks |
| Real-world case studies and implementation | Understand proof of value, deployment barriers, and adoption lessons | Use peer benchmarking and success metrics to progress pipeline opportunities | Consulting, implementation support, reference architectures, change management |
| Data infrastructure and interoperability | Connect fragmented systems, datasets, and workflows | Appeal to IT, data, and informatics buyers with integration and scalability value | Data platforms, integration middleware, cloud architecture, API management |
Lead Quality Assessment
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | Very High | The event theme is tightly aligned to healthcare, pharma, AI, analytics, and digital transformation buyers. |
| Decision-maker availability | High | Official description explicitly references senior executives and AI leaders, indicating strong executive presence. |
| Data collection potential | Medium | Good strategic event for account identification, but attendee-list quality depends on whether organizer releases participant or speaker organizations. |
| Apollo targeting potential | Very High | Clear account universe exists across hospitals, pharma, biotech, medtech, research, and health IT buyers. |
| Geographic targeting potential | High | Boston and the Northeast provide dense, high-value clusters; expansion to national and selected global healthcare hubs is straightforward. |
| Best outreach approach | High | Use account-based outreach focused on use cases, compliance, ROI, implementation proof, and peer case studies rather than generic event messaging. |
| Overall lead quality | High | Strong fit for high-value enterprise healthcare and life sciences sales motions, especially if the client sells AI, data, software, infrastructure, or advisory services. |
| Best use case | High | Ideal for targeted account list building, speaker-based prospecting, sponsor targeting, and healthcare AI thought-leadership outreach. |
| Limitations / risks | Medium | Current-year company-level attendee evidence is not available in the supplied official source, so list-selling claims should not be made without further verification. |
Apollo.io Targeting Recommendation
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Hospital & Health Care; Pharmaceuticals; Biotechnology; Medical Devices; Research; Higher Education; Information Technology & Services; Computer Software; Computer & Network Security; Management Consulting | Build a compliant account universe aligned to the event’s likely buyer base |
| Departments | Information Technology; Engineering; Data / Analytics; Innovation; Operations; Clinical Informatics; Research & Development; Procurement; Strategy; Compliance | Capture both technical and economic buying centers |
| Seniority | C-Level; VP; Head; Director; Senior Manager | Prioritize strategic decision-makers and strong influencers |
| Job titles | Chief AI Officer, Chief Data Officer, Chief Information Officer, CTO, Chief Medical Information Officer, VP AI, VP Data & Analytics, Director of Data Science, Director of Machine Learning, Head of Clinical Innovation, VP Digital Transformation, Director R&D Informatics, Director Procurement, Strategic Sourcing Manager, AI Governance Lead | Match the summit’s likely executive and technical audience |
| Geography | Primary: Massachusetts, New York, New Jersey, Pennsylvania, Connecticut, Maryland. Secondary: California, Illinois, North Carolina, Texas, Washington. Optional international: UK, Switzerland, Germany, Canada | Focus first on regions most likely to produce attendees and high-fit buyers |
| Employee size | 200–500; 501–1,000; 1,001–5,000; 5,001–10,000; 10,001+ | Best fit for organizations with enterprise budgets and structured AI initiatives |
| Keywords | artificial intelligence, machine learning, clinical AI, digital health, healthcare analytics, drug discovery, precision medicine, real-world evidence, clinical informatics, MLOps, AI governance, health data platform | Narrow to organizations actively aligned with summit themes |
| Technologies, if relevant | Cloud data platforms, analytics platforms, machine learning tooling, data governance systems, healthcare interoperability stacks | Helpful for advanced Apollo segmentation where technology data is available |
| Revenue range, if relevant | $50M–$500M; $500M–$1B; $1B+ | Prioritize firms capable of budgeted AI programs and multi-stakeholder procurement |
| Company type | Public companies, private growth companies, nonprofit health systems, academic medical institutions | Covers the likely mix of provider, pharma, biotech, and research buyers |
| Funding / public company filters | Use selectively for biotech and digital health growth accounts | Useful when targeting innovation-stage buyers and high-growth healthcare technology firms |
Suggested Apollo Search Logic: ("artificial intelligence" OR "machine learning" OR "clinical AI" OR "drug discovery" OR "healthcare analytics" OR "digital transformation") AND (healthcare OR hospital OR pharma OR biotechnology OR medical) AND (Chief AI Officer OR Chief Data Officer OR CIO OR CTO OR "Director of Data Science" OR "VP Digital Transformation" OR "Head of Clinical Innovation").
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Sources & Verification Notes
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| RE•WORK event page / supplied official website content | Official organizer source | Confirmed event name, city, country context, organizer, and official date listing of November 17–18, 2026; confirmed audience positioning around healthcare, pharma, AI, data science, and senior executives | High |
| User-supplied known event details | Provided event input | Venue: The Hilton Boston Park Plaza; city: Boston; state: MA; country: United States; start and end dates | Medium to High, used where not contradicted by official organizer content |
| Verification note | Research methodology | No current-year attendee list, sponsor directory, exhibitor list, attendance figure, or speaker organization list was included in the supplied official content. Company-level attendance claims were therefore not made. | High compliance note |
| Suitability note | Lead generation assessment | Suitable for B2B attendee list building only through compliant account-based targeting, speaker/sponsor monitoring, and future official directory validation. Not suitable for claiming a confirmed attendee list based on current evidence. | High |
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