Moderna Plans 2027 Cancer Vaccine Launch After Phase 3 Melanoma Win

Moderna癌症疫苗在黑色素瘤3期试验中疗效优于Keytruda Moderna证实了其个体化mRNA平台的有效性，证明癌症疫苗需要定制化靶向新抗原，因为约90%的肿瘤突变在患者个体之间存在差异。 Moderna首席执行官Stéphane Bancel与Jorge Conde共同深入解读了其与默克合作研发的个体化黑色素瘤癌症疫苗具有里程碑意义的3期试验结果。该结果显示，该疫苗在无复发生存期和无远处转移生存期方面均优于Keytruda单药治疗。该平台对患者肿瘤与健康组织进行测序，利用算法筛选最多34种特异性新抗原，并在大约42天内合成mRNA注射剂，以引导T细胞由内而外攻击特定的癌症指征。Bancel详细阐述了在工艺BLA监管框架下以工业规模生产N=1个性化药物所面临的工程与监管挑战，并概述了向肺癌、肾癌、膀胱癌和胰腺癌拓展的计划。除肿瘤学领域外，Moderna还利用同一个迭代平台公布罕见遗传性肝病的晚期试验结果，并研发针对自身免疫性疾病根源的治愈性疗法。 Moderna与默克开发的个体化mRNA癌症疫苗intismeran联合Keytruda在黑色素瘤3期临床试验中取得积极结果，在首次中期分析中均达到了无复发生存期（RFS）和无远处转移生存期（DMFS）终点。 (3:47) 2期试验的5年随访数据显示，约80%接受治疗的黑色素瘤患者维持无病状态，相较于Keytruda单药治疗，无复发生存期改善了约50%。 (3:47) Moderna的生产平台实现“针头到针头”（即从肿瘤活检测序到医院交付）大约需要42天，该平台采用针对N=1量身定制的无细胞酶促合成工艺。 (20:00) Moderna计划通过工艺生物制品许可申请（Process BLA）提交监管审批，目标是在2027年实现商业化供应，并由位于马萨诸塞州马尔伯勒的专用制造工厂提供支持，该工厂每年有能力生产数万剂个性化药物。 (22:15) 除黑色素瘤外，Moderna正在将该平台拓展至肺癌、肾癌、膀胱癌、胰腺癌和胃癌，并将mRNA技术应用于罕见遗传性肝病和自身免疫性疾病。 (30:00)

Moderna CEO Stéphane Bancel and a16z General Partner Jorge Conde examine the clinical, technical, and manufacturing mechanisms behind Moderna and Merck’s individualized mRNA cancer vaccine, intismeran, following positive Phase 3 results in melanoma. Bancel argues that pairing de novo T-cell instruction with checkpoint inhibition overcomes the historical failures of cancer vaccines through a scalable, cell-free production platform. Clinical Durability and Dual Immune Mechanisms (4:40) In August 2026, Moderna and Merck reported that their individualized neoantigen therapy met primary recurrence-free survival (RFS) and secondary distant metastasis-free survival (DMFS) endpoints in a Phase 3 melanoma trial. This confirmed five-year Phase 2 follow-up data presented at ASCO, where the vaccine combined with Merck's Keytruda achieved an ~80% disease-free survival rate—an approximate 50% improvement over Keytruda alone. Bancel emphasized that reaching five years without recurrence is clinically recognized as a cure. Bancel explained that the two therapies work orthogonally. Immune checkpoint inhibitors like Keytruda release inhibitory brakes on immune cells, but roughly 40% of melanoma patients on monotherapy fail to achieve five-year disease-free survival and face risks of lifelong autoimmune disorders. The individualized mRNA vaccine provides precise molecular coordinates, instructing cytotoxic T cells to hunt specific mutations. Blood analyses confirmed the mRNA creates de novo T cells targeted to patient-specific neoantigens rather than merely expanding existing immune clones. Overcoming Delivery Hurdles and Tumor Heterogeneity (10:00) Bancel attributed the failure of over a thousand prior cancer vaccine trials across two decades to inadequate delivery and an overreliance on shared antigens. Traditional peptide or protein vaccines circulated loosely in peripheral blood, yielding low immunogenicity. In contrast, Moderna’s intramuscular mRNA travels directly to lymph node antigen-presenting cells (APCs), which translate the sequences internally and present antigens from within the cell. Clinical data also revealed that roughly 90% of tumor neoantigens are completely unique to each patient, explaining why shared-antigen therapies consistently failed. Moderna sequences a patient's tumor and healthy tissue, comparing three gigabytes of genetic data letter-by-letter. A proprietary algorithm selects up to 34 patient-specific mutations into a single mRNA molecule. While current trials rely on a decade-old algorithm ("Intismeran 1.0"), Bancel noted Moderna is analyzing blood and genomic data from the 20% of non-responding patients to design an updated version 2.0. Synthetic Production and Process-Based Regulation (20:00) Unlike autologous cell therapies like CAR-T that require harvesting, engineering, and expanding living cells in large bioreactors, Moderna treats mRNA strictly as digital information. Its manufacturing pipeline relies entirely on enzymatic chemistry in liquid solution, synthesizing DNA templates and transcribing mRNA cell-free without bacterial fermentation or E. coli cultures. This synthetic approach compresses the "needle-to-needle" cycle—from tumor biopsy to hospital delivery—to roughly 42 days. Because liquid enzymatic reactions require small physical volumes, Moderna is miniaturizing its hardware to increase throughput within fixed cleanroom envelopes at its Marlborough, Massachusetts facility, which is designed to yield tens of thousands of doses annually. From a regulatory perspective, Bancel stated intismeran will follow CAR-T precedents by seeking a "process BLA" rather than a product BLA, proving to regulators that a standardized, automated manufacturing process reliably generates reproducible patient-specific therapies. Expansion Vectors in Oncology and Autoimmunity (30:00) Moderna is expanding intismeran across three oncology vectors. First, it is pairing the vaccine with Keytruda in established checkpoint indications, including Phase 3 non-small cell lung cancer and Phase 2 bladder and kidney trials. Second, it is testing intismeran as a post-surgical monotherapy in stage 1 lung cancer, seeking to eliminate tumor recurrence without the lifelong autoimmune risks of checkpoint inhibitors. Third, it is targeting checkpoint-resistant cancers, evaluating intismeran in pancreatic and gastric cancers alongside targeted agents like KRAS inhibitors. Beyond oncology, Bancel highlighted upcoming pivotal readouts for pediatric rare liver diseases and an expansion into autoimmune disorders. Moderna's autoimmune strategy comprises both off-the-shelf mRNA modulators designed to recalibrate immune signaling pathways and an exploratory, individualized platform that aims to identify and eliminate the specific autoreactive T cells causing tissue damage. While Moderna is targeting regulatory submissions and potential availability as early as 2027, commercial success hinges on forthcoming detailed Phase 3 data presentations, payer negotiations on cost and value, and clinical proof that the platform can succeed in historically refractory indications such as pancreatic cancer.

Moderna 首席执行官 Stéphane Bancel 表示，Moderna 与默沙东合作的个体化 mRNA 新抗原疗法在黑色素瘤 3 期临床试验中达到主要与次要终点，成为历史上首个在后期临床证实有效的癌症疫苗，并展示出 mRNA 技术平台向早期肿瘤单药治疗及自身免疫疾病拓展的潜力。 3期临床数据与双重免疫机制协同 (4:40) Bancel 指出，Moderna 与默沙东联合开展的个体化新抗原疗法在黑色素瘤 3 期试验首次中期分析中，不仅达到了无复发生存期（RFS）的主要终点，还提前达到了无远处转移生存期（DMFS）的次要终点。结合此前在 ASCO 披露的 2 期五年随访数据，联合疗法使约 80% 的患者在术后五年内未出现复发，相比帕博利珠单抗（Keytruda）单药组将复发风险降低了约 50%。肿瘤学界普遍将五年无复发视作临床治愈标志，Moderna 正在推进监管申报，计划最早于 2027 年实现该疗法的商业化上市。 该方案与免疫检查点抑制剂形成了互补的正交生物学机制。Bancel 用比喻解释称，Keytruda 负责解除免疫系统的抑制刹车（“释放猎犬”），但既往数据显示约 40% 的黑色素瘤患者单药治疗五年内仍会复发，并面临 1 型糖尿病、红斑狼疮或克罗恩病等严重自身免疫毒性风险；而 mRNA 疫苗则在分子层面精确教育 T 细胞识别肿瘤突变（“指示目标”）。血液检测证实，该疫苗不仅能扩增已有免疫，更能诱导生成此前患者体内不存在的全新（de novo）特异性 T 细胞克隆，实现靶向清剿。 克服历史瓶颈：新抗原独特性与mRNA递送 (10:00) 在既往二十余年间，肿瘤疫苗领域经历了一千多次临床试验失败。Bancel 认为此次突破归因于体内递送生物学与绝对个体化。Moderna 于 2015 年发表的研究表明，mRNA 经肌肉注射后会直接引流至淋巴结，进入抗原呈递细胞（APC）并在细胞内部翻译呈递抗原，其免疫应答强度显著优于直接在外周血液循环中稀释降解的传统重组蛋白或多肽疫苗。 在突变靶标选择上，临床试验证实约 90% 的新抗原在患者之间完全独特，使得以往依赖共享抗原的通用疫苗在生物学上难以奏效。Moderna 依托低成本测序技术，对比患者肿瘤与健康组织的全部 3GB 基因序列，利用专有算法从数百上千个突变中筛选出最多 34 个临床最相关的特异性新抗原并串联编码。Bancel 透露，目前试验仍沿用十年前构建的“Intismeran 1.0”基础算法；团队正通过回溯 20% 无应答患者的血样与基因组，探索向 2.0 版本迭代，以期突破胰腺癌等难治癌种。 42天全合成制造与流程BLA监管路径 (20:00) 不同于自体 CAR-T 细胞疗法需要在体外反应器中对活体免疫细胞进行扩增与基因重构，mRNA 属于信息分子，生产端仅需患者的数字化基因对比序列文件。该流程完全采用水溶液中的无细胞酶促化学反应合成 DNA 模板，规避了质粒与大肠杆菌发酵体系，随后经体外转录并封装入脂质纳米颗粒（LNP）。整个“针头到针头”（从活检采样到医院交付）周转时间目前约为 42 天，反应体积微小使得硬件占用空间显著低于传统生物反应器。 产能与质量控制方面，Moderna 在马萨诸塞州马尔伯勒建立的商业化制造基地年产能达数万剂，足以覆盖黑色素瘤的适度规模。在监管审批机制上，Bancel 明确该药遵循类似细胞疗法的“流程生物制品许可申请”（Process BLA），而非传统的“产品 BLA”。由于每位患者的成药化学序列皆不相同，FDA 的审评核心在于验证自动化黑箱系统的流程重现性与受控标准，即相同样本输入必须稳定产出质量一致的定制药剂。 跨适应症拓展向量与自身免疫前沿 (30:00) 依托从头诱导 T 细胞生成的机制，Moderna 规划了三大拓展向量：第一是与 Keytruda 联用，推进非小细胞肺癌 3 期试验以及肾癌和膀胱癌 2 期试验；第二是进军 1 期肺癌等早期肿瘤，术后作为单药使用以规避检查点抑制剂导致的终身性自身免疫副反应；第三是针对胰腺癌、胃癌等检查点抑制剂以往无效的高风险癌种，尝试单独攻关或与新型靶向药（如 Revolution Medicines 的 KRAS 抑制剂）联合应用。 除肿瘤管线外，Moderna 预计将于年内公布罕见儿科遗传性肝病的后期关键试验数据，并宣布进军自身免疫疾病领域。Bancel 透露，公司正同步开发两种路径：一是重置异常免疫通路的通用现货型（off-the-shelf）mRNA 产品；二是处于实验室探索阶段的个体化平台，旨在直接特异性清除攻击自体组织的自反应性免疫细胞，力求从发病根源实现干预。 Moderna 的个体化 mRNA 疗法在黑色素瘤中确立了临床概念验证并推动了流程化生物药监管实践，但该技术仍面临 20% 患者无应答的机制挑战，在胰腺癌等“冷肿瘤”中的有效性亦待临床检验。此外，未来全球商业化普及不仅依赖 42 天生产周期的进一步缩短与微型化降本，还取决于尚未公布的药品定价能否获得商业医保体系的认可。

## Background 该内容由 a16z 普通合伙人 Jorge Conde 与 Moderna 首席执行官 Stéphane Bancel 于 2026 年 9 月 2 日在播客及 RSS 平台联合发布。节目围绕 Moderna 与默沙东联合研发的个性化黑色素瘤 mRNA 疫苗在 3 期临床试验中取得积极结果展开，深入探讨了其测序与算法筛选机制、单人单药的超复杂工业化制造、跨癌种临床拓展以及 mRNA 在罕见病与自身免疫疾病中的广阔应用前景。 ## TL;DR 节目深入剖析了 Moderna 与默沙东研发的个性化黑色素瘤癌症疫苗（Intismeran）取得突破性 3 期临床成功的深层逻辑。该疗法通过对患者肿瘤与健康细胞进行全测序，利用算法筛选多达 34 个新抗原并合成为长链 mRNA，在 APC 细胞内由内而外重新训练 T 细胞，从而与免疫检查点抑制剂形成正交协同。为解决单人单药（N=1）的极端工程挑战，Moderna 依靠全合成无质粒酶促反应与设备微型化，将针头到针头的生产周期压缩至约 42 天，并以工艺 BLA 模式打通监管通道。未来，Moderna 计划将该技术拓展至肺癌单药治疗及胰腺癌等冷肿瘤，并进一步攻关罕见遗传病与自身免疫性疾病的底层病因。 ## Atmosphere & style 对谈氛围严谨专业且极具远见，既有顶尖生物科技商业对话的高维视野，又充盈着老友重逢时的熟稔与从容。Stéphane Bancel 展现出兼具工程师偏执与医药领航者底气的叙事风格，面对医学史上的重大突破既兴奋克制，又对工艺面积、周转周期和死磕 20% 无应答者的细节如数家珍。听众能真切感受到一项曾历经上千次失败的技术终于迎来临界点时的历史厚重感，以及底层平台技术重构人类对抗绝症版图时的巨大张力与澎湃希望。 ## Bulletin - `05:00` Moderna 与默沙东合作研发的个性化黑色素瘤 mRNA 疫苗（Intismeran / mRNA-4157）在 3 期临床首期中期分析中提前达到无复发生存期与无远处转移生存期双终点，成为二十年来首个在黑色素瘤中疗效超越 Keytruda 单药的癌症疫苗。 - `13:21` 该疗法通过对比患者肿瘤与健康组织的基因测序数据，利用算法筛选最多 34 个高特异性突变新抗原定制单链 mRNA；数据显示约 90% 的新抗原在患者之间完全不同，证明了个性化定制的不可替代性。 - `20:00` 得益于全合成无质粒水相酶促反应与设备微型化工程，Moderna 已将活检至回输的“针头到针头”周期压缩至约 42 天，并通过 Process BLA（工艺生物制品许可）路径打通个体化药物监管审批。 - `30:00` Moderna 正在向肺癌（3 期）、肾癌、膀胱癌以及早期肺癌单药治疗拓展，并计划利用下一代 AI 算法攻关胰腺癌等“冷肿瘤”，后续还将推进罕见遗传病与个体化自身免疫疾病管线。 ## Key takeaways - `10:00` 癌症疫苗并非预防原发癌症，而是作为治疗性疫苗重新教育免疫系统识别逃逸的突变信号，从而预防癌症复发。 - `10:00` 与传统在血液中游弋的重组蛋白或合成多肽不同，mRNA 注射后迁移至淋巴结并进入抗原呈递细胞（APC）内部表达，实现自内而外的天然抗原呈递与强效免疫激活。 - `13:21` 基因测序分析显示患者间约 90% 的新抗原完全不重合，彻底终结了寻找“共享抗原”的旧研发路径，奠定了全流程一人一药（N=1）的生物学必要性。 - `05:00` mRNA 疫苗与免疫检查点抑制剂（Keytruda）构成正交协同：Keytruda 负责解除免疫刹车，而 mRNA 疫苗则在分子级别精准导航 T 细胞识别肿瘤靶点。 - `05:00` 黑色素瘤 2 期临床数据显示，mRNA 疫苗联合 Keytruda 治疗使患者 5 年无病生存率达到约 80%，在肿瘤临床上已被多位医生视作临床治愈。 - `16:05` 当前 3 期成功所依赖的算法（Intismeran 1.0）已固化运行 10 年，团队正全力利用全基因与血液数据及 AI 技术攻关算法 2.0，重点破解那 20% 无应答群体的耐药机制。 - `20:00` 与依赖活细胞体外扩增的 CAR-T 相比，mRNA 是纯粹的“信息分子”，制造过程采用微型反应器进行全合成水相酶促反应，无需大肠杆菌发酵或质粒制备。 - `22:30` 降低个性化药物固定成本的核心在于压缩机器在洁净室的占地面积和缩短生产周转周期，Moderna 马尔伯勒工厂完全投产后年产能将达数万剂。 - `27:30` 面对一人一药的制造特性，FDA 与 Moderna 采取了“工艺 BLA（Process BLA）”审评路径，核心是严格验证算法和合成管线在相同输入下产生完全一致输出的极致重复性。 - `30:00` 血液对比试验证实该疗法能在患者体内诱导产生治疗前完全不存在的全新 T 细胞（de novo education），为攻克 Keytruda 单药无效的胰腺癌和胃癌提供了全新机制依据。 - `30:00` 在 I 期肺癌等早期癌症中，Moderna 正在推进 mRNA 疫苗单药辅助治疗，力求在不引发免疫检查点抑制剂终身自身免疫副作用的前提下防止复发。 - `35:00` Moderna 正在将 mRNA 技术从肿瘤拓展至儿童罕见肝脏遗传病，并在实验室内探索利用免疫系统定向清除自身反应性免疫细胞的个体化自身免疫疾病疗法。 ## Detailed walkthrough ### `00:00` 突破肿瘤免疫瓶颈：个性化 mRNA 癌症疫苗问世 在这期 a16z 播客中，投资合伙人 Jorge Conde 再次对话 Moderna 首席执行官 Stéphane Bancel。两人上一次在 2020 年 12 月录音时，讨论的核心还是 Moderna 如何利用数字化平台以极快速度应对新冠疫情，那期节目被冠以“制造疫苗的机器”（The Machine That Made the Vaccine）。而到了 2026 年 8 月，Moderna 与默沙东（Merck）联合公布了一项重磅医学里程碑：双方合作研发的个性化黑色素瘤 mRNA 疫苗在 3 期临床试验中取得积极结果。这是肿瘤学界二十多年来，在经历了上千次癌症疫苗试验失败后，首个真正取得成功的癌症疫苗。 ```mermaid flowchart TD accTitle: 个性化癌症疫苗机制流程图 accDescr: 展示从患者活检、基因比对、算法筛选抗原，到合成 mRNA 训练免疫系统的完整流程。 subgraph Step1["1. 基因测序与比对"] A["患者肿瘤组织活检"] --> C["DNA 全基因组测序"] B["患者健康组织样本"] --> C C --> D["逐字母对比核苷酸变异"] end subgraph Step2["2. 算法筛选与 mRNA 定制"] D --> E["算法筛选关键突变<br/>（最多选出 34 个新抗原）"] E --> F["化学合成个性化 mRNA 分子"] end subgraph Step3["3. 免疫再训练"] F --> G["注射入患者体内"] G --> H["精确训练 T 细胞识别漏网突变"] H --> I["特异性清除黑色素瘤细胞"] end ``` 这种疗法的核心逻辑在于纠正人体免疫系统的“漏网之鱼”。人体内部随时都在产生癌细胞，正常情况下免疫系统能迅速识别并予以消灭；但当癌细胞逃逸后，单纯依赖常规手段很难将其清除。Moderna 的做法是通过对患者的肿瘤组织进行活检，提取 DNA 进行完整测序，同时对其健康体细胞进行测序，在单核苷酸级别逐字对比，再利用专有算法筛选出最致命、最具特异性的突变新抗原（最多编码 34 个突变）。将定制的 mRNA 注入体内后，便能直接训练患者的免疫细胞重新识别并靶向攻击癌细胞。因为不同患者之间的抗原重合度极低（约 90% 的所选抗原因人而异），这种个性化设计绝非边缘特例，而是整个疗法奏效的底层前提。 - 整个癌症疫苗研发领域探索已超过 20 年，此前经历了 1000 多次失败的临床试验。 - 该疗法是首个在黑色素瘤治疗中表现优于 Keytruda（帕博利珠单抗）单药疗法的药物。 - 该技术已将“从肿瘤活检到完成单人定制药物制造”的周期大幅缩短至约 42 天。 --- ### `05:00` 临床数据惊喜：5年生存率与正交免疫机制 在本次公布的 3 期临床试验首期中期分析（Interim Analysis）中，该疗法不仅提前达到了无复发生存期（Recurrence-Free Survival, RFS）这一主要终点，甚至提前达到了通常需要更长时间才能显现结果的次要终点——无远处转移生存期（Distant Metastasis-Free Survival, DMFS）。Stéphane Bancel 直言这一结果连他们自己都感到意外和振奋。此前在 2026 年春季 ASCO（美国临床肿瘤学会）年会上公布的 2 期临床数据显示，接受 mRNA 疫苗联合 Keytruda 治疗的患者，相较于 Keytruda 单药组，5 年无复发生存率降低了约 50% 的复发风险；在手术与治疗 5 年后，约有 80% 的患者仍维持无病生存（Disease-Free）。在肿瘤学领域，患者术后 5 年无病生存通常被临床医生视为已达到临床治愈（Cure）。 “It's the first time there is an agent in melanoma that is better than Keytruda alone.” Stéphane Bancel 这样强调这项成果在临床上的分量。目前 Moderna 正在全速与监管机构推进审批申报，目标是在 2027 年让该药尽早上市惠及患者，而位于马萨诸塞州的专属制造工厂也已准备就绪，攻克了为每位患者单独定制生产药物的工业化规模难题。 ```mermaid flowchart LR accTitle: 免疫检查点抑制剂与 mRNA 疫苗的协同机制 accDescr: 对比说明释放免疫闸门与定向精准导航的协同互补机制。 subgraph Keytruda["免疫检查点抑制剂（Keytruda）"] K1["阻断 PD-1 免疫抑制信号"] K2["『打开闸门放狗』<br/>（全面解除免疫抑制）"] K1 --> K2 end subgraph mRNA["Moderna 个性化 mRNA 疫苗"] M1["编码肿瘤特异性新抗原"] M2["『精准指认猎物』<br/>（分子层级训练 T 细胞）"] M1 --> M2 end K2 --> Combine["协同作战：解除抑制 + 精准打击"] M2 --> Combine Combine --> Target["高效杀伤肿瘤，减少脱靶误伤"] ``` 随后，Stéphane 深入拆解了为何单靠免疫检查点抑制剂 Keytruda 是不够的，以及两者的协同机制为何被称为“正交”（Orthogonal）： 1. **Keytruda 的局限与副作用**：如果将免疫系统比喻成猎犬，Keytruda 的作用本质上是“打开犬舍的闸门把猎犬释放出去”。根据既往 3 期临床数据，Keytruda 单药治疗黑色素瘤有 60% 的患者在 5 年后实现无病生存，但仍有 40% 的患者治疗无效。更棘手的是，免疫疗法带来的往往不是化疗或放疗那样的毒性，而是严重的自身免疫疾病（如 1 型糖尿病、红斑狼疮、克罗恩病等）。对于那 40% 无应答的患者来说，他们不仅未能控制癌症，反而平白承受了自身免疫疾病的痛苦。 2. **正交协同的底层逻辑**：早在 2015 至 2016 年 Moderna 与默沙东达成战略合作时，Moderna 就从研发传染病疫苗的经验中领悟到 mRNA 调动免疫系统的精确性。他们意识到不能只靠解除免疫系统的刹车（放狗乱咬），而是必须在分子层级精确教育 T 细胞“癌细胞究竟长什么样”。个性化 mRNA 疫苗将这套精准导航系统赋予被释放的猎犬，实现了与免疫检查点抑制剂机制完全互补、正交的作用通路。 ### `10:00` 为什么称作“癌症疫苗”以及 mRNA 技术的制胜机制 Jorge Conde 首先探讨了概念定义：通常人们提起“疫苗”，往往是指预防某种疾病的发生；但在这类试验中，患者本身已经罹患癌症，因此这种疗法并非预防癌症发生，而是“预防癌症复发”。对于临床干预而言，这本身就是一个非凡的概念。 Stéphane Bancel 赞同这种定性，并解释道，“疫苗”这一称谓并非 Moderna 首创，而是沿用了该领域上千次临床试验一贯的表述。无论是新冠还是流感疫苗，其核心都是在病毒感染前训练免疫系统；而在癌症场景下，人体内随时都在因外部环境或细胞复制错误产生 DNA 突变并形成癌细胞。通常情况下，免疫系统能及时发现并清除它们，但一旦肿瘤生长失控，就意味着免疫系统漏掉了关键信号。因此，该疗法的本质是“重新教会免疫系统去识别它遗漏的肿瘤信号”，本质上属于治疗性疫苗（therapeutic vaccine）。 针对该领域过去上千次试验均以失败告终、唯独 Moderna 与默沙东（Merck）取得突破的原因，Stéphane Bancel 指出了两大核心支柱：mRNA 底层技术与个体化设计。在 mRNA 技术层面，Moderna 早在 2015 年就与颁发诺贝尔生理学或医学奖的瑞典卡罗林斯卡学院（Karolinska Institutet）联合发表了研究：当将 mRNA 注射入肌肉后，它会迁移至淋巴结并进入关键的免疫细胞——抗原呈递细胞（APC）。mRNA 在 APC 内部直接翻译成蛋白，实现“从免疫细胞由内而外地呈递抗原”。这与以往采用重组蛋白或合成多肽的传统疫苗有着本质区别：后者注射后仅在血液循环中游弋，虽然能被免疫系统看见，却无法像 mRNA 那样直接在 APC 细胞内由内而外激活免疫应答。 ```mermaid flowchart TD accTitle: mRNA 与传统癌症疫苗抗原呈递机制对比 accDescr: 对比传统蛋白多肽疫苗在血液循环中被动接触免疫细胞，与 Moderna mRNA 进入 APC 细胞由内而外表达抗原的过程。 subgraph TRAD["传统方法（蛋白/多肽）"] T1["体外反应器合成蛋白/多肽"] --> T2["注射至体内进入血液循环"] T2 --> T3["在血液中循环游弋"] T3 --> T4["被动接触免疫细胞（表层识别）"] end subgraph MRNA["Moderna mRNA 机制"] M1["肌肉注射患者定制 mRNA"] --> M2["mRNA 迁移至淋巴结"] M2 --> M3["进入抗原呈递细胞 (APC)"] M3 --> M4["APC 细胞内部直接翻译抗原"] M4 --> M5["由内而外强效呈递给免疫系统"] end ``` - 过去癌症疫苗领域已进行了多达 1,000 多次临床试验，绝大多数以失败告终。 - 关键机制差异在于：传统蛋白/多肽疫苗在血液中被动循环，而 Moderna 的 mRNA 能直接穿透淋巴结并进入 APC 细胞，从细胞内部启动天然抗原表达与呈递。 --- ### `13:21` 从“共享抗原”转向“个体化定制”：90% 的新抗原不可替代 除了 mRNA 独特的细胞内抗原呈递机制外，另一个决定性突破是彻底打破“共享抗原（shared antigen）”的旧思路。过去临床常试图寻找不同患者之间的共有抗原，但癌症本质上是一种高度异质性的 DNA 疾病。随着过去 20 年间基因测序成本的大幅骤降，Moderna 转向了前所未有的全个性化路径：获取患者肿瘤组织的活检样本，读取其约 3GB 的全部基因序列，同时对其健康细胞进行全测序，进行逐字逐句、核苷酸对核苷酸的比对。 算法会从比对发现的数百甚至数千个突变中，筛选出免疫学意义最显著的突变，挑选多达 34 个新抗原并将其编码到一条完整的长链 mRNA 分子中，在约 30 天内完成针对该患者的专属药物制造，并送回医院进行肌内注射。Stéphane Bancel 强调，在 ASCO（美国临床肿瘤学会）公布并发表的 2 期临床数据显示（其机制同样适用于 3 期）：患者之间的新抗原重合度极低，大约 90% 的抗原在人与人之间是完全不同的。这证实了如果不采用单人单策的个体化定制，绝大多数患者将根本无法获得精准的免疫识别。 > “For the patient, actually, 90% of the antigen are different from a human to another one.” —— Stéphane Bancel --- ### `16:05` 解密黑盒子与算法迭代：当前的 Intismeran 是未来最差的版本 当 Jorge Conde 询问选择“最多 34 个新抗原”的背后依据以及筛选算法时，Stéphane Bancel 表示核心算法涉及高度机密的核心技术，但他透露了其研发脉络：起初他们整合了肿瘤免疫学领域前沿的公开数据库与文献，结合自身生成的大量内部数据，并与 AI 诊断、细胞治疗及 T 细胞谱系映射（T-cell mapping）领域的外部伙伴展开广泛合作来训练模型。 Stéphane Bancel 指出，当前公布的 3 期临床数据所使用的算法，其实与 2 期甚至 1 期完全相同，是一个已经固化运行了 10 年的算法版本（即 Intismeran 1.0）。尽管 2 期数据显示 80% 的患者在 5 年后仍保持无病生存，但仍有 20% 的患者无应答。现在 Moderna 已经获得了 3 期患者的全部样本、血液和基因测序数据，团队正在深度挖掘这些数据，力图找出应答与不应答的分子机制，并计划在获得充分科学依据后向 FDA 提交申请，将算法升级至 2.0 版本。他形象地比喻道：就像人们常开玩笑说“当前的 AI 是我们余生中能见到的最差版本”一样，现在的 Intismeran 同样也是未来医疗史上最简陋的一版。这不仅为那 20% 无应答的黑色素瘤患者带来希望，也为胰腺癌等传统免疫疗法难以攻克的冷肿瘤带来了攻关契机。 > “Well, it's exactly the same for Intismeran, which is the current version of Intismeran that Moderna [has] is the worst version of Intismeran you're going to see for the rest of medical history.” —— Stéphane Bancel - 在黑色素瘤 2 期试验中，接受治疗的患者 5 年无病生存率（disease-free rate）达到了惊人的 80%。 - 当前获益巨大的临床结果完全建立在 10 年前开发的第一代算法（Intismeran 1.0）之上，未融合过去十年间肿瘤免疫学的最新认知。 - 团队正全力比对 20% 无反应患者的组织与全血测序样本，探索算法向 2.0 迈进的安全升级路径。 --- ### `19:00` 工程学基因与单人单药（N=1）的超复杂供应链挑战 Jorge Conde 谈到了两人的深厚私交，笑称他们相识甚早（开玩笑说甚至追溯到幼儿园时期），并指出 Stéphane Bancel 从骨子里就是一个工程师，从 Moderna 创立第一天起就对流程优化、高效运营有着近乎偏执的追求。Jorge 指出，既然 90% 的患者新抗原各不相同，意味着商业化必须面对“为每一个单独患者定制一整套药品”的极端工程挑战。他请 Stéphane 深入拆解完成试验乃至未来商业化推进所需的庞大运营体系。 Stéphane 欣然回应，并对比了肿瘤领域目前另一类主流的个体化疗法——CAR-T 细胞疗法。以此为切入点，他开始系统剖析从患者活检、测序比对、mRNA 快速合成再到医院回输这一整套极其精密严苛的“N=1”工程供应链挑战。 > “And one thing that was true then is true today, is you are, well, first of all, you are an engineer at heart. And you have, from the very, very beginning, been obsessed with, with process, with operations, with being efficient.” —— Jorge Conde ### `20:00` 针头到针头周期：个性化 mRNA 癌症疫苗与 CAR-T 的本质区别 Jorge Conde 提到，CAR-T 细胞疗法通过取出患者的免疫细胞，在体外进行基因重编程，再输回患者体内以识别并攻击肿瘤，而 Moderna 的个性化癌症疫苗（mRNA-4157 / V940，即 intismeran）似乎也有相似的逻辑：从活检中提取肿瘤样本，为患者定制专属疫苗。因此，从活检到回输的“静脉到静脉”（vein-to-vein）周期至关重要。 Stéphane Bancel 澄清，Moderna 目前从活检到疫苗在医院准备好注射（needle to needle，针头到针头）的时间约为 42 天，未来通过自动化和机器人技术还将进一步压缩。与 CAR-T 相比，mRNA 疫苗具有根本性的不同：Moderna 根本不需要提取患者的免疫细胞在反应器中体外培养，所需要的仅仅是“信息”。 ```mermaid flowchart TD accTitle: mRNA 个性化疫苗全合成制造流程 accDescr: 展示从患者样本测序获取数字文件，到全合成酶催化生成 mRNA 纳米颗粒的过程。 subgraph S1["数据获取与数字化"] A["健康细胞测序"] B["肿瘤细胞测序"] C["生成数字序列文件"] A --> C B --> C end subgraph S2["全合成酶促反应"] D["无质粒合成 DNA 模板"] E["水相酶促转录 RNA"] F["脂质包裹 (LNP)"] C --> D D --> E E --> F end subgraph S3["交付终端"] G["个性化疫苗成药 (约42天)"] F --> G end ``` Stéphane 解释道：“正如你我讨论过的，mRNA 最美妙的地方在于它是一个信息分子。”（“As you and I talked about, the beautiful thing of mRNA is an information molecule.”）工厂接收到的只是健康细胞和肿瘤细胞的基因序列文件。基于这串信息，Moderna 不使用大肠杆菌或质粒生长繁殖，而是完全在水溶液中通过全合成、酶催化的化学反应合成 DNA 模板，再转录出 RNA 并包裹脂质纳米颗粒（LNP）。正因为这一过程完全合成且催化效率极高，它更像小分子制药，反应器体积极其微小；而 CAR-T 和重组蛋白技术依赖庞大的生物反应器，因为如果对活细胞压缩过度，细胞就会死亡。 - 针头到针头（needle-to-needle）全流程周期目前约为 42 天。 - 疫苗制造全流程为酶促、全合成水相反应，无需使用质粒（plasmid）或大肠杆菌发酵培养。 - 反应器微型化，摆脱了传统生物制药因活细胞密度受限而必须采用巨型反应器的物理瓶颈。 --- ### `22:30` 机器微型化与“占地面积”执念：从第一代冰箱到规模化工厂 为了在进入临床试验前实现“一人一药”，Moderna 早在临床一期前就必须微型化所有设备。第一代机器体积巨大，外形类似“一台巨大的美式大冰箱”。当时管理层对工程团队的要求是：优先保证产品质量和临床实验的确定性，不追求极端效率。“因为如果科学本身行不通，浪费五年去制造一台漂亮、惊艳、高度优化的机器人又有什么意义呢？”（“...because if it doesn't work in a clinic, what's the point of wasting five years making a beautiful, amazing, optimized robot, even science doesn't work, right?”）如果因为设备半吊子出现次品，导致临床试验得出假阴性结果，判定这一疗法无效，“那对人类而言显然将是一场灾难”。 当期中分析显示二期临床数据大获成功（目前已有表现极其优异的 5 年疗效持续性数据）时，Stéphane 意识到研发团队已经处于设备迭代滞后的幸福烦恼中。公司迅速抽调顶尖工程师，全力攻关设备的微型化与效率优化。 Stéphane 指出，降低个性化药物成本的核心是降低固定成本，而在洁净室（clean room）面积固定的情况下，单台机器的物理体积决定了产能上限： - 如果同一洁净室地表面积内能容纳 2 倍乃至 10 倍数量的生产单元，整体通量就会暴增，单次生产的固定资产分摊成本便会断崖式下跌。 - 团队严格围绕两大核心指标进行极限优化：一是周转周期（cycle time），周转越快，单套资产全年的产出频次越高；二是占地面积（平方英寸）。 - Stéphane 自嘲在工厂视察时“总是招人烦”，因为他会严查一切可以节省的空间，甚至将计算服务器移出洁净室，只为尽可能压缩机器体积，从而彻底击穿药品的终极生产成本。 --- ### `25:00` 产能规划与个人“极客模式”攻克癌症的局限性 在谈及马萨诸塞州马尔伯勒（Marlborough）工厂的产能规划时，Stéphane 透露，由于目前有 9 项临床试验正在同时推进，Moderna 已经生产了数千剂个性化癌症疫苗。马尔伯勒工厂完全投产后，年产能将达到数万剂级别；随着制造技术的持续优化，同一厂房的通量还将成倍提高，足以覆盖黑色素瘤的整体市场需求，未来也可以根据需要复制建造更多制造基地。关于药物的销售成本（COGS）和最终定价，Moderna 目前尚未对外披露，将等待公布完整临床数据并与支付方（医保及商业保险）充分沟通其临床价值后再做商定。 Jorge 提到 GitLab 创始人（Sid Sijbrandij）在确诊骨肉瘤后开启“创始人模式”（founder mode）、自己寻找定制方案的案例，询问未来这类超级极客是会求助于 Moderna，还是会长期存在分散的个体化自救现象。 Stéphane 明确认为，绝大多数患者最终都会选择 Moderna，因为工业化标准带来了不可逾越的安全与便利壁垒： - 注射剂产品面临极高的微生物污染风险，“如果你给某人注射的产品中哪怕只有一个细菌拷贝，都可能导致患者发生败血症（sepsis）”。 - 个性化定制涉及极其复杂的多步工序，手工或非规范环境极易出错；而 Moderna 经过 FDA 标准的良好生产规范（GMP）严苛验证，将风险降到了极低水平。 - 他打了个生动的比方：“当你在原始洞穴里、街上没有刀具店而你必须养活家人时，你当然会自己动手做第一把刀；但当街角开了一家能生产高品质刀具的商店时，作为人类，你就会把时间省下来去做别的事情。” --- ### `27:30` 监管破局：审评整个生产工艺，而非审评单一药物（Process BLA） 针对 Jorge 关于“每位患者的分子序列都不同，监管机构究竟审批什么”的疑问，Stéphane 解释了个性化医疗的监管底层逻辑：该疗法走的是工艺生物制品许可申请（Process BLA），而非传统单一产品的 Product BLA。 Stéphane 指出，CAR-T 疗法此前已经开辟了这一监管先例。Moderna 虽然已有 5 款采用传统产品审批路径上市的产品，但针对个性化癌症疫苗，从最早向 FDA 提交试验用新药申请（IND）开始，申报的就是“工艺 IND”（Process IND）。在过去近十年间，Moderna 团队与 FDA 保持了长期且高频的沟通： | 阶段 | 监管沟通与核准重点 | |:--- |:--- | | **临床申请期 (IND)** | 审核工艺安全性，评估系统是否具备足够的过程控制以安全开展一期临床试验 | | **二期临床结束会议 (End of Phase 2)** | 在启动各项三期临床前，与 FDA 逐一锁定研究方案设计及制造质控规程 | | **技术细节专题沟通** | 针对生产制造中出现的新技术难点，主动申请额外会议，向监管机构普及新知并获取指导 | | **工艺 BLA (Process BLA) 审评** | 验证整套算法、合成管线在输入与输出之间的极致重复性与鲁棒性 | Stéphane 总结了监管机构对于这一“黑盒”系统的核心诉求：“FDA 真正想知道的——这非常合情合理，换作为了我自己的家人我也同样会要求这点——就是：如果在前端输入相同的肿瘤和血液样本，在黑盒子末端制造出来的是否会是完全相同的产品。”（“Jorge, what the FDA wants to know, which is very legitimate, which I would want for my own family's sake, obviously, which is if you get the same sample at the beginning, the tumor, and the blood, so you get the same product make at the end of a big black box.”）Moderna 必须首先向自己、随后用完整数据向 FDA 证明整套流程的坚不可摧，确保相同输入必然产生相同输出。 ### `30:00` 个体化癌症疫苗的未来布局：超越黑色素瘤的三大战略方向 Jorge Conde 将话题引向黑色素瘤之外的广阔前景，询问该疗法能否广泛应用于各类癌症，以及癌症疫苗未来究竟怀揣怎样的宏大目标。Stéphane Bancel 表示 Moderna 的抱负极为宏大，因为他们已经在科学上证实了这项技术的核心能力。在当年的 ASCO（美国临床肿瘤学会）年会上，Moderna 展示了黑色素瘤患者接受治疗前后的血液对比分析，结果表明该疗法不仅实现了现有 T 细胞的扩增，更创造了在患者治疗前体内根本不存在的全新 T 细胞（de novo education of T-cells），精准识别 mRNA 所编码的肿瘤突变。正如 Stéphane Bancel 所说：“在我看来，我们已经向自己以及临床界证明了，Moderna 的 mRNA 技术能够教会免疫系统产生全新的 T 细胞去攻击体内的癌症。” 基于这一生物学机制的验证，Moderna 与默沙东（Merck）正沿着三大方向推动癌症疫苗从黑色素瘤（早期试验涵盖了 II 期、III 期和 IV 期患者）向其他癌种全面拓展： ```mermaid flowchart TD accTitle: mRNA癌症疫苗临床拓展三大方向 accDescr: 展示Moderna推进mRNA癌症疫苗的三大研发方向：与Keytruda联用、早期癌症单药治疗、以及突破非免疫检查点响应的难治癌种。 subgraph V1["方向一：检查点抑制剂已获批癌种"] A1["与 Keytruda (PD-1) 联用"] --> A2["正交协同效应"] A2 --> A3["肺癌 (III期) / 肾癌 (II期) / 膀胱癌 (II期)"] end subgraph V2["方向二：疾病早期单药治疗"] B1["I期肺癌 (吸烟者筛查)"] --> B2["术后 INT (mRNA-4157) 单药辅助"] B2 --> B3["避免免疫检查点抑制剂终身自身免疫副作用"] end subgraph V3["方向三：检查点无效的难治癌种"] C1["胰腺癌 & 胃癌"] --> C2["全新T细胞生成机制"] C2 --> C3["探索与其他正交机制药物联用 (如 KRAS 抑制剂)"] end ``` - **方向一：进军 Keytruda 已被证明有效的适应症**。由于 PD-1 抑制剂与 mRNA 疫苗的作用机制完全正交，二者结合能够产生强大的协同抗癌效果。Moderna 已针对肺癌开展 III 期临床试验，针对肾癌和膀胱癌开展 II 期试验，全面探索能否在 Keytruda 既有获批标准疗法的基础上带来显著的生存获益改善。 - **方向二：深入免疫检查点抑制剂难以涉足的早期疾病阶段，探索单药治疗**。Moderna 在 2026 年春季启动了一项针对 I 期肺癌患者的 III 期临床研究，评估其个体化产品（Intismeran / mRNA-4157）作为单药疗法的潜力。目前对于 I 期肿瘤，临床通常仅采取手术观察，避免使用 PD-1 等检查点药物，因为后者不仅并非人人响应，还容易引发严重的终身自身免疫病。若通过 X 射线定期筛查既往吸烟人群，在极早期发现肿瘤后行手术切除，并辅以副作用与常规疫苗相差无几（如仅有一天的轻微疲劳感）的 mRNA 单药治疗，将彻底改变早期癌症的治疗格局。 - **方向三：攻克免疫检查点抑制剂无效的高风险“冷肿瘤”**。尽管临床研究曾证实 Keytruda 在胰腺癌和胃癌中折戟，但由于 mRNA 疫苗具备诱发全新 T 细胞的独特机制，Moderna 坚信这一全新机制值得验证。此外，针对 Revolution Medicines 前一日获批的针对 KRAS 突变靶点的胰腺癌突破性新药，Bancel 强调将正交机制的靶向药与 mRNA 疫苗联用具有极强的科学合理性，这为攻克胰腺癌生存难题带来了全新的联合用药构想。 --- ### `35:00` 解析 20% 无应答者、AI 迭代与 mRNA 平台的下一座高峰：罕见病与自身免疫 展望未来，Stéphane Bancel 强调当前的成果还只是“Intismeran 1.0”版本。他正全力督促研发团队借助人工智能（AI）去分析海量的临床试验数据，重点钻研那些未能获益的群体。正如 Stéphane Bancel 所言：“我想死磕那 20% 在五年后依然没有响应的患者，搞清楚他们为什么没有响应，以及我们是否能对算法或底层技术做微调来帮助他们。” Jorge Conde 感叹 Moderna 展现了极强的平台延展性——一项最初并非为大流行打造的技术平台，在为全球数亿人提供新冠疫苗后，又成功反哺并加速了十年前立项的肿瘤治疗。Bancel 顺势透露了 mRNA 技术正在征服的后续垂直管线： - **罕见遗传病**：Moderna 预计在年内获得针对儿童罕见肝脏遗传病的关键性/晚期临床试验数据，其早期 I/II 期数据已显示患儿在用药三年后状态非常出色。 - **自身免疫性疾病**：在当年的科学日（Science Day）上，Moderna 正式宣布将 mRNA 平台全面对准自身免疫病。制药工业长期以来仅仅是在“对症治疗”以缓解患者痛苦，而 Moderna 凭借多年在传染病和癌症免疫调控中积累的深厚认知，致力于靶向自身免疫疾病的根本病因。 在被问及自身免疫疗法是通用型还是个体化时，Bancel 透露双管齐下：既有适用于所有人的通用型管线，更有令他兴奋的、尚在实验室探索阶段的个体化自身免疫疗法——直接利用免疫机制精准定位并消灭体内那些攻击自身组织失控免疫细胞，从根本上逆转疾病。节目最后，Conde 热情相约未来录制播客第三集以完成“传染病—肿瘤—自身免疫病”的三部曲访谈，并在节尾附上了 a16z 的官方合规投资免责声明。 ## Notable quotes > `30:00` 我们已经向自己以及临床界证明了，Moderna 的 mRNA 技术能够教会免疫系统产生全新的 T 细胞去攻击体内的癌症。 — Stéphane Bancel > `35:00` 我想死磕那 20% 在五年后依然没有响应的患者，搞清楚他们为什么没有响应，以及我们是否能对算法或底层技术做微调来帮助他们。 — Stéphane Bancel ## Mentioned Stéphane Bancel, Jorge Conde, Moderna, Merck, Keytruda, Intismeran, mRNA-4157, V940, ASCO, FDA, Karolinska Institutet, Revolution Medicines, GitLab, Sid Sijbrandij, a16z ## Video description a16z General Partner Jorge Conde sits down with Moderna CEO Stéphane Bancel to discuss a major milestone for mRNA technology: positive Phase 3 results from Moderna and Merck’s individualized treatment for melanoma, after more than a decade of work on personalized cancer vaccines. Stéphane explains how the treatment works by sequencing an individual patient’s tumor and healthy cells, identifying the mutations most relevant to their cancer, and encoding up to 34 of them into an mRNA designed specifically for that patient. Rather than simply unleashing the immune system, the goal is to teach it exactly what to recognize and attack. They also unpack the engineering challenge of manufacturing a different medicine for every patient, how Moderna has brought the process down to roughly 42 days from biopsy to treatment, and what it would take to manufacture personalized medicines at scale. Finally, Stéphane looks beyond melanoma to lung, kidney, bladder, pancreatic, and gastric cancers, as well as Moderna’s longer-term work applying mRNA to rare genetic and autoimmune diseases. [Source](https://mgln.ai/e/1344/afp-848985-injected.calisto.simplecastaudio.com/d1df597a-30d8-4cae-bb4c-22a8ec496e6d/episodes/13517b9d-37c2-4bce-9066-1221f8aa9119/audio/128/default.mp3?aid=rss_feed&awCollectionId=d1df597a-30d8-4cae-bb4c-22a8ec496e6d&awEpisodeId=13517b9d-37c2-4bce-9066-1221f8aa9119&feed=BXDamaKF)

[30:00] Stéphane Bancel: 我们已经向自己以及临床界证明了，Moderna 的 mRNA 技术能够教会免疫系统产生全新的 T 细胞去攻击体内的癌症。 [35:00] Stéphane Bancel: 我想死磕那 20% 在五年后依然没有响应的患者，搞清楚他们为什么没有响应，以及我们是否能对算法或底层技术做微调来帮助他们。

[0:00] It's the first time there is a cancer vaccine working. The field has been doing that for 20 plus years, more than a thousand clinical trials that have all failed. What was different this time? What is it about mRNA technology that enables the immune system to learn in a way that other approaches were unable? We all have cancer cells all the time in our body. Our immune system is very well trained to basically notice those cancer cells very early and get rid of them. then the question is how can you retake the immune system? We're going to basically take a biopsy of your tumor. We're going to read all the letters of its DNA. And then we're going to do the same things with a healthy cell of your body. And we're going to literally compare letter by letter, nucleotide by nucleotide. And then we're going to use an algorithm to identify which one of those mutations are the most relevant. And so when this is injected in your body, it teaches the immune system the signature of your cancer cell that it missed. What gets regulated here? Because every dose is different. Basically, what the FDA wants to know. the company was already working toward another goal: using mRNA to fight cancer. A decade later, That bet has reached a major milestone. A-16Z general partner Jorge Conde sits down with Moderna CEO Stefan Banzel following positive phase 3 results from Moderna and Merck's individualized mRNA treatment for melanoma. It's the culmination of a project Moderna has been working on for roughly a decade. Stefan explains how Moderna takes a patient's tumor, sequences it against their healthy cells, identifies the mutations unique to that cancer, and uses that information to manufacture a to attack. And because roughly 90% of the selected antigens differ from one patient to another, personalization isn't an edge case. It's fundamental to how the treatment works. They also get into the extraordinary operational challenge behind this. How do you manufacture thousands of different medicines, one patient at a time, quickly and reliably enough to make personalized medicine work at scale? And finally, they look at where Hi, welcome to the A16Z podcast. I'm Jorge Conde, a general partner on the A16Z BioN Health team. I am thrilled today to welcome back Moderna CEO, Stefan Bancel. For folks that have been long-time listeners may recall... Stefan joined us on the A6 and Z podcast back in December of 2020. when we were talking about all of the work Moderna did to bring us the mRNA COVID vaccine. And at the time, if you can go back and listen to that episode, you'll hear how quickly, Moderna was able to, to react to the existence of the virus to analyze it, to essentially print a vaccine that would protect people against the COVID-19 vaccine and hence put us in a much better position with respect to the COVID pandemic. We titled that episode, The Machine That Made the Vaccine. And the reason why we're talking again today in August 2026, is because Moderna... has put out news on a really big advancement on what they can do with mRNA technology. when it comes to cancer. And so I want to hand it over to you, Stefan. Again, a very big welcome. Thank you for coming back. But maybe the place to start is let's lead with the news. Moderna and Merck announced earlier this month in August that you had conducted a phase three clinical trial in melanoma and have gotten very encouraging results. So why don't I hand it over to you and tell us, what have you announced? What have you seen in this phase three trial? And then I do want to dig in into what Moderna is doing in cancer. Wonderful. So, Roy, thank you so much for having us back. We're very happy to be with you. So, indeed, last week now, We shared the news with our colleagues at Merck that after working 10 years, on an individualized treatment against cancer using mRNA technology, that the phase three was positive. It's a first of many. It's the first time that there is an agent, in melanoma that is better than Ketudra alone. So it's a big deal for patients, of course, with melanoma. It's the first time there is a cancer vaccine working. The field, as you know, has been doing that for 20 plus years, I think more than a thousand clinical trials. That's how it all failed. And if you look at the phase two data, because what we announced last week is that we met the primary goal. and part of a study which was Recurrence-Free Survival, I hate people having the cancer back or dying that we met. And then to our own surprise, because this was [5:00] The first interim analysis. This is not the end of a study. It's the first interim analysis of a study. And what was a surprise event to us is we met the secondary endpoint, which was distant metastasis-free survival. which is, of course, takes more time to mature because it means that you have distance metastases from your primary tumor. And we also made that endpoint, which was great. Again, unexpected from our side, but again, means it is really good. We will share the data very soon at a big medical oncology conference, which is what the field does. But just to give you a sense, maybe to orient kind of directionally, We showed at ASCO, the big oncology conference in the spring of 2026, a few months ago, that our phase two study, which was also randomized against Ketudra alone, So the same type of study showed That's the wrong... 50% of people had recurrence-free survival versus people only getting ketudra. And this is five years after treatment. And as you know, in oncology, five years is considered by a doctor like a cure. And so it's a big, big deal. And if you look at the data from, again, that phase two, you had around 80% of people that were disease-free five years after their treatment and their surgery. of melanoma. And so we're very excited about what it means for the field. We are working very hard already with regulators to file So the drug can be available to patients as soon as possible. And we hope in 2027, and then we're going to try to make it as fast as we can. The factory is ready in Massachusetts, but we have figured out how to make and scale a product for every human being at the time. I mean, there's so much to unpack here, so this is an extraordinary advance for the treatment of, in this case, melanoma and hopefully over time, cancerous more broadly. So let's unpack some of this if we could, Stefan. The first one, for folks that are less familiar with with cancer treatment. What is Keytruda and why is Keytruda alone not sufficient? Why was this particular mRNA cancer vaccine necessary in conjunction with Keytruda? Sure. So if you look at Keytruda, which is kind of one of the leading immunotherapy that people might have heard of, is basically, if I oversimplify for non-biologists, it's basically a molecule that basically opens the gates for letting the dogs out that are going to go and attack your cancer from your immune system, if you want. The thing about checkpoints is when they work, they are fantastic because those people, five Bye. cured in the sense of not remaining disease But... Only 60% of people are This is free after five years. If you look at the... phase three published data of Ketudra. So again, for those 60% of people, it's amazing. But it means that there's 40% of people where you go through a treatment, you're fighting for cancer, and the treatment doesn't really work for you. And also what is difficult is those three beds are wonderful, but a lot of time come with very serious side effects. Very different from chemotherapy or radiotherapy. The side effects of immunotherapy are mostly immune diseases. So you see people, if you look at the label of clinical studies, People that get checkpoints, whether it's K2DRA or any other type of checkpoints from other companies, They end up having type 1 diabetes, lupus, Crohn disease, these type of things. Of course, it's better to have those diseases than, of course, being dead from your cancer, which is why those have become standard of care. But think about those 40% of people who don't respond to checkpoint. They get an autoimmune disease most of the time. and they don't get the benefit of a medicine. And so what we try to do with Merck And it's really a technology that emerged from Moderna Labs back in 2015, 2016, when we did a partnership with Merck, as we were looking for. one of the best companies in immunotherapy to partner and to have a complement approach. The idea that we have at the time using our infectious disease learning from our infectious disease vaccine, we learn a lot about the immune system and how mRNA interacts with the immune system, we thought we could develop a mechanism of action that was totally orthogonal, very different. from immunotherapy. because you will be able to start from a sequence of your tumour, So that we could design a product to basically teach, if I go back to the dog analogy, To teach those dogs... what to look for. very specifically. And that's really the beauty of our technology is if you think about K2D, it basically unleashes the dogs. but they go a bit randomly sometimes. It's your immune system. Whereas, More than a product is able to molecular level. inside your immune system, to very specifically teach your T-cell, this is what you need to look for. And that thing is actually on your cancer cell so that those T cells go and basically attack your cancer cells. Okay, so now that's where the personalized cancer vaccine technology will make a big impact on the treatment of melanoma. We'll come back to the personalized piece because I think that's just fascinating, not only [10:00] from a technological standpoint, but just from an operational standpoint. So I do want to come back to that. But let's focus on the word vaccine. So typically, when you think of the word vaccine, it is to prevent a disease. Here, in this context, these patients already have cancer. So in a sense, you are preventing something. You're not preventing the cancer. What you're preventing is the return of the cancer, which is in and of itself an extraordinary thing to think about from a therapeutic intervention perspective. So number one, is that a fair characterization? That's a fair characterization. And the reason the field has used the word vaccine, it was not us using it, we just followed the field. As I mentioned, there's been a thousand plus clinical trial. It's because it's about teaching your immune system. If you think about a COVID or a full shot, you teach your immune system before you get the virus infecting your body. Here, you teach your immune system, not about the virus, but about basically the cancer signal that your immune system missed. Because what we know today in the field is that we all have cancer cells all the time in our body, whether it's outside factors or just as you have cell replication and you have mistakes that happen that create mutations of DNA that are cancer cells Our immune system is very well trained to basically notice those cancer cells very early and get rid of them But if your cancer grows then the question is how can you reteach your immune system? So I think that's why the field use award vaccine for that approach as well. Even as you said, it's a therapeutic treatment approach post-cancer. It's about the teaching of the immune system. Okay. And so as you point out, the field has tried this many time to afford. On the order of a thousand clinical trials have tested this theory. They've all failed. You and Moderna and Merck have succeeded here. What was different this time? What is it about mRNA technology that enables the immune system to learn in a way that other approaches were unable to be successful? Yeah, I think there are two components. One is the mRNA technology and I think the other one is the individualization by designing a product for one human at a time. So let me go through those two. On the technology of mRNA side, what we have known and published actually with Karolinska as you know the institute in Sweden that gave the Nobel Prize of Medicine back in 2015 is that with all technology I cannot speak about other mRNA companies that have different mRNAs different lipids and so on but with all technology when we inject our mRNA in the muscle whether it's a COVID shot, a flu shot, or this cancer treatment, basically the mRNA goes down to your lymph node and enters the APCs, the antigen-presenting cell, which, as you know, are key components of your immune cells, and the mRNA gets inside the APCs. This we've demonstrated and proven at the time of Karolinska. And then it basically translates the message contained in the mRNA inside the APCs, inside your immune cells and presented from within. So I think it's a very important differentiation from most of the previous vaccine in cancer in the field that were made by protein or peptide that basically are made in reactors are injected in the patient. but they basically turn into the blood because as you know recombinant or protein when you inject them, they just go into your blood and they turn around. So your immune system sees them but not in the same manner from within as it's done with the mRNA. So we think that one very important component of immune presentation if that makes sense The other component is really the individualization In the past a lot of times people have tried with non i protein taking a review of peptide but also we tried a shared antigen Whereas here what we said is because cancer is a disease of DNA, what we're going to do here, because the cost of sequencing has dropped so much in the last 20 years, is we're going to basically take a biopsy of your tumor. We're going to read all the letters of its DNA, the three gigabytes of its genes. And then we're going to do the same things with a healthy cell of your body. And we're going to literally compare letter by letter, nucleotide by nucleotide. And then we're going to use an algorithm to identify of your hundreds or thousands of mutations, which one, based on the current knowledge of a field of immunology in cancer, which one of those mutations are the most relevant. We select the 34 that we believe are the most relevant and we stitch them together into one big mRNA molecule, which we make in 30-ish days for you, that is injected in a hospital intramuscularly. And so when this is injected in your body, basically it teaches the immune system the signature of your cancer cell that it missed, not the signature of every other patient with a shared antigen, [15:00] with a very specific signature, of your cancer cell. And what we showed at ASCO and we published, from a phase two study, but we believe it's the same thing in the phase three. because it's mechanistic. is at around 90, 90% of the antigen. are different patient to patient. Because when we started, we had no idea because, again, the field came from shared antigen. So when we started, we were like, we have no idea. We're going to get 2%, 5%, 90% of the same antigen across the field. For the patient, actually, 90% of the antigen are different from a human to another one. Wow. So the only way this can work is through personalization. We can individualize, exactly. You know, assuming that carries over. And so in that regard, uh, uh, You know, if you're doing, let's say, this normal to tumor comparison of the genome, you find the differences. I'm curious how you arrive at 34 is up to 34 is the right number. I'm sure there's a very good reason for that. But what is the algorithm that enables you to do that? Is this something proprietary to Moderna? Is this something that is known within the field? Help us understand, help us look into that black box. Sure. So I want to share a little bit about the black box, not too much because there's a lot of know-how and things are very confidential to us. But basically, we started with, of course, what is known in the field. And so we basically use a lot of database and publication and a lot of scientists and doctors to kind of best in class in immunology and in oncology. And then from that starting point, we use a lot of internal data that we generated over time. We also partner with some companies that because they are in the diagnostic space, of AI, let's say cell therapy and other space in oncology, had access to a lot of data, a lot of T-cell mapping and so on. That's why they're useful. for the learning. The thing that is interesting about the data we shared last week is this is what I consider... in Tizmoran version 1.0. because the algorithm from a phase three, was the same from a phase two, was the same from a phase one. But because we've been doing this for 10 years, it's a 10 year old algorithm. So as you look at the data, it works pretty well, right? As we said about the phase two data, 80% of people are disease-free after five years. It's amazing for those patients. But there are still 20% of patients that don't respond. And so one other thing we're going to be doing now that we have access to a phase three patient data and samples. is to go back and mine that data. to figure out why some patients responded And why some of our patients did not respond because we have access to all their blood samples, the sequence, everything. And when they try to see, can we improve the algorithm? And we will go to CFDA if we find... scientific reason why we should change the algorithm to go from, let's say, 1.0 to a 2.0 algorithm, and then change it. Of course, we have to do that in a very controlled way to ensure we don't lose efficacy. very obviously. But the way I think about it is like when we talk about AI, we always joke that the current version of AI is the worst we're going to see in our lifetime. Well, it's exactly the same for Intismerine, which is the current version of Intismerine that Moderna is the worst version of Intismerine you're going to see for the rest of medical history. And so that gave me a lot of hope, not only in melanoma for those 20% of patients that don't respond, but also for potentially over tumors that have been really hard in the field like, you know, pancreas cancer and others where immunotherapy doesn't work. We want to be able to learn a lot about the technology using also what the field has learned in the last 10 years, because the field has learned a lot, as you know. This is even not in Intisperine 1.0. So that's why I'm so excited about what's coming next. That's fantastic. So, um, Looking back, uh, You and I have had, we've known each other for a very long time. I won't depress you or me by saying how long. But you were very young, you were in kindergarten. So I've had the benefit of seeing Moderna from the earliest days. And one thing that was true then is true today. is you are, well, first of all, you are an engineer at heart. And you have, from the very, very beginning, been obsessed with, with process, with operations, with being efficient. And those things need to be absolutely true. If you're going to attempt to do what you're trying to do here with personalized cancer vaccines and make a medicine for each individual patient, precisely because in 90% of the cases, there's no overlap in terms of the antigens. Can you talk us, walk us through a bit the operational lift that is required here that you've already had to do to even run the trial, but that you would have to do if you eventually commercialize this product? Sure. And let me, maybe one way to frame it is, I think a lot of people think about the other big personalized therapy that exists in cancer is CAR T cell therapy, right? And in that case, the thing [20:00] and CAR T-cell therapy for folks that may not be familiar is this idea of, that you take a patient's tumor, and then you take the patient's immune cells You take them out of the body, And you essentially reprogram the immune cells and re-engineer them to be reactive to the tumor and put them back into the patient. I'm oversimplifying, of course. But that's CAR T cell therapy in a very sort of simple nutshell. In this case, you're doing in some ways things that are very similar, right? You're taking a piece of the tumor that you have in the form of a biopsy, presumably. specific to that patient's tumor. How do you think about essentially the vein to vein time? Like what needs to be true from the moment you sort of see a patient and get access to the tumor to the moment that patient receives their personalized vaccine? Sure. So the time is around 42 days now, needle to needle. So from taking the biopsy to getting the vaccine in the hospital ready for you. I think we're going to be able to improve that as we still have a lot of efficiencies to work on and automations and robotics. the A place where this is very different from Cartier, is that We don't have to take your immune cells. We program them ex vivo in a reactor in our factory and send them back to your hospital. The only thing we need is the information. As you and I talked about, the beautiful thing of mRNA is an information molecule. And so basically what we get from the lab is the sequence of your healthy cells. and the sequence of your cancer cells. So we just get the file. And then we use that information to basically... Make the DNA. But now we don't make it with Plasmid. growing E. coli or whatever. We make it all synthetic. So it's all enzymatic in liquid, in water. Then we make the RNA from the template. Then we put the lipid around it. And because of that, and that it's a synthetic process, it's much more like small molecule. then a large molecule. If you think about CAR-T, for me, the analogy is the recombinant world. where you have cells and big reactors and you have big volumes. Because as you know, the reason you have big volumes in biotech industry is if you compress the cells too much, they die. You have the same issue with CAR T. So everything is big. Whereas here, because it's all in water and it's all enzymatic, meaning it's very catalytic, the reactors are very, very tiny. And so what we've been doing since before the clinic, because as you said, we had to start developing the technology to individualize it, one human at a time, to even do a phase one study, right? Is we shrunk everything down. So the first version of a machine that looks like a big American fridge was a bit big and cranky because we told the team, make it good enough so you have good quality. But we're not serving for efficiencies yet because if it doesn't work in a clinic, what's the point of wasting five years? making a beautiful, amazing, optimized robot, even science doesn't work, right? So we told the team, make it good so that we have no quality issue and we don't have a false experiment, a false negative in the clinic, because it would be terrible for patients if you build a robot kind of working but not working. You run the study and it tells you the science doesn't work and you don't. If it should have worked, right, that would be a disaster for humanity, obviously. And so the team did exactly that. They developed a robot. That was good in terms of quality, but it was not very efficient. And when we got the phase two data, that this was working. The first interim of phase two data at only two years. Now we have five years of data maturing beautifully for duration of efficacy. We told the team, "Okay, now we're behind." I knew this was going to happen in case of success, which is a happy program. And so we dedicated a lot of very smart engineers to think about, okay, now how do you make a very efficient machine that you can compress even the volume of a machine? Because one of the important vectors, of course, is time, as you mentioned, cycle time from needle to needle, but also cost. And so one way to reduce the cost is reduce the footprint on the floor. Because if you have a fixed envelope of a clean room, facility and you can put a 2x or 10x more machines in that soft face area, Of course, you're going to get a bigger throughput and a much lower price on your fixed cost. And so we are obsessed about... cycle time. Because the more you can reduce cycle time, the more you can get a turnaround, let's say, in a year. on your assets. And the second vector I'm obsessed about is square inches. Literally, I'm always a pain in the butt, sorry, when I go to the factory to look at all the space we can save, how we can be creative, how even we can move some compute out of the clean rooms just to shrink things as much as you can. It's got a huge impact on cost of the product at the end of the day. [25:00] and had, um, at scale, um, How many eat? Roughly, let's just focus on melanoma. How many doses would you need to produce in a given year? So we've already got thousands of doses because of nine clinical studies that are ongoing. The facility will be able to make the one in Marlborough, Mass., at tens of thousands of doses, And then as we keep improving the technology, that number is going to go up in the same facility. And then we might need to build several other facilities. But if you look at the incidence of melanoma, if you're in a tenth of a thousand of doses, you're going to cover... You're going to easily leave them in the middle of my market. Yeah, I can believe that. Have you disclosed how you think about cogs and price, or is that something that— We have not disclosed yet. We need first to disclose the data. We want our colleagues. We need to engage with the payers once we can share the data with them in terms of what is the value being driven there and so on. But this has not been discussed yet. So maybe one place to focus is on this concept of personalization. I'm sure you've seen the story of the GitLab founder who went founder mode on his own osteosarcoma. Number one, uh, Do the future of the future? SIDS OF THE WORLD. Um, come to Moderna? Or is this end of one phenomena something that you think will just happen and exist in parallel? So I think they will come most of them to Moderna. Because he will just going to be easier and safer. Because as you know, Making an injectable product always carry risk. of contamination of a product. If you inject to somebody a product that has even one copy of bacteria you might give the patient's sepsis, then you always have a question of quality because when you have a multi-step process, a mistake can happen. And of course, if it's industrialized, and has been validated in terms of good manufacturing practice, kind of FDA standard, you have much less chance of this happening. So it's a bit like every tool in life, which is, you know, do you make your first knife because there's no knife store and you are in a cave and you need to feed your family? Yes, of course, you make your first knife because you have to feed your family, right? But when you have a store making high-quality knives down the street, you're going to use your time to do something else. So I think it's a bit of the same phenomenon, which is like in any technology, which is when you have industrial scale, of high quality product You use your time as a human to do something else with your time, right? And in that world, how does the regulatory apparatus function here? So in other words, You mentioned earlier, you along with Mark will prepare a regulatory filing soon. What gets regulated here? Because every dose is different, so obviously every dose doesn't get approved. Is it Is it obviously the process for synthesizing mRNA? Is it the algorithm? Is it a combination of the entire system? Help us understand that and build intuition around how we think that these kinds of personalized medicines will be regulated in the future? Yes. So the good news is there are precedents. As you mentioned, CAR-T. CAR-T was also approved in the same way as we believe Intismeran will be, which is as a processed BLA, not a product BLA. So as you know, Moderna has five products approved. So... That's really product approval. On this one, the whole process since we started in the clinic, the IND was a process IND. because we had to ask the FDA, can we go to the clinic? Do you think it's safe? And do you think we have a good control of the process so we can do safely a phase one study? So we already had that discussion just to go into the clinic years ago. And then before we started every phase three, we need to have end of phase two meeting and And agree with design. of a study the manufacturing protocol with the FDA. So those discussions have happened for years. And so it's not like we have not talked to FDA for the last 10 years and we're going to show up at their front door in a week or two and tell them this is a new product. And they're going to go, why is this? There's been a lot of discussion, a lot of engagement. Several times we've had technical questions on the manufacturing front where we basically requested additional meetings to ask the guidance to also educate them on the technology, what we've learned and so on. So there's already been a lot of discussions. And... there's a very clear regulatory pathway in terms of approving the entire process. Basically, Jorge, what the FDA wants to know, which is very legitimate, which I would want for my own family's sake, obviously, which is if you get the same sample at the beginning, the tumor, and the blood, so you get the same product make at the end of a big black box. And that's what we have to demonstrate first to ourselves, and then with the data to the FDA, so that we have really robustness of the whole process. So if we have the same input, we're going to get the same output going [30:00] to patient as an individualized medicine. How do we think about moving beyond, or how do you all think about moving beyond melanoma? Is this an approach that's going to be applicable to a broad range of cancers? Are there cancers that are much more likely where this is going to be a viable option versus others? And sort of what's your, I'll use the word, what's the ambition here for where cancer vaccines can have an impact? So the ambition is pretty big because we believe... We have demonstrated that at least to ourselves and we hope to the world, there's always be skeptics, but that's always true, that... We are able to to create a de novo education of T-cell. And this, we showed it even at ASCO this year, where we took the blood process, before treatment, after treatment, of cancer patients, melanoma, we were technology. And we showed that I don't think we have an expansion of the T-cells. But we have de novo, so new T cells being created that recognize what we code in the mRNA that was not in the patient's body before the treatment. So we already In my book, I've proven to ourselves and to the clinical community that modernized amount of technology can developed teach the immune system to develop new T cell to go attack your cancer. So based on that, they are basically I would say three different vectors we're going after in terms of expansion from melanoma. So this study, to remind people, was a cancer patient in stage two, stage three, and stage four. that were enrolled in that phase first study. So what we're doing is we're going first everywhere where K2DRA works. Because as I told you, we believe the mechanism of action of a PD-1 and a PD-1, modern Aetis Moran are totally orthogonal. So we think these allow to have synergistic elements. and performance of efficacy for the patients. And so we are in phase three for lung. We're in phase two for kidney cancer, bladder cancer. So we have a whole slew of studies ongoing where the world knows that Ketudra works because Ketudra has been approved there. And we believe you're going to see a material improvement versus Ketudra alone. Before you run the clinical experiment, it's impossible to know are you going to get 50% like we saw in the phase two of melanoma, or you're So these are a lot ongoing. The second vector is, is to go early in disease, Where Checkpoint work? And the best example is we announced in the spring of 2026, starting a phase three study. For patients with stage one lung cancer. But as Intismarine, so Moderna's product, as a monotherapy. Without checkpoints. And we are doing that because we believe when you go early in disease, Checkpoints are not used because of a side effect that they bring. Uh-huh. Because if you have stage one cancer, The medical field thinks it's worth monitoring your cancer versus giving you a checkpoint because, Not everybody is going to respond. But everybody's going to get pretty serious lifelong side effects, like autoimmune disease. But what if you could have an mRNA made for cancer patient that has lung disease, stage one, which you can find easily with x-ray, let's say, in former smokers. It's the easiest target population. Just screen regularly with x-ray your former smokers. And if you do it regularly, you're going to go from not seeing the cancer to seeing the cancer. And then the idea is, do you do a surgery, which is to the side of care? and you give intismarine monotherapy. which the side effect is similar to a vaccine. You know, you might feel tired for a day, but that's it. So in cancer, it's a pretty cool type of side effect, right? And that's another approach we have in terms of clinical studies. where checkpoints are not available today. The third vector is where checkpoints don't work. So, of course, it's where you have a highest risk. But because the mechanism of action is different from a checkpoint, We and Mark, believe that there is a very good scientific rationale to go try. So two places we are trying right now is pancreas cancer, and also gastric cancer. Those two cancer type checkpoints and K2-rad do not work. The clinical studies have been run in the past. And they were negative. But we think because, again, the mechanism of action is different. from checkpoint. And we know now that we have a proof that we can create de novo T cell. We think it's an experiment worth running. If we have good signal, we'll think about combination. As you know, literally yesterday, you know, Revolution Medicine had a wonderful new medicine approved for pancreas cancer using the CARAS mutation. What if you could combine that medicine and intismaran? Those are very orthogonal. mechanism of action. For me, it makes no scientific sense that if it doesn't work, and we should not sonno. [35:00] in pancreas cancer, by itself. And of course, the revolution of medicine those great improvement of survival in pancreas cancer. If you combine those two things, we believe it should have benefit. Again, you need to run the clinical experiment to see how much, but that's the type of things we're going to want to do. So if you think about In this modern medicine, it's going to be used with keturon. It's going to be used early in disease work at the dry, and it might be used In places where K2J doesn't work, But with other agents. Well, that gives a lot of reason for, I think, cancer patients and their families to have a lot of hope for the future of novel therapies in this field. And on top of what we just said, remember, this is Intismeran 1.0. So what I saw is very powerful and I'm really pushing our team. to think really outside the box and to do a lot of analysis and to use AI to look at that gigantic set of data that we have, which is, What are the things we can learn from the clinical studies? to understand about the people that did not respond. Because I think you always learn more from things that don't work. Anything that work? So I want to obsess about the 20% of patients that do not respond five years out so we can understand why. They did not respond. And can we tweak anything in the algorithm or in the technology? to be able to help them. Well, that's remarkable. And I, Just to wrap, I think It's remarkable to see how you were able to take a technology platform that originally wasn't built, for a pandemic. Um, pointed at a pandemic, create a vaccine for millions and millions and millions of people, and essentially point it back towards treating some of the diseases that you had originally intended 10 years later, as you described. Yes, it's really remarkable. And the piece that's going to be exciting, maybe to close, is before the end of the year, we should have our pivotal studies or late-stage study, for rare genetic disease for kids that have rare genetic disease of the liver. So it's another vertical at which we're pointing the technology. The phase one, two, I've shown kids three years on drugs doing fantastic. So we'll see when we get that data. And in June, we had our annual science day. And we announced that the next mountain where we are pointing on mRNA platform is autoimmune disease. Because if you think about it, We've learned a lot from infectious diseases which are mediated by the immune system. cancer, we've just been talking a lot about immune system. So we learned so much about the immune system that we think we have some very novel approach. on how to treat the root cause of autoimmune disease, not the symptoms, which is what the pharma industry has been doing. It's, of course, very helpful to patients to treat the symptoms so they can have higher quality of life. But it doesn't treat the root cause. And we think we might not find ways. to use the immune system to treat the root cause of autoimmune disease. So there's still a lot of ways to point the platform. So we're quite excited about what's to come. Would the theory there be that you'd have of personalized autoimmune modulators. Or would this be more product or more process? So we're doing both. So what we presented in the spring was a product that would be the same for everybody. But what I'm most excited about, which is in the lab still, is the ability to do individualized autoimmune treatment where you target directly to the immune cells that are attacking your body. as self when you have an autoimmune disease and who are basically part of your immune system going attacking those immune cells that are out of order so that you are able to take the symptom of the immune disease out. Again, it's still early days, but that's what I'm excited about today. Well, going from infectious disease to cancer to eventually autoimmune disease, we would love to have you back on the podcast to film episode three and complete the trilogy when you're ready. Thank you so much for joining us on the A16Z podcast. It's always, as always, it's great to see you. And congratulations. Thanks again for listening, and I'll see you in the next episode. and is not directed at any investors or potential investors in any A16Z fund. Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details, including a link to our investments, please see A16Z.com forward slash disclosures. [40:00] . you Thank you.