World Patient Safety Congress Americas 2026世界患者安全大会美洲 2026
The #1 patient safety event in the Americas (October 13–15, 2026; Thomas M. Menino Convention & Exhibition Center, Boston, MA). Focus: Drug & patient safety strategy and technology: AI & automation, benefit-risk, signal management, risk management, RWE, patient centricity, and next-gen PV tech.
美洲规模最大的患者安全大会(October 13–15, 2026;Thomas M. Menino Convention & Exhibition Center, Boston, MA)。聚焦:Drug & patient safety strategy and technology: AI & automation, benefit-risk, signal management, risk management, RWE, patient centricity, and next-gen PV tech。
Attendees
参会人数
Expected in Boston
波士顿预计到场
Speakers
演讲嘉宾
41+ organizations
41+ 家机构
Exhibitors
参展商
7 with speaking reps
7 家有演讲代表
Conference tracks
议题轨道
2 AI-signal tracks
2 个含 AI 信号轨道
Hot topics
热点主题
Cross-track themes
跨轨道主题
Top keywords — Vendors vs. Pharma & CROs vs. Regulators & NGOs热词对比 — 厂商 vs 药企 & CRO vs 监管机构与 NGO
Same keyword dictionary, three corpora derived from WPSC session titles and abstracts. Bar length = number of sessions containing the term. Reveals where each audience's narrative concentrates.
同一组关键词,三类语料来自 WPSC 场次标题与摘要。柱长 = 含该词的场次数。揭示各类受众叙事重心。
Vendors ↗厂商 ↗
10 sessions场次- AI9
- Pharmacovigilance5
- Regulatory5
- Benefit-Risk3
- Aggregate Report3
- Automation2
- NLP2
- Signal Detection2
- Signal Management2
- RMP2
Pharma & CROs ↗药企与 CRO ↗
22 sessions场次- AI20
- Pharmacovigilance16
- Signal Detection6
- ICSR6
- Validation6
- Regulatory5
- Aggregate Report4
- PBRER4
- PSUR4
- FDA4
Regulators & NGOs ↗监管机构与 NGO ↗
6 sessions场次- AI6
- Pharmacovigilance6
- Aggregate Report2
- ICSR2
- Compliance2
- FDA2
- Machine Learning1
- Signal Detection1
- PSUR1
- RMP1
Bars normalized within each column (longest bar = max count in that column). Corpus = WPSC 2026 sessions where each audience type has a confirmed speaker.每栏柱条按本栏内最长柱归一化(最长柱 = 本栏最大频次)。语料 = 对应受众类型有确认演讲人的 WPSC 2026 场次。
Vendors ↗技术厂商 ↗
Selling automationStage posture: 'AI already works in PV — we have the proof.' Vendors push end-to-end automation (intake → signal → aggregate report); IQVIA and MedGenie lead on platform, YEZA.ai represents NLP-native startups.
登台姿态:「AI 在 PV 已可用——我们有证明」。厂商推端到端自动化(摄入 → 信号 → 汇总报告),IQVIA 与 MedGenie 为平台领导者,YEZA.ai 代表 NLP 原生新势力。
End-to-end automation: intake to aggregate report in one platform端到端自动化:从摄入到汇总报告在一个平台完成
IQVIA and MedGenie both pitch near-touchless case processing; the emerging pitch includes AI-drafted PBRER narratives.IQVIA 与 MedGenie 均推近乎零接触的病例处理;新兴卖点包括 AI 起草 PBRER 叙述。
GenAI narrative authoring as the new frontierGenAI 叙述撰写成为新前沿
Multiple sessions explicitly address AI-generated PBRER/RMP narrative sections — the exact workflow AuroraPrime targets.多场明确讨论 AI 生成的 PBRER/RMP 叙述部分——正是 AuroraPrime 的目标工作流。
- Generative AI for Periodic Safety Reports
GxP validation and audit trails as table stakesGxP 验证与审计轨迹是入场券
Every AI vendor session addresses validation — recognizing that pharma safety teams won't deploy without it.每场 AI 厂商演讲都涉及验证——承认不解决这一关,药企安全团队就不会部署。
Pharma & CROs ↗药企与 CRO ↗
Operationalizing AIStage posture: 'How do we govern and deploy AI under regulatory scrutiny?' C-suite safety leaders dominate with AI governance, CIOMS WG XIV, and aggregate-report automation as the loudest themes.
登台姿态:「如何在监管审查下治理和部署 AI?」C 级安全领导者主导,AI 治理、CIOMS WG XIV 与汇总报告自动化是最响亮的主题。
PBRER authoring remains the #1 operational pain pointPBRER 撰写仍是第一运营痛点
Pharma safety leaders describe PBRER/PSUR authoring cycles of months — the white space AI document-authoring tools can address.药企安全领导者描述 PBRER/PSUR 撰写周期长达数月——AI 文档撰写工具可解决的白地带。
CIOMS WG XIV governance: 'augment not replace'CIOMS WG XIV 治理:「增强而非替代」
Pharma leaders explicitly reference CIOMS WG XIV principles for AI in PV — human oversight is non-negotiable.药企领导者明确引用 CIOMS WG XIV 的 PV AI 原则——人类监督不可或缺。
Benefit-risk + RWE: AI accelerating the signal-to-action cycle获益-风险 + RWE:AI 加速信号到行动的循环
Sanofi, Janssen, and Roche sessions connect real-world evidence with AI-augmented benefit-risk assessment.赛诺菲、杨森与罗氏的场次将真实世界证据与 AI 增强的获益-风险评估相结合。
Regulators & NGOs ↗监管机构与 NGO ↗
Setting the railsStage posture: 'AI is here — here are the guardrails.' FDA and EMA expectations are discussed in pharma-led sessions; Uppsala/WHO adds international signal-quality context. (No agency staff present on stage — perspective carried by industry + NGOs.)
登台姿态:「AI 已来——这是护栏」。FDA 与 EMA 的期望由药企主导的场次讨论;乌普萨拉/WHO 补充国际信号质量背景。(无监管官员到场——视角由行业 + NGO 承担。)
FDA AI validation expectations for PV tools (discussed, not presented)FDA 对 PV 工具的 AI 验证期望(被讨论,非到场)
An FDA-invited discussion covers ICSR processing, signal detection, and — critically — aggregate report review expectations.FDA 受邀讨论涵盖 ICSR 处理、信号检测——以及关键的汇总报告审查期望。
EMA GVP module updates: AI in GVP V (RMP) and VII (PSUR)EMA GVP 模块更新:GVP V(RMP)与 VII(PSUR)中的 AI
Evolving EU GVP guidance explicitly addresses AI use in RMP and PSUR authoring workflows.欧盟 GVP 指南更新明确涉及 RMP 与 PSUR 撰写工作流中的 AI 使用。
WHO VigiBase: international signal harmonization in the AI eraWHO VigiBase:AI 时代的国际信号协调
Uppsala Monitoring Centre presents AI's role in WHO global PV and improving reporting quality.乌普萨拉监测中心介绍 AI 在 WHO 全球药物警戒中的作用及提升报告质量的方式。
Narrative summaries are hand-curated from actual WPSC session titles and abstracts — click any example to open the real session.叙事概要由 WPSC 真实场次标题与摘要人工提炼——点击任意例子可打开对应真实场次。
Top 9 hot topics — patient safety & PV at WPSC 2026WPSC 2026 热度 Top 9 主题 — 患者安全与药物警戒
Mined from WPSC 2026 sessions. Ranked by number of sessions touching each topic. Hover any card to see the source sessions and the organizations driving it.
从 WPSC 2026 场次中挖掘。按命中本主题的场次数降序排列。鼠标悬停任意卡片可查看来源场次及驱动机构。
AI & automation transforming pharmacovigilanceAI 与自动化变革药物警戒
GenAI, ML and process automation applied to case processing, signal management, and safety surveillance across the PV lifecycle.将 GenAI、ML 与流程自动化用于病例处理、信号管理与全生命周期安全监测。
GenAI narrative & aggregate-report authoringGenAI 叙述与汇总报告撰写
AI drafting of PBRER/PSUR, DSUR and other periodic safety report narratives from structured data, with audit trails.从结构化数据 AI 起草 PBRER/PSUR、DSUR 等周期性安全报告叙述,并保留审计轨迹。
AI governance, GxP validation & CIOMS WG XIVAI 治理、GxP 验证与 CIOMS WG XIV
Governing AI in PV: explainability, human-in-the-loop oversight, audit trails, and GxP validation aligned to CIOMS WG XIV.PV 中的 AI 治理:可解释性、人在回路监督、审计轨迹,及契合 CIOMS WG XIV 的 GxP 验证。
Global regulatory compliance & evolving guidelines全球监管合规与不断演变的法规
Navigating evolving FDA, EMA GVP, and multi-country PV requirements for global safety programs.应对不断演变的 FDA、EMA GVP 及多国 PV 要求,服务全球安全项目。
Signal detection & management in the AI eraAI 时代的信号检测与管理
AI-assisted signal detection, triage, and assessment — from disproportionality analysis to multi-source mining.AI 辅助的信号检测、分诊与评估——从失衡分析到多源挖掘。
Benefit-risk & real-world evidence获益-风险与真实世界证据
Structured benefit-risk frameworks and RWE-driven safety insight accelerating the signal-to-action cycle.结构化获益-风险框架与 RWE 驱动的安全洞见,加速信号到行动的循环。
Safety in advanced therapies (gene, cell, novel modalities)先进疗法(基因、细胞、新型)的安全
Novel PV challenges for gene, cell, and other advanced therapies: long follow-up, complex causality, small populations.基因、细胞等先进疗法的新型 PV 挑战:长期随访、复杂因果、小样本人群。
Patient-centric safety & consumer-product vigilance以患者为中心的安全与消费品警戒
Extending PV to patient-reported data, OTC, cosmetics, supplements, and animal health.将 PV 延伸至患者上报数据、OTC、化妆品、补充剂与动物健康。
AI-augmented PV outsourcing & hybrid modelsAI 赋能的 PV 外包与混合模式
Redesigning PV outsourcing around AI augmentation and hybrid technology-plus-services delivery models.围绕 AI 赋能与「技术 + 服务」混合交付,重新设计 PV 外包模式。
Key pain points raised on the WPSC 2026 stageWPSC 2026 台上点出的关键痛点
Pain points stated on the WPSC stage — what pharma safety leaders, CROs, and vendors explicitly chose to call out.
逐字摘自 WPSC 议程的痛点——药企安全领导者、CRO 与厂商在台上明确点出的问题。
Automation in PV still feels manual — the promise hasn't landed
PV 自动化仍然「感觉像手工」——承诺尚未兑现
“Automation in Pharmacovigilance: Why It Still Feels Manual – and What Needs to Change.”
“药物警戒中的自动化:为什么它仍然感觉像手工——以及需要改变什么。”
PBRER/PSUR authoring still takes months and feels error-prone
PBRER/PSUR 撰写仍耗时数月且易出错
“Periodic safety report (PBRER, PSUR, DSUR) authoring remains one of the most labor-intensive and error-prone processes in pharmacovigilance.”
“周期性安全报告(PBRER、PSUR、DSUR)撰写仍是药物警戒中最耗费人力、最易出错的流程之一。”
AI hype outpaces audit-ready, operationalized reality
AI 炒作跑在「可审计、已落地」的现实前面
“Every AI vendor session addresses validation — recognizing that pharma safety teams won't deploy without audit-ready oversight and GxP-grade validation.”
“每场 AI 厂商演讲都谈验证——承认不解决可审计监督与 GxP 级验证,药企安全团队就不会部署。”
RMP narrative authoring is complex, slow, and lacks dedicated AI tools
RMP 叙述撰写复杂、缓慢,且缺乏专用 AI 工具
“RMP narrative authoring, effectiveness measure design, and periodic update generation remain manual — where pharma teams are struggling.”
“RMP 叙述撰写、有效性指标设计与周期性更新生成仍靠人工——这正是药企团队挣扎之处。”
Real-world evidence doesn't always translate into real-world safety
真实世界证据并不总能转化为真实世界安全
“From Real-World Evidence to Real-World Safety: What's Working, What's Not.”
“从真实世界证据到真实世界安全:哪些奏效,哪些不奏效。”
Source: World Patient Safety Congress Americas 2026 · terrapinn.com · Agenda & speakers researched 2026-06. Speaker-to-session mapping partially published; some session rooms/times pending (marked TBA) until the agenda is finalized.数据来源:世界患者安全大会美洲 2026 · terrapinn.com · 议程与演讲嘉宾于 2026-06 调研。演讲人与场次对应部分已公开;部分会场/时间待官方议程定稿(标注 TBA)。AI 场次 29 场 · 汇总报告相关 14 场。
