The Bioprocessing Summit 2026The Bioprocessing Summit 2026
August 10–13, 2026 · Westin Boston Seaport District, Boston, MA & Virtual. 8 streams · 14 tracks · symposia + training seminars (Cambridge Healthtech Institute (CHI)). A bioprocess & CMC summit — mapped against AuroraPrime's regulatory/CMC document-authoring white space.
August 10–13, 2026 · Westin Boston Seaport District, Boston, MA & Virtual。8 streams · 14 tracks · symposia + training seminars（Cambridge Healthtech Institute (CHI)）。一场生物工艺与 CMC 峰会——对照 AuroraPrime 的监管 / CMC 文档撰写白地带。
Streams
Stream 数
Upstream → emerging modalities
上游 → 新兴模态
Tracks
Track 数
Across 4 days incl. symposia
4 天，含专题研讨
Hot topics
热点主题
5 AI / digital
其中 5 个 AI / 数字化
Pharma leads
药企 leads
Senior CMC / quality / data scientists
资深 CMC / 质量 / 数据科学家
Reg / quality sessions
监管 / 质量场次
CMC filing, standards, GxP+AI
CMC 递交、标准、GxP+AI
What each audience is talking about三类受众各自在谈什么
Directional keyword heat across the three fixed audiences. Note the contrast on the last row of each column: 'Regulatory doc authoring' is near-zero on the vendor side — the white space AuroraPrime walks into.
三类固定受众的方向性关键词热度。注意供应商一列最后一行：「监管文档撰写」近乎为零——正是 AuroraPrime 切入的白地带。
Vendors供应商
Pharma & CROs药企与 CRO
Regulators / Quality监管 / 质量
14 tracks — ranked by relevance to AuroraPrime14 条 track — 按与 AuroraPrime 的相关度排序
Relevance judged against AuroraPrime's wedge: AI authoring of regulatory/CMC documents. The CMC-heavy and digital/AI tracks rank highest; pure process-science tracks rank lower.
相关度依据 AuroraPrime 的切入点：AI 撰写监管 / CMC 文档。CMC 密集与数字 / AI track 最相关；纯工艺科学 track 较低。
#7Digital Transformation & AI in Bioprocess生物工艺数字化转型与 AI
highestIntensification, Digitalization & AI强化、数字化与 AI
Where Weave Bio, Zifo, Novasign, Yokogawa present; GxP+AI quality
Weave Bio、Zifo、Novasign、Yokogawa 演讲地；GxP+AI 质量
The summit's single most relevant track for AuroraPrime — the only one explicitly about AI + digitalization. Direct competitor Weave Bio presents here (Aug 13), alongside data/AI adjacents Zifo, Novasign, and Yokogawa. Plenaries put heads of quality from Gilead, GSK, and Pfizer on stage debating 'GxP-compliant AI in a vague regulatory framework' — the exact buyers, and the exact anxiety, that AuroraPrime's validated, audit-trailed document authoring answers. This is where we should concentrate booth traffic and in-audience engagement.
本会与 AuroraPrime 最相关的一条 track——唯一明确聚焦 AI + 数字化的 track。直接竞对 Weave Bio 在此演讲（8/13），同场还有数据/AI 邻接的 Zifo、Novasign、Yokogawa。全体会议让 Gilead、GSK、Pfizer 的质量负责人登台，讨论「模糊监管框架下的 GxP 合规 AI」——正是我们的目标买家、以及我们「可验证、有审计轨迹的文档撰写」要回答的那份焦虑。这里应是我们集中投放展位人流与受众互动的地方。
#8Analytical Intelligence分析智能
highModernizing Analytics分析现代化
Genedata 'AI-native CMC'; predictive CMC decisions
Genedata「AI-native CMC」；预测性 CMC 决策
#10Gene Therapy CMC & Analytics基因治疗 CMC 与分析
highGene Therapy, RNA & LNPs基因治疗、RNA 与 LNP
Heavy CMC/comparability/potency; USP standards
CMC / 可比性 / 效价密集；USP 标准
#12Cell Therapy CMC & Manufacturing细胞治疗 CMC 与制造
highCell Therapy细胞治疗
BLA / 21 CFR 601; potency; COGS
BLA / 21 CFR 601；效价；COGS
#13Oligonucleotide & Peptide CMC and Manufacturing寡核苷酸与多肽 CMC 与制造
highEmerging Modalities新兴模态
Phase-appropriate CMC; impurity control
分期 CMC；杂质控制
#14CMC for ADC & Next-Generation ConjugatesADC 与下一代偶联物 CMC
highEmerging Modalities新兴模态
DAR, linker-payload, regulatory CMC
DAR、linker-payload、监管 CMC
#2Cell Line Development & Engineering细胞株开发与工程
mediumUpstream上游
AI CLD + IND-readiness (Great Bay Bio)
AI 细胞株开发 + IND 就绪（Great Bay Bio）
#3Cell Culture & Upstream Processing细胞培养与上游工艺
mediumUpstream上游
Digital twins, in-silico, PAT
数字孪生、in silico、PAT
#4Formulation, Stability & Delivery制剂、稳定性与递送
mediumDownstream下游
AI/ML formulation modeling; stability reports
AI/ML 制剂建模；稳定性报告
#5Advances in Purification & Recovery纯化与回收进展
mediumDownstream下游
In-silico process characterization; HCP clearance
in silico 工艺表征；HCP 清除
#6Intensified & Continuous Bioprocessing强化与连续生物工艺
mediumIntensification, Digitalization & AI强化、数字化与 AI
AI soft sensors, PAT, continuous
AI 软测量、PAT、连续工艺
#9Next-Generation Analytical Methods新一代分析方法
mediumModernizing Analytics分析现代化
MS, PTMs, method validation reports
质谱、PTM、方法验证报告
#11Gene Therapy Manufacturing基因治疗制造
mediumGene Therapy, RNA & LNPs基因治疗、RNA 与 LNP
AAV/viral-vector manufacturing & impurities
AAV / 病毒载体制造与杂质
#1Novel & Alternative Expression Systems新型与替代表达系统
lowUpstream上游
Host-system science; little CMC-doc surface
宿主系统科学；CMC 文档面很少
Hot topics — 10 themes spanning the program热点主题 — 贯穿议程的 10 个方向
Cross-track themes mined from session keywords. Heat = how prevalent across the program; Fit = relevance to AuroraPrime (AI authoring of regulatory/CMC documents).
从场次关键词归纳的跨 track 主题。Heat＝在议程中的普遍程度；Fit＝与 AuroraPrime（AI 撰写监管/CMC 文档）的契合度。
1.GxP-Compliant AI Under a Vague Regulatory Framework不明朗监管框架下的 GxP 合规 AI
The single most recurring pain across the summit: deploying AI in biopharma quality must follow GxP principles within what speakers repeatedly call a "vague regulatory framework," with the risk that poorly-planned digitalization merely adds digital complexity. MasterControl frames compliant, purpose-built AI as cutting quality-review time by ~30% while keeping humans central.
本届峰会出现频率最高的横向痛点：在生物制药质量中部署 AI 必须遵循 GxP 原则，但多位讲者反复称当前监管框架「含糊不清」；若数字化规划不当，只会徒增数字复杂度。MasterControl 主张：用专门构建的合规 AI 可将质量审查时间缩短约 30%，同时保持人在回路。
2.Digital Twins & In-Silico / Mechanistic Bioprocess Modeling数字孪生与计算机 / 机理模型驱动的生物工艺
Digital twins, in-silico simulation, and mechanistic/data-driven modeling recur across upstream, downstream, and continuous processing. Merck notes process characterization remains experiment-intensive and is moving toward model-based PC to set proven acceptable ranges; mechanistic chromatography modeling and hybrid models aim to cut wet-lab burden. Novasign brings six industrial digital-twin use cases — biosimilar development, viral vectors, media optimization, UF/DF, and fully integrated control of a continuous bioprocess sustained beyond 30 days.
数字孪生、计算机模拟与机理 / 数据驱动建模在上游、下游与连续工艺中反复出现。Merck 指出工艺表征仍高度依赖实验，正转向基于模型的工艺表征来界定经验证可接受范围；机理色谱建模与混合模型旨在减少湿实验负担。Novasign 带来六个工业数字孪生用例——生物类似药开发、病毒载体、培养基优化、UF/DF，以及对连续生物工艺持续 30 天以上的全集成控制。
3.AI/ML Predictive Process Control, PAT & Soft SensorsAI/ML 预测性工艺控制、PAT 与软测量
Real-time process control via PAT, Raman spectroscopy, and AI-driven soft sensors is a cross-cutting theme. RedShift Bio targets the gap between quick-but-unreliable benchtop titer data and delayed core-lab HPLC; continuous processing relies on soft sensors and PAT to control CQAs in real time. Yokogawa now brings predictive, model-based control and automation to multi-bioreactor cultivation, integrating bioreactor, sensor, and offline-instrument data per unit.
基于 PAT、拉曼光谱与 AI 驱动软测量的实时工艺控制是贯穿性主题。RedShift Bio 瞄准「快但不可靠的台式滴度数据」与「滞后的中心实验室 HPLC」之间的差距；连续工艺依赖软测量与 PAT 实时控制关键质量属性（CQA）。Yokogawa 进一步把预测性、基于模型的控制与自动化带入多生物反应器培养，逐单元整合反应器、传感器与离线仪器数据。
4.AI-Native CMC Data & Analytical IntelligenceAI 原生 CMC 数据与分析智能
A persistent gap between massive analytical data generation and actionable insight. Takeda cites the widening data-to-insight gap; Genedata argues advanced modalities, compressed timelines, and rising regulatory expectations demand a new CMC-data approach, while data integrity, FAIR data, and sample-lineage traceability (Janssen) underpin compliance. Zifo now makes the substrate explicit — its FAIR Data Factory turns siloed instrument and manufacturing data into FAIR, semantically connected, AI-ready assets for predictive development and autonomous decision support.
海量分析数据生成与可执行洞察之间存在持续鸿沟。Takeda 指出数据到洞察的差距正在扩大；Genedata 认为先进模态、压缩的时间线与不断提高的监管期望需要全新的 CMC 数据方法；数据完整性、FAIR 数据与样本谱系可追溯性（Janssen）则是合规基础。Zifo 进一步把这一「底座」显性化——其 FAIR Data Factory 把孤岛化的仪器与生产数据转化为 FAIR、语义互联、AI 就绪的资产，用于预测性开发与自主决策支持。
5.AAV Empty/Full Capsid & Gene-Therapy CMCAAV 空 / 满衣壳与基因治疗 CMC
Empty/partially-filled AAV capsids compromise efficacy, yet Eli Lilly notes current monitoring methods are slow, costly, and low-throughput. Sanofi flags poorly-understood AAV structure-function and acute stability/degradation; Primera Genotech argues AAV process development is non-standardized versus plasmids or mAbs.
空 / 部分填充的 AAV 衣壳会损害疗效，但 Eli Lilly 指出现有监测方法慢、贵且低通量。Sanofi 强调 AAV 结构-功能关系尚不清晰、稳定性 / 降解敏感；Primera Genotech 认为 AAV 工艺开发不像质粒或单抗那样标准化。
6.CAR-T / In-Vivo Cell Therapy CMC, COGS & AccessCAR-T / 体内细胞治疗 CMC、成本与可及性
Cell-therapy CMC centers on complex, costly autologous manufacturing that limits scalability and access (Mass General), reliance on costly CDMOs blocking late-stage transition, and allogeneic/in-vivo CAR-T introducing new CMC challenges. In-vivo lentiviral vectors as off-the-shelf products demand higher purity standards (Kite Pharma).
细胞治疗 CMC 聚焦于复杂、昂贵的自体生产限制了规模化与可及性（Mass General）、对昂贵 CDMO 的依赖阻碍向后期推进，以及异体 / 体内 CAR-T 带来的新 CMC 挑战。作为现货产品的体内慢病毒载体要求更高纯度标准（Kite Pharma）。
7.High-Concentration mAb Formulation & Viscosity Prediction高浓度单抗制剂与黏度预测
Predicting viscosity is critical for high-concentration subcutaneous antibody formulations where excess viscosity limits injectability, and multispecific antibodies make viscosity harder to predict (Stevens Institute). AI/ML formulation modeling, Bayesian optimization, and high-throughput screening are deployed against developability and stability.
黏度预测对高浓度皮下注射抗体制剂至关重要——黏度过高会限制可注射性，而多特异性抗体更难预测黏度（Stevens Institute）。AI/ML 制剂建模、贝叶斯优化与高通量筛选被用于应对可开发性与稳定性问题。
8.Continuous & Intensified Bioprocessing连续与强化生物工艺
Perfusion, intensified fed-batch, N-1 perfusion, and continuous downstream are heavily featured. BOKU flags fully continuous solid-liquid separation as an unsolved bottleneck; Sejong notes perfusion long-term stability is unsecured; Merck describes the hard trade-off between batch, continuous, and hybrid modes across PQ, GMP practicality, and flexibility.
灌流、强化补料分批、N-1 灌流与连续下游被重点呈现。BOKU 指出全连续固液分离仍是未解瓶颈；Sejong 指出灌流长期稳定性尚无保障；Merck 描述了批次、连续与混合模式之间在 PQ、GMP 可行性与灵活性上的艰难取舍。
9.Comparability, Potency Assays & CQA Control可比性、效价检测与 CQA 控制
Comparability and robust potency assays recur across modalities. J&J flags maintaining consistency as processes scale to global supply and defining potency assays that satisfy regulators yet stay practical; USP highlights lack of concordance between emerging analytical platforms, requiring method bridging and well-characterized reference materials.
可比性与稳健的效价检测在各模态中反复出现。J&J 强调工艺扩大到全球供应时维持一致性的难度，以及如何定义既能满足监管又切实可行的效价检测；USP 指出新兴分析平台之间缺乏一致性，需要方法桥接与充分表征的参比物质。
10.ADC, Oligo & RNA/LNP Next-Generation Modality CMCADC、寡核苷酸与 RNA/LNP 新一代模态 CMC
New modalities expand the CMC challenge: ADCs run 5-10x mAb cost with heterogeneous DAR and sensitive linker-payloads (BioPharm Services, Henlius); oligo synthesis brings complex impurities and endotoxin-removal incompatibility (Biogen); LNPs are highly sensitive to processing conditions, making reproducible target CQAs a scale-up bottleneck (MIT).
新模态扩大了 CMC 挑战：ADC 成本是单抗的 5–10 倍，DAR 异质且连接子-载荷敏感（BioPharm Services、Henlius）；寡核苷酸合成带来复杂杂质与内毒素去除不兼容（Biogen）；LNP 对工艺条件高度敏感，使重现目标 CQA 成为放大瓶颈（MIT）。
Stage pain points — 11 challenges raised on the agenda台上痛点 — 议程上提出的 11 个挑战
Each is grounded in a verbatim quote from a session abstract. 9 relate directly to documentation / CMC filing — AuroraPrime's territory (highlighted). Fit = relevance to AuroraPrime; "What it means to us" spells out the implication.
每条都基于场次摘要中的原文引述。其中 9 条直接关乎文档 / CMC 递交——AuroraPrime 的主场（已高亮）。Fit＝与 AuroraPrime 的契合度；「对我们的意义」说明其含义。
Companies repeatedly stumble on CMC submissions, drawing health-authority queries and Complete Response Letters.企业在 CMC 申报上反复踩坑，频繁收到各国药监机构的问询和完整回复函（CRL），导致审批受阻。
“The common CMC pitfalls, queries from health authorities worldwide, and Complete Response Letters (CRLs) will be exemplified throughout this training class.”
Raised by: Biologics CMC Consulting · Training Seminars提出方：Biologics CMC Consulting · Training Seminars
What it means to us: Dead-center for us: AI authoring directly reduces the CMC submission errors that trigger HA queries and CRLs — our lead demo use case.对我们的意义：正中靶心：AI 撰写直接减少触发各国药监问询与 CRL 的 CMC 申报错误——我们的首选 demo 场景。
A brand-new 2026 CTD Quality guidance changes how teams must prepare eCTD Module 2.3 and Module 3, opening a knowledge gap for submission preparation.2026 年全新的 CTD 质量指南改变了 eCTD 模块 2.3 和模块 3 的撰写方式，团队在监管申报准备上出现明显的知识缺口。
“introduces the brand new CTD Quality guidance (2026)... learn how to execute CMC activities and how to prepare eCTD Module 2.3 and Module 3 Quality for regulatory submission.”
Raised by: Biologics CMC Consulting · Training Seminars提出方：Biologics CMC Consulting · Training Seminars
What it means to us: Highest fit: M2.3 QOS and Module 3 are exactly what AuroraPrime generates. Position us as staying current with the new 2026 CTD Quality guidance — a sharp differentiator.对我们的意义：契合度最高：M2.3 QOS 与模块 3 正是 AuroraPrime 生成的内容。把我们定位为「紧跟 2026 新 CTD 质量指南」——强差异化点。
Pricing and access problems for gene therapies are largely pre-determined by CMC, manufacturing, and analytical decisions made early in development.基因疗法的定价与可及性难题，其实在研发早期的 CMC、生产和分析决策阶段就已被悄悄决定，而非单纯的市场或报销下游问题。
“Many of the pricing and access challenges facing gene therapies today are often viewed as downstream market or reimbursement issues. In reality, they are frequently determined much earlier by CMC, manufacturing, and analytical decisions mad”
Raised by: Gensight Biologics · Gene Therapy CMC & Analytics提出方：Gensight Biologics · Gene Therapy CMC & Analytics
What it means to us: Supports our narrative that well-documented CMC decisions early on pay off downstream — AuroraPrime captures and structures those decisions from the start.对我们的意义：支撑我们的叙事：早期把 CMC 决策文档化，下游才受益——AuroraPrime 从一开始就捕获并结构化这些决策。
New modalities (bispecifics, trispecifics, DVDs) expand the impurity spectrum and complicate ICH Q6B–aligned impurity control.双特异性、三特异性、DVD 等新型分子拓宽了杂质谱，使得符合 ICH Q6B 的杂质控制更加复杂。
“The emergence of new biologic modalities, such as bispecific antibodies, transpacific antibodies, and DVDs, has increased the complexity of impurity control due to the unique molecular structures and expanded impurity spectrum.”
Raised by: AbbVie · Advances in Purification & Recovery提出方：AbbVie · Advances in Purification & Recovery
What it means to us: Impurity/specs content flows straight into M3 and specifications — sections we author; reinforces the advanced-modality authoring story.对我们的意义：杂质/质量标准内容直接进入 M3 与 specs——都是我们撰写的章节；强化先进模态撰写叙事。
ADC analytical and CMC control is hard due to structural complexity, heterogeneous DAR, and sensitive linker-payload chemistries.ADC 因结构复杂、DAR（药抗比）不均一以及连接子-载荷化学敏感，分析表征与 CMC 控制都极具挑战。
“Antibody-drug conjugates (ADCs) present unique analytical and CMC challenges due to their structural complexity, heterogeneous drug-to-antibody ratios, and sensitive linker-payload chemistries.”
Raised by: Shanghai Henlius Biotech, Inc. · CMC for ADC & Next-Generation Conjugates提出方：Shanghai Henlius Biotech, Inc. · CMC for ADC & Next-Generation Conjugates
What it means to us: ADC M3/specs are document-heavy and hard to get right — a high-value target for AI authoring where manual effort hurts most.对我们的意义：ADC 的 M3/specs 文档重且难做对——AI 撰写的高价值目标，人工最痛之处。
Synthetic oligonucleotides pose unique CMC challenges from solid-phase synthesis, diverse chemical modifications, and complex impurity profiles, requiring phase-appropriate strategy.合成寡核苷酸因固相合成、多样化学修饰和复杂杂质谱带来独特的 CMC 挑战，需要分阶段适配的策略。
“Synthetic oligonucleotide therapeutics, including antisense oligonucleotides (ASOs), siRNAs, and conjugated oligonucleotide modalities, present unique Chemistry, Manufacturing, and Controls (CMC) challenges due to their solid-phase synthesi”
Raised by: GondolaBio · Oligonucleotide and Peptide CMC and Manufacturing提出方：GondolaBio · Oligonucleotide and Peptide CMC and Manufacturing
What it means to us: Phase-appropriate CMC documentation across the program lifecycle — AuroraPrime generates these documents stage by stage.对我们的意义：贯穿项目生命周期的分期 CMC 文档——AuroraPrime 按阶段逐步生成这些文档。
Cell line development is a major bottleneck — long timelines, variable productivity, and poor pool-to-clone predictability, especially for bispecifics and Fc-fusions.细胞系开发（CLD）是主要瓶颈：周期长、产量波动大、从细胞池到克隆的可预测性差，对双特异性和 Fc 融合蛋白等复杂生物药尤甚。
“Cell line development (CLD) remains a major bottleneck due to long timelines, variable productivity, and limited pool-to-clone predictability, particularly for complex biologics such as bispecific antibodies and Fc-fusion proteins.”
Raised by: Thermo Fisher Scientific Inc. · Cell Line Development & Engineering提出方：Thermo Fisher Scientific Inc. · Cell Line Development & Engineering
What it means to us: Mostly upstream cell-line science — outside our document surface; only a faint IND-readiness edge. Low direct fit.对我们的意义：主要是上游细胞株科学——在我们文档面之外；仅有微弱的 IND 就绪边缘。直接契合度低。
Implementing AI in biopharmaceutical quality is held back by an unclear regulatory framework and the risk of merely digitizing complexity.在生物制药质量体系中落地 AI 受制于模糊的监管框架，且存在只是把复杂流程数字化、并未真正简化的风险。
“the implementation of AI must follow GxP principles in what is currently a vague regulatory framework”
Raised by: Gilead Sciences · Cell Culture & Upstream Processing提出方：Gilead Sciences · Cell Culture & Upstream Processing
What it means to us: The GxP+AI anxiety is our strongest messaging hook: AuroraPrime answers it with validated, audit-trailed authoring — reframe from quality systems to document authoring.对我们的意义：GxP+AI 焦虑是我们最强的 messaging 钩子：AuroraPrime 用可验证、有审计轨迹的撰写来回应——把话题从质量体系引到文档撰写。
Quality review in regulated bioprocessing is slow and manual, with manufacturers ranging from paper-based to digitally mature; compliant AI is needed to cut review time.受监管的生物工艺生产中，质量审核既慢又依赖人工，厂商成熟度从纸质到数字化参差不齐；需要合规的 AI 来缩短审核时间（约 30%）同时保持合规。
“Bioprocessing manufacturers range from paper-based to digitally mature. Learn actionable strategies for implementing purpose-built, compliant AI that delivers measurable ROI—reducing quality review time by ~30% while keeping humans central ”
Raised by: MasterControl Inc. (Jake Ure) · Intensified & Continuous Bioprocessing提出方：MasterControl Inc. (Jake Ure) · Intensified & Continuous Bioprocessing
What it means to us: Adjacent — this is quality review (MasterControl's turf), but AuroraPrime cuts combined authoring + review time; useful contrast, not our core.对我们的意义：邻接——这是质量审核（MasterControl 地盘），但 AuroraPrime 能压缩「撰写+审核」总时长；可作对比，非核心。
Personalized N-of-1 manufacturing must be made scalable and cost-effective while still demonstrating comparability, control, and run-to-run GMP compliance.个性化 N-of-1 生产必须在保证可比性、过程控制和批次间 GMP 合规的前提下，做到可规模化且具成本效益。
“The critical next step is translating this breakthrough into scalable, cost-effective standard care for thousands with rare genetic diseases.”
Raised by: Independent Consultant / USP Cell and Gene Therapy Expert Committee · Gene Therapy CMC & Analytics提出方：Independent Consultant / USP Cell and Gene Therapy Expert Committee · Gene Therapy CMC & Analytics
What it means to us: Comparability and run-to-run GMP documentation at scale — supporting evidence for our authoring value in personalized manufacturing.对我们的意义：规模化下的可比性与批间 GMP 文档——为我们在个性化生产中的撰写价值提供佐证。
Lack of consistent, science-based quality standards across the mRNA–LNP lifecycle undermines reliability, comparability, and regulatory confidence.mRNA-LNP 全生命周期缺乏一致、基于科学的质量标准，削弱了可靠性、可比性以及监管层面的信心。
“The rapid growth of mRNA therapeutics highlights the need for consistent, science-based quality standards to support raw-material testing, manufacturing, and release testing.”
Raised by: US Pharmacopeia · RNA and LNP Production and Formulation提出方：US Pharmacopeia · RNA and LNP Production and Formulation
What it means to us: Standards and comparability content feeds specifications and M3 — moderate-to-high fit for our authoring across the mRNA-LNP lifecycle.对我们的意义：标准与可比性内容进入 specs 与 M3——对我们在 mRNA-LNP 全生命周期的撰写，中高契合。
Where AuroraPrime fits — the CMC document-authoring white spaceAuroraPrime 的切入点 — CMC 文档撰写的白地带
This summit is rich in CMC science and data tooling but almost empty of CMC document authoring. Those gaps are AuroraPrime's wedge.
本峰会的 CMC 科学与数据工具丰富，但 CMC 文档撰写几乎空白。这些缝隙正是 AuroraPrime 的切入点。
CMC data is everywhere; CMC document authoring is absentCMC 数据遍地，CMC 文档撰写缺位
Evidence: 8 streams of CMC science, but across all sponsors only AuroraPrime and Weave Bio actually author regulatory/CMC documents.
证据：8 大 stream 都是 CMC 科学，但全体赞助商里真正撰写监管 / CMC 文档的只有 AuroraPrime 与 Weave Bio。
Angle: Own the gap between 'generating CMC data' and 'authoring the CMC filing'.
切入点：占据「生成 CMC 数据」与「撰写 CMC 递交」之间的缝隙。
From digital twin output → Module 3 narrative从数字孪生产出 → 模块 3 叙述
Evidence: Novasign, Sanofi, BMS show rich digital-twin / modeling data, but no one turns it into eCTD-ready M3 text.
证据：Novasign、Sanofi、BMS 展示了丰富的数字孪生 / 建模数据，却无人把它转成 eCTD 就绪的 M3 文本。
Angle: Position AuroraPrime as the layer that converts process data into the filing.
切入点：把 AuroraPrime 定位为「把工艺数据转成递交文档」的那一层。
GxP-compliant AI authoringGxP 合规的 AI 撰写
Evidence: Gilead/GSK/Pfizer stress 'AI must follow GxP in a vague regulatory framework' — but only for quality systems, not authoring.
证据：Gilead/GSK/Pfizer 强调「AI 必须在模糊监管框架下遵循 GxP」——但只谈质量系统，未谈文档撰写。
Angle: Bring validated, audit-trailed AI authoring to a quality-anxious audience.
切入点：向高度关注质量的受众，带来可验证、有审计轨迹的 AI 撰写。
Advanced-modality CMC (CGT / RNA / ADC) authoring先进模态 CMC（CGT / RNA / ADC）撰写
Evidence: Gene/cell/RNA/ADC tracks are dense with comparability, potency, and CQA filings work — all document-heavy, none automated.
证据：基因 / 细胞 / RNA / ADC track 充满可比性、效价、CQA 递交工作——全是文档密集，却无自动化。
Angle: Target the hardest, newest CMC documents where manual authoring hurts most.
切入点：瞄准最难、最新、人工撰写最痛的 CMC 文档。
Notable speakers — senior quality / CMC / data leaders重磅讲者 — 资深质量 / CMC / 数据负责人
The Digital Transformation & AI track puts heads of quality from Gilead, GSK, and Pfizer on stage — the exact buyers for validated AI authoring.
Digital Transformation & AI track 让 Gilead、GSK、Pfizer 的质量负责人登台——正是可验证 AI 撰写的目标买家。
Anthony R. Mire-Sluis
SVP, Global Quality · Gilead SciencesGilead Sciences
Plenary: 'The Correct Way to Bring Digitalization & AI into Biopharma Quality'全体：「把数字化与 AI 正确带入生物药质量」
Susan Hynes
Global Head of Quality · GSKGSK
Plenary chair · Digital & AI in Quality全体主持 · 质量中的数字化与 AI
Lynn Bottone
SVP, Quality Operations · PfizerPfizer
Fireside panel · AI in Quality炉边圆桌 · 质量中的 AI
Sivashankar Sivakollundu
Assoc Dir, Robustness & Digital Strategies · Bristol Myers SquibbBristol Myers Squibb
AI/ML predictive models for commercial manufacturing商业化制造的 AI/ML 预测模型
Justin A. Beller
Dir, Cell & Gene Therapy Analytical Ops · NovartisNovartis
Reframing development through data & digital strategy用数据与数字战略重塑开发
Anastasia Nikolakopoulou
Principal Scientist, Data Sciences Process Modeling · SanofiSanofi
Control strategies for integrated continuous purification集成连续纯化的控制策略
Zhuangrong Huang
Sr Staff Engineer · TakedaTakeda
LLM-powered data extraction → in-silico CHO optimizationLLM 驱动数据提取 → in silico CHO 优化
Source: The Bioprocessing Summit 2026 · bioprocessingsummit.com. Research hand-curated from the official agenda (2026-06); see research/bioprocessing-summit-2026/.数据来源：The Bioprocessing Summit 2026 · bioprocessingsummit.com。研究依据官方议程人工整理（2026-06），见 research/bioprocessing-summit-2026/。