GLP-1、肽类与万亿美元健康革命
- 押注生物科技20年后,Cornell称2025年“可能是我整个职业生涯中最令人兴奋的一年”——原因不只是收入,更在于商业验证。 GLP-1药物年收入将“轻松超过1000亿美元”,这正是他所描述的、一次性削减年度医疗支出万亿美元的健康革命“我们已经准备好了”的首次商业证明。
- 真正重排资金流向的判断是:顶尖科学家已经破解了保护我们免受大多数致命疾病侵袭所需的大多数药物。 自抗生素、疫苗和卫生条件带来上一次跃升以来,预期寿命曲线几乎没有变化;因此,缺口在于让现有药物触达更多人,机会不在新靶点,而在复杂性、成本和依从性。
- 2025年华尔街低估的发现,是药品的价格弹性。 复方GLP-1价格约为品牌药每月400–500美元的一半,通过 Hims & Hers 等渠道吸走了处方市场之外15–20%的需求;月费150美元的口服 Wegovy 上市初期相对推进速度约为 Zepbound 的4倍,几个月内就把市场从每周新增20万张处方推到30万张。
- 他对减重药竞赛的逆向判断是:追求更大幅度减重是错误目标。 “人们并不是在解决这枚巨型火箭筒”——他们要的是耐受性和可持续使用,因此真正的制胜区间是 BMI 40以上,以及更长的给药间隔,而不是最大药效;Pfizer收购的资产可能按月给药,Amgen则在推进从月度到季度给药。
- PCSK9才是真正的免费午餐,最终规模应该超过GLP-1。 天生不产生该蛋白的人群,终生心血管疾病风险降低88%;已获批药物可将 LDL 降低50%,将事件风险降低20–25%。它如今落后,只是因为“你什么感觉都没有”——胆固醇是“一个在后台持续运转的沉默杀手”,不会提供推动长期坚持的即时反馈。
- 筛查是他的癌症攻势,而且正在发生拐点:Guardant 的血液检测与 Exact Sciences 的粪便检测同步加速,因为真正的瓶颈是完成检测,而不是标志物。 他预计5年内会出现可信的多癌种早期检测;对于 Prenuvo 式全身成像,他个人选择不做,因为当足够多的检测叠加在一起、每项都存在实质性假阳性率时,一次扰乱生活的假阳性几乎注定会出现。
- 他最近才从贯穿职业生涯的AI怀疑主义转向确信,真正值得下注的护城河是数据,而不是模型。 能够通过机器人生成专有“科学token”的公司将占据优势,因为“已记录的文献中有很多其实是错的”;针对已知但难以成药靶点的 model-to-molecule 流程,已经能在1个月内完成,而 Lila Sciences 等公司过去需要数年,但新靶点发现还没有被系统性破解。
药物已经存在,机会在于产生影响
回顾20年创建和投资生物科技公司的经历,Cornell的结论是,2025年“可能是我整个职业生涯中最令人兴奋的一年”,原因不是科学突破,而是商业验证。GLP-1药物年收入将轻松超过1000亿美元,但真正令他兴奋的是,这些药物证明我们“已经准备好迎接”一场百年难遇的公共卫生革命。
重排整个讨论框架的判断是:“顶尖科学家已经破解了保护我们免受大多数致命疾病侵袭所需的大多数药物。”预期寿命图表“几十年来几乎没有变化”——上一次拐点来自抗生素、疫苗和卫生条件——因此,缺口“未必在于需要更多药物”,而在于让现有药物真正产生影响。
当他说万亿美元革命时,指的是一件具体且具有通缩效应的事:“每年医疗支出减少1万亿美元。”它即将到来的证据来自需求端:人们“用脚投票”,实际上是在说:“我不想再等到疾病已经显现后,才被动地去治疗自己。”
健康体系有5层
这套体系分为进攻和防守两部分:进攻包括营养、力量训练、系统性检测和持续追踪数据;防守则是药物所在的领域。5层分别是:血脂优化、心脏代谢健康、神经认知健康、炎症健康和血压。每一层都在个人主动管理的范围内,而且每一层都已经有对应药物。
在血脂方面,他认为人们没有真正内化的数字是:大多数中年男女在40岁到80岁之间某个时点发生心脏病或中风的概率,“大约在30%到50%之间”。从他汀到 PCSK9 抑制剂,可以把这一概率降到“低于10%”——“在我看来,这很悲哀”,因为药物明明已经存在。
这些层级会彼此放大,他将其描述为一个整体机制,而不是5个孤立风险:血糖让血管变得脆弱,LDL在血管内不断沉积,同样的过量进食会引发炎症反应,血液在这套系统中的压力又随年龄上升。“天哪,这就像一枚定时炸弹,所有问题最终一起引爆。”每条轴线都是其他轴线的力量倍增器。
他的收益判断没有任何保留:尽早、主动地管理这些因素,“它们无疑会让我们的预期寿命额外增加10年”,并有可能让已经“几十年几乎横盘”的寿命曲线重新出现拐点。
GLP-1商业化证明需求存在
他的第一个关键判断与卖方共识相反。华尔街“非常关注下一款GLP-1能否带来更多减重、更多减重、更多减重”,但数据表明,“人们并不是在解决这枚巨型火箭筒”——他们只想减掉一部分体重、稳定下来并维持住。更高剂量带来更强疗效,也带来更多副作用,因此患者真正追求的是可持续使用:“我怎样开始用药,然后一直用下去?”
第二个关键点是 Lilly Direct。传统模式依赖大量销售代表拜访医生,既耗资本又耗人才;Lilly加上数字化前端,让患者可以直接拿到处方,并从公司收到药物。到2025年底,“新加入的人中超过一半是直接进来的。”
复方GLP-1引发的“戏剧和喧闹”带来了最重要的教训:价格弹性极大。复方版本的价格约为品牌药每月400–500美元的一半,团队数据表明,通过 Hims & Hers 等渠道,市场中有15–20%的需求流向了处方体系之外——人们愿意承受制造和安全风险的不确定性,因为每月200–250美元负担得起,而500美元负担不起。
随后是2026年的口服 Wegovy,其上市初期相对推进速度约为 Zepbound 的“4倍”。他认为这不是因为患者排斥针头,而是因为月费150美元、年费1800美元,“这些药会被迅速抢购”:根据他“上周五”查看的数据,市场已经从上市前每周约20万张新增处方增至每周30万张。
BMI 40以上人群仍未被充分服务
机制可以这样理解:GLP-1是食物进入小肠时由人体释放的一种激素,在体内只能维持约2分钟。“如果要达到现在每周一针的效果,我们余生每小时得给自己注射30次。”它会减慢胃部消化、作用于驱动饱腹感的大脑受体——合在一起就是“关掉食物噪音”——同时刺激胰腺释放胰岛素,保护血管和肾脏。
他第一次接触这一领域是在2005年,当时任职 Amylin Pharmaceuticals;那时每天注射2次已经是“最不可思议的突破”。如今的分子作用时间更长、效力也强得多;Pfizer刚收购了一款“可能每月给药一次”的资产,Amgen则在推进月度或季度给药。他最看重的是给药间隔,因为“药物越容易服用,患者就越有可能坚持使用”。
在 semaglutide(Ozempic、Wegovy)与 tirzepatide(Zepbound、Mounjaro)之间,他的团队刻意采取了不浪漫化的判断:“它们最终都实现同样的目标,只是采用了不同的新颖IP策略来实现这些目标”,两者“基本可以互换”。
投资问题始终是:一款药凭什么赢?BMI 25到39的人群“用任何现有选项都能得到很好的服务”,因此,真正的制胜区间在 BMI 40以上——这里需要极长的剂量递增过程才能达到高激素水平,也需要更大幅度地降低食物噪音。长期来看,他会押注低剂量药物保护所有人,避免人们从青春期到60多岁期间平均增加约5个 BMI 点,但他也指出,“这些人群还没有接受过测试”。
GLP-1不是免费午餐
Patrick提出了一个尖锐问题:如果你在用药期间吃的东西,完全等同于不用药时会吃的东西,结果会不会不同?他的让步在先——如果只看体重,“其实不需要这些药”。但如果家族病史和糖尿病前期意味着你无法产生足够胰岛素来清除葡萄糖,“是否足以逆转你向糖尿病发展的进程仍是未知的”,所以“我可能会说,你大概仍然需要这些药”。
他认为单靠自律会失去两项收益。第一是成瘾保护:未来一年左右将公布关于毒品、酒精和赌博的数据,这些行为都经过大脑中同一套饱腹信号通路。第二是心脏保护:Novo Nordisk过去一年的数据显示,心脏病和中风风险降低超过20%,“与减重无关”——在他看来,这说明背后存在“另一个完全不同的生物学驱动因素”。
当被要求为最聪明的怀疑者辩护时,他没有回避:“GLP-1确实存在真实的毒性。”恶心、呕吐和腹泻会导致患者早期停药;药品标签列有胆结石和胰腺炎风险;快速减重还会伴随肌肉流失。他的权衡很明确——这些疾病合计会消耗5到10年寿命,而药物的风险“只要停药,就能做一些事情加以处理”。“GLP-1不是免费午餐。”
3道障碍阻挡预防性药物
他列出的3道障碍是“复杂性、成本和便利性”,但他实际描述的第三项是依从性。复杂性方面,他自己的经历就是样本:从血液检测发现胆固醇问题,到最终拿到药物,花了2年时间,其间要等待6周才能预约、反复抽血。“系统中的摩擦不断叠加、叠加、再叠加。最终,我认为很多人就此放弃。”
最能说明问题的一句话是:“为什么我可以拿起 iPhone,打开 Amazon,点一下按钮,第二天就收到牙膏;但为了保护自己不发生心脏病,却要经历一段不可思议的旅程,打数百个电话、看几次医生、被反复扎针和检查?”
成本方面,真正值得下注的结构性错配是:需要服用数十年的慢性预防药物,“定价却和急性治疗差不多”。这是一个时间跨度问题;随着医疗体系从“等到几乎太晚”转向主动预防疾病,他预计定价模式将出现真正的创新。
至于依从性:“药物只有在我们服用时才有效”,每增加一次给药、一次去药房和一个决策节点,患者停药的概率就会上升——“这就是人性,我自己也一样。”坚持用药是“阻碍我们实现最佳健康结果的一道隐形障碍”,所以从每日2次到每周1次,再到可能的季度给药,用他的话说,是“一个巨大的突破”。
PCSK9是真正的免费午餐
发现过程本身就是论据。人类遗传学发现,有一群人携带某种突变,无法产生 PCSK9 蛋白;该蛋白通常会妨碍人体清除 LDL。持续15年的纵向研究显示,这一缺陷使他们终生罹患心血管疾病的风险降低88%——“那太不可思议了”,于是整个行业的目标就变成把这一优势赋予其他所有人。
当前药物可将坏胆固醇降低50%;对于已经发生过心血管事件的患者,风险降低超过20%,对于高风险患者,风险降低约25%,而心脏病如今仍是“美国第一大杀手”。治疗方式也从注射型单克隆抗体转向 RNA 干扰,长效分子让给药频率从每年26针降到可能每年2针。
Patrick面对怀疑者提出的问题——LDL难道没有有益作用吗?——答案来自遗传学,而不是理论:你可以把 PCSK9 蛋白压到零,但即便在动物模型中,能够实现的 LDL 最大降幅也只有80–90%;而那些体内没有该蛋白的人“活得非常长久、健康”。结论是:“这一次确实是免费午餐。”
尽管风险收益更优,PCSK9为什么没有卖得比GLP-1更好?GLP-1会带来副作用和可见结果,所以你知道自己正在用药;胆固醇什么都不给你——它是“一个在后台持续运转的沉默杀手”,甚至能在人处于最佳身体状态时将其击倒。他认为,长期来看,PCSK9“无论用药人数还是收入,都应该远远超过GLP-1”,风险收益也优于他汀。
早期检测改变治疗结果
阿尔茨海默病“几十年来一直是一片荒地”,而他的判断是:“我们终于破解了密码的开头,但还没有完整答案。”Biogen和 Eli Lilly 的抗淀粉样蛋白药物,可让晚期患者的病情进展放缓约30%,但那时大部分损伤已经发生。若能更早发现斑块,就等于“关掉水龙头”——他的猜测仍有保留:Lilly今年晚些时候的数据可能支持40%、50%甚至更高的效果,最终让我们醒来时“生活在一个没有这种疾病的世界”。
他从进攻角度看待癌症,部分原因是寿命延长可能提高癌症发生率:“人活得越久,最终总会有某种东西找上门。”癌症难治有两个原因:发现得太晚,以及癌症是“一个狡猾的恶魔”——即便把肿瘤缩小到零,残存的少数细胞也会获得生长优势并重新定向。
筛查是他最兴奋的领域,商业含义也最清晰。Exact Sciences的粪便检测和 Guardant Health 的血液检测都在增长,但“血液检测正在出现拐点”,因为真正限制规模化的是样本完成率,而不是标志物质量。他用敏感性和特异性评估每项诊断:100个癌症中能抓到多少,以及100个干净样本中有多少假阳性。他预计5年内会出现真正优秀的多癌种早期检测——“如果我们还做不到,那就是我们的耻辱。”
在治疗方面,重要的是曲线斜率:CAR-T已经从提取患者细胞、在体外武装,发展到 Capstan 等公司通过静脉注射在体内完成治疗,超过70%的患者实现100%的肿瘤缩减,并且长期维持。他用亲身经历说明这一变化:他的连襟父亲近10年前死于多发性骨髓瘤,“今天他的预后会完全不同”。对于 Prenuvo 式全身成像,他个人选择不做:更多数据是好事,“前提是你能把它放在正确语境中理解”,但当足够多的维度叠加、每一项都有实质性假阳性率时,一次扰乱生活的假阳性几乎不可避免。
AI的护城河是专有数据
他的概念框架是科学超级智能:一位顶尖科学家,配备“达到爱因斯坦水平或数倍于爱因斯坦水平”的智能代理基础设施。人类科学家受到两重限制——大脑能记住的内容,以及人手能够完成的移液操作。去掉这两道限制后,系统就可以枚举“所有数量为 n 的假设”,挑选下一项最佳实验并全天候运行,把3至5年的时间线压缩到不到2年。
他长期以来的反对理由,以及最终改变看法的原因是:只用已发表研究训练的模型,遵循的是“垃圾进、垃圾出”的范式,因为“已记录的文献中有很多其实是错的”,而且无法重复验证。因此,赢家需要AI人才、资本,以及“生成公共领域不存在的科学token的新方法”——token生成本身会成为护城河。在 Lila Sciences,他看到机械臂自动移动培养皿;他们接近完成的一家公司已经“开始展示曲线弯折”,这意味着科学超级智能可能遵循“一套相当确定的规模化规律”。
对于今天已经真实存在的能力,他划出了一条清晰界线:新靶点发现还没有被系统性破解;已经被破解的是针对已知但难以成药靶点的药物开发。筛选在计算机中运行,Lila Sciences 和 Enabla 等公司可以把原本需要几年的 model-to-molecule 流程压缩到1个月。被问到这条曲线是否已经不可避免时,他说:“在我看来,我们已经在这条曲线上了”,而这一转变发生在“非常近期”。
草根层面的镜像是肽类亚文化:Reddit群组在随机对照试验和 FDA 路径之外自我试验,人们说“我没有时间”,带着一个希望立即验证的假设。他的判断确实不确定——“我认为很难知道”——但同时提到 FDA 领导层在 Marty Makary 带领下正试图减少摩擦:用AI系统在创纪录时间内梳理数千页申办方文件,并重新审视哪些动物证据可以由细胞实验替代,以及哪些重复研究可以合并为一项。
影响重新塑造了他的投资方式
对他影响最深的两个人是:父亲,一个“永不停止创业的人”,但没有一件事真正成功,10多年前因帕金森病去世;他在生命最后几天告诉儿子,自己“从来没有在最艰难的阶段坚持足够久,把任何事情做到底”。以及母亲,她反复灌输“我们总是全力投入,永远不会放弃”,并让他相信自己可以做到任何事。“我从父亲那里看到,承担风险意味着什么,也看到失败并不会让人生停摆。”
他是家里第一个上大学的人,进入 MIT,随后加入 Merrill Lynch,从资本市场做到衍生品交易台,并被分配负责生物科技。他爱上这个领域,是因为那里的“风险收益关系关乎生死”。他发现生命科学投资人都在执行类似的纯股票策略,于是利用夜晚和周末制作了一份演示稿,论证可以保持回报、同时降低风险。他把材料发给所有人,得到的回应是:“一片寂静。”几个月后,Deerfield Management这家12人公司的交易主管 Jeff Kaplan 打来电话;他于2005年加入,当时24岁,身边最年轻的人也已经40岁左右。
入行10年后,他通过 Deerfield 自己的患者旅程数据改变了看法:被开具终身用药的人,平均坚持约1年就停药。“没错,药物只有在人们服用时才有效,但他们没有服用。”他称那是一段“非常黑暗的时期”——已婚、刚有了第一个孩子,他开始问自己:“我们是不是只是在优化最大预期回报,却没有对公共健康产生任何影响?”答案不是离开投资,而是把投资方向从发明药物转向让药物产生影响。
这最终促成了 Bridgewell。他与曾任 Bridgewater COO 的 Brian Kreiter 一起,从第一性原理出发设计“人类健康的操作系统”。目标不是“十年一遇、价值1000亿美元的GLP-1革命”,而是带来万亿美元成本节省的革命。每天早上9:15,他会与科学家、生物统计学家、商业和AI专家、交易员及结构化融资人士开会,回答3个问题:创新会成功还是失败,是否与市场相关,以及能否以有吸引力的回报完成融资;同时寻找那些“应该存在、但目前还不存在”的药物。别人为他做过最体贴的事,是他的妻子 Cass 总能在他意识到自己已到临界点之前,先看出来。
1. The State of Modern Medicine
You and I have had these conversations for many years. We've been partners and friends for a long time, so it's hard to know where to begin the conversation because I suspect we'll go for hours talking about drugs, bio, healthcare, and a million things that affect us all.
You have this cockpit-like view into what's going on in the state of medicine today. How would you describe the state of the union—the daily cockpit view that you get of the whole industry? Give us a dispatch from that room. What do you see today?
Alex Cornell
When I look at this moment in terms of where we are in medicine, and look back over my 20 years of building and backing biotech companies, I would say that 2025 is probably the single most exciting year in my entire journey.
To unpack that, what we're seeing is that GLP-1 medicines are showing us what happens when we get to the root of disease. These medicines have the potential to do everything from protect us from being diabetic after being pre-diabetic, all the way through lowering our risk of having a heart attack or a stroke, protecting our kidneys, and soon, we're going to see the opportunity to protect us from developing addictions to alcohol and drugs. So, it's a profoundly important single medicine.
Because these medicines are incredibly powerful and can do wonders for people's long-term health, what we're seeing is that the adoption of these medicines has exceeded almost everyone's expectations, including my own, which were pretty darn high. I think it's easy now to conclude that this class of medicines will easily be in excess of 100 billion dollars a year in revenue.
What gets me fired up about that is not necessarily this once-in-a-decade, 100-billion-dollar revenue opportunity that exists within GLP-1s. What gets me fired up is that it's actually the first commercial proof that we are ready for what I think we're going to look back on in time as a once-in-a-lifetime, trillion-dollar revolution in all of public health. In order for that to be true, there are going to be layers of attack that are needed to help us live our longest and best lives.
I think one of the things a lot of people don't appreciate when I meet them and we start talking about where medicine is and what it can do is that incredible scientists have already cracked the code on most of the medicines we need to protect us from most of the diseases that will claim most of our lives.
Mm-hmm. That's a really important point, because what that means is that there are tons and tons of people who have traveled through all different mazes to arrive at the biological target and come up with a medicine against that target that can help us to live longer and better lives. When we think about the gap that exists in the world today, the reality is that when we look at any life expectancy charts, they haven't budged in decades.
In fact, the last major advancement where we had an inflection was decades ago, on the back of antibiotics, vaccines, and better hygiene. We've gotten nowhere since then. The gap is not necessarily needing more medicines; it's actually pointing those medicines at the impact that they can have.
Alex Cornell
And so, to me, what I'm excited about with the GLP-1 opportunity is that we're seeing the first commercial proof that we're ready to head in that direction. The reason those sales have exceeded our expectations is that people are taking their future into their own hands. People are basically voting with their feet, saying, "I'm done waiting to reactively go and treat myself for the diseases that I backward-lookingly manifest. I'm ready to go get after and help myself to the—"
2. Designing the Modern Health Stack
Longest and fullest. I wanted to zoom in on a concept that you and I have been riffing on a lot recently, which we're calling the health stack. Stack is a term in technology, like your tech stack is all the various components that you use to create your overall thing. We thought this idea could be applied to health.
We're all interested in our own health. It's a universal interest and concern. Maybe riff a little bit to begin on this notion of the modern, evolving, and emerging health stack.
Alex Cornell
A health stack has a couple of different elements to it. It has elements of offense and defense. On the offensive side of the equation are some of the basics that we all know about. It's everything from proper nutrition, strength training, proper monitoring and testing, and doing those activities in a systematic way, tracking that data, and building off of it over time. Later on, we could talk about how AI can play a big role in enabling that to reach its final chapter of what it takes for impact.
What I find most interesting about it is that if we think about 5 core dimensions, not only are they within our hands to be proactive about protecting ourselves, but we have the medicines to do that. To me, the 5 key layers are lipid optimization, cardio-metabolic health, neurocognitive health, inflammatory health, and our blood pressure.
When we think about lipid optimization, we have—and our bodies produce—cholesterol. There's a type of cholesterol called LDL cholesterol that's really dangerous, and it's dangerous because this cholesterol builds up in our bodies over time. It's slowly accumulating in our vasculature, and as it accumulates, it gets to a point where it causes a blockage. That's a heart attack and a stroke.
We have medicines today, whether they're statins or PCSK9 inhibitors, that can do wonders to reduce our level of cholesterol. Most middle-aged men and women walking around have somewhere between a 30% and a 50% probability of having a heart attack or a stroke sometime between the time that they turn 40 and the time that they turn 80. To me, that's tragic, because we have medicines that can help us dramatically lower that risk to sub-10%.
Looking at the next layer, cardio-metabolic health, what we're talking about is the glycemic environment in our bodies combined with visceral fat. These are 2 major drivers or impediments to our long-term health. To give you an intuition for these, the higher the level of glucose in our bodies, think about it as making our vasculature more brittle.
If you are both having lipids accumulate in your body and your vasculature is getting more brittle, you're only force-multiplying the risk that you ultimately have one of those horrific heart attacks or strokes. But we can do something about that. We've got amazing GLP-1 medicines. Clear data from Eli Lilly show a 94% reduction in your risk of moving from being pre-diabetic to diabetic.
We see amazing data in terms of what it does to both help us lose weight and have category shifts, going from obese to overweight and from overweight to normal weight. It's a game-changer in terms of our long-term health.
Moving down to neurocognitive health, the data is not out yet, but later on this year, we're going to see the next step for what are called anti-amyloid medicines—medicines that can go right at the heart of the accumulation of plaques, this time not in our vasculature but in our brains, that lead to all sorts of damage and cognitive decline.
We've got medicines today that can go right at those plaques and bust them. What Lilly's probably going to show later on this year—it's my guess, but I think the data really supports it, and we'll see—is that getting at those plaques earlier, before they accumulate as significantly, is going to show dramatic effects on protecting us from developing Alzheimer's.
Moving on to inflammatory health, one of the things I think people don't appreciate is that the food we eat is actually quite inflammatory. Over time, we've moved from being hunters and gatherers to being able to have as much access to Pop-Tarts as we want. I love them, too. You don't get 1; you get 2.
We overeat to a point where it drives an inflammatory response in our bodies. You can think about that whole equation: if we have both lipids accumulating and our body has a high-glycemic environment making our vasculature brittle, and the same food that we're eating is driving an inflammatory environment around it, oh my goodness, it's like a ticking time bomb for all of that to go off.
Not only is the inflammatory environment of our body implicated in driving an increase in cardiovascular events, strokes, and heart attacks, but it's also implicated in a whole set of inflammatory diseases that span everything from atopic dermatitis to ulcerative colitis and Crohn's disease.
And then, finally, blood pressure. Maybe this one is very intuitive to people, but you can imagine that if we're living high-stress lives, if we're not working out, if we're developing obesity, and we have this high-glycemic environment, our vasculature is brittle, our LDL is mounting, and on top of that, the pressure going through that system is getting higher and higher as we're aging and doing nothing about it.
Oh my God, that’s just another force multiplier. So all of these axes that I define as the 5 key layers of defense, the defensive side of a health stack, each of them has medicines available to help us control our fate. Each of them has medicines available that, if we could get on them early and be proactive about where we’re going with our health, will undoubtedly add an extra decade of life to our expected lifespan and have the potential to take curves that have been dead flat for decades and drive one of the first inflections ever.
I want to spend a little bit of time on each—maybe not all 5, but at least 4 of the 5 levers—to let you explain what you’re seeing and learning, especially from your perch as an investor. One of the things that makes you so unique is that ultimately you’re trying to make money on all this stuff, and you’re doing so with extreme care and precision, on a very sophisticated team, and with lots of data. There’s money on the line here, so this isn’t just you reading something and trying something. It comes out on a scoreboard.
I want to start with GLP-1s because it’s obviously the thing everyone understands the most. It’s visceral. Maybe to begin, it would be for you to tell us what specifically you’re seeing in 2025 and 2026 that is so exciting, because these things have been around for a little while and people are starting to get on them earlier than that. What is the inflection? And then I want to get into the actual mechanics of how it works.
The one that’s about to come out next year, which seems maybe even more revolutionary than semaglutide and tirzepatide—what happened recently that has you so extra excited about them?
Alex Cornell
Maybe one of the things most people don’t realize is that there are a couple of different injectable GLP-1s on the market today. We have some of the first oral versions coming to market now, and more that are coming. These medicines exist at lots of different doses.
I think one of the most interesting discoveries that I made over the past year, just looking at all of the data that we get to consume as investors, was that I wanted to know the answer to this: Wall Street is very focused on the next GLP-1 having more weight loss. I’m sitting back and thinking to myself, I don’t know if that’s the right focal point.
One of the most interesting findings from diving into the data is that people are not solving for this massive bazooka. People are solving for something that helps them lose some weight, stabilize, and be there. I think that’s really interesting because what that means to me is that what people really want is something that’s going to give them a health advantage but be incredibly tolerable.
What we find is that as you go higher and higher in doses, the unintended consequence is that, yes, you’re going to have more weight loss, but there’s going to be a whole host of other side effects that come with it. That is different from most medicines, where we’re trying to maximize the efficacy of the medicine—really where Wall Street minds typically tend to go. What people are maximizing for here is, how do I get on these things and then stay on them?
So that, to me, was one of the big unlocks for 2025: this idea that people want to protect themselves. If you marry that with the next big discovery from 2025, it’s that typically the way medicines are commercialized is that you have big pharmaceutical companies—Eli Lilly, Novo Nordisk—that have armies of sales reps out everywhere, calling on doctors, making sure they know about their medicines, pitching the attributes and why they’re the best in class, and why there’s no other option that their patient should be pursuing other than their medicine.
As you can imagine, that’s a very capital-intensive exercise. It’s a very human-talent-intensive exercise. What we saw, interestingly, was that Eli Lilly, pretty early on last year, pushed more aggressively into a nontraditional way to get these medicines into the hands of people. They added to their legions of salespeople a digital front end in LillyDirect that allowed people to get a prescription from their doctor and get the medicine directly from Eli Lilly.
It was one of the first big insights that consumers want to be able to get these medicines themselves and not have to go through traditional means to get them. As you fast-forward toward the end of 2025, what we started to see was that, oh my goodness, more than half of the new people joining were coming in directly.
Hold that with the third point that comes from 2025, which was all sorts of theater and dramatics around compounded GLP-1s. What we learned from the compounded GLP-1s was that not only do people want something that’s going to defend them and be tolerable, and not only do they want something that they can get through all the frictions of the system—just hit a button and have it come to their homes, a real consumer-like product—but price matters a ton.
Through most of 2025, the average monthly cost of a GLP-1 was north of $500. Thanks to our administration, those prices are coming down, and I think that’s really good. It’s particularly good because what we learned from the compounded versions of GLP-1s was that there is massive price elasticity in this market.
Compounded GLP-1s cost about half as much per month as the traditional, approved GLP-1s by Lilly and Novo. We were collecting data that was suggesting somewhere between 15% and 20% of the market that you couldn’t capture through scripts was actually flowing through groups like Hims & Hers and other sources, where people knew they wanted the benefits and wanted to be proactive about their health. They wanted to get these GLP-1s, but they couldn’t possibly afford $400 or $500 a month. They could afford $200 or $250 a month.
To me, that’s profound because you’ve got a compounded version that hasn’t gone through any clinical trials. You know nothing about the manufacturing, but you know that these medicines are so important to your health that you’re willing to take the risk—not only the safety risk of the medicine, but all these risks and unknowns of where it’s even coming from.
Mhm.
Alex Cornell
I left 2025 thinking to myself, oh my goodness, we’re finally starting to see people step up and vote with their feet. They said, “I want the benefits of these medicines.”
Now you get to 2026, and this is the absolute game changer. In 2026, we now have an oral version of Wegovy. This medicine has launched over the last couple of months. We are seeing every week that the oral version of Wegovy is setting record after record after record.
3. The Biological Mechanisms of GLP-1
You might think, yeah, of course—who wants to inject themselves once a week for the rest of their life? But I don’t really think that’s what’s driving an almost 4× relative launch cycle for oral Wegovy versus the most recent injectable launch, Zepbound. People want these medicines, and the lowest end of the curve doesn’t cost $500 a month or $250 a month; it costs $150 a month.
Now we’ve seen that, at the lower end of the curve, if we get to an $1,800-a-year cost, these medicines fly off the shelves. To put that in context, prior to the launch of oral Wegovy, just a few months ago, the GLP-1 market was moving at about 200,000 recorded new scripts per week. That meant 200,000 new people getting on these medicines per week.
The most recent data that I looked at this past Friday says that this has now moved from 200,000 a week to 300,000 a week in just a few months’ time.
Crazy.
We have to take these incredible learnings from the commercialization of GLP-1s, and the most logical conclusion is that, yes, people are ready and people do want to go and be proactive. Arming them with the stack that can help us all live an extra decade means really focusing hard on what it takes to close that gap between invention and impact.
When I say this trillion-dollar revolution, what that means, really, is this trillion-dollar reduction in our annual health care spend. I think that’s really possible now.
I want to spend some time explaining what’s actually going on with this class of drugs. Starting with semaglutide, the single-acting one, going to tirzepatide, the dual-acting one, and then going to the triple-acting one that’ll be coming out this year or next year, can you do your best to explain what this thing is and what it does?
I think people’s original conception was, “It’s a drug I take and I lose weight.” I think you have a really interesting way of explaining and understanding these things as maybe the most important modern drug. It seems worth spending some time just explaining literally what it is, what the science progression has been, and where you see it continuing to go. This isn’t static.
A lot of people don’t realize these medicines have actually been around for 20 years. Some of my first exposure to GLP-1 as a drug class happened in my early days entering the industry as a young biotech investor back in 2005, with Amylin Pharmaceuticals having what we thought at the time was the most miraculous breakthrough.
GLP-1 is a hormone that our bodies naturally produce. The problem with this naturally produced hormone is that once it’s produced by our bodies, it only lasts for about 2 minutes before it’s gone. If we just pause there, what does that mean practically? If you were to take human GLP-1 and we were injecting it, we’d have to inject ourselves 30 times an hour for the rest of our lives to get the benefit of what we can get today with either one pill a day or one injection a week.
The science behind moving from a protein that lasts for 2 minutes to a protein that can last over a week is a dramatic transformation. What’s good about that is it’s a hormone that’s already in our bodies, and it’s a medicine that we’ve got data on for over 20 years. We know a remarkable amount about it, not just because it’s been around for 20 years, but because it’s now been in millions and millions of people.
So, how does it actually work? When we eat food, at some point that food makes its way to our small intestine. When food gets to our small intestine, that’s what triggers the release of GLP-1 in our bodies naturally. That GLP-1 molecule travels all over our bodies and interacts with receptors in our stomachs that help to slow the digestion of food.
It also interacts with receptors in our brains that help us to feel fuller longer, to feel satiated. The combination of those 2 mechanisms of action is what allows us to turn off the food noise and seek out and consume far fewer calories than we’ve ever done before. In addition to that, it plays an important role in regulating the production of our insulin. It interacts with the receptors on our pancreas that trigger the release of insulin.
It plays a big role in not just having that sugar not affect our vasculature, but also making sure that sugar isn’t destroying our kidneys. The mechanism and the science behind it are actually pretty well elucidated. Biologically, we know how it’s produced, and we understand all the different places in the body that it interacts.
When you think about all the places in the body that it interacts, it then becomes no surprise that it’s had such an incredible range of effects: protecting us from becoming diabetic, reducing the risk of having heart attacks and strokes, and lowering our level of inflammation because we’re consuming less food and having less of an inflammatory response to that. It goes all the way through to helping us lose weight, which is a bit of a virtuous cycle in terms of lowering our blood pressure.
When you look across the 5 axes, the 5 layers of defense that are mission-critical for us maximizing the number of years that we can live and having the most life in those years, I fundamentally believe there’s no molecule that’s more important than GLP-1 across that entire axis.
When we think about the different forms that it’s available to us in, we could really crack the most important code, which is moving from something impractical—30 shots an hour—to the early days with Amylin Pharmaceuticals of a twice-a-day shot, to where we are today. Today, we have not just longer-acting, once-a-week versions, but far more potent versions, meaning we need far less of it, and it starts to get to levels that we can inject that have incredible pharmaceutical properties.
As we think about it, I think the next axis to think about is not just the form by which you get it, oral or injectable, and not just the duration of the dosing. Orals we take every day; today, we take injectables once a week. There are some amazing ones that Pfizer just acquired that look like they might be once a month. Amgen is also working on a once-a-month version that might be once a quarter.
The duration of time between those doses is really important because the easier it is to take a medicine, the more likely you will be to stay on these medicines and have the longest-term benefit from them. I think the next important axis to focus in on is how we think about dose and the tradeoffs between semaglutide and tirzepatide.
Semaglutide is Ozempic and Wegovy; tirzepatide is Zepbound and Mounjaro. Our team’s fundamental perspective is that they all achieve the same goals. They were just novel IP strategies to achieve those same goals, and I would say that they’re all pretty much interchangeable.
How do we think about them from an investment perspective and a human-impact perspective? Those 2 perspectives actually come together because when we think about investing in medicine, the key question that we’re focused on is, “Why does a medicine have a right to win?” For a medicine to have a right to win, what we’re essentially saying is that this medicine is going to have a differential impact for people such that people should choose it.
The right-to-win analysis also comes down to the different segments of the market that we’re thinking about. To put a framework around this, we always think about the obesity market as having 3 main segments: people that are overweight, which are basically BMIs between normal—roughly 25—and 30; obese, which is between 30 and 40; and morbidly obese, which is north of 40.
When we look at the aperture from a BMI of 25 up to a BMI of just under 40, that’s where most of the patients are today that require reactive treatment. I would argue that in the future, we could talk about why GLP-1s might be appropriate for just about everyone. That’s because the reality of it is, as you go from your adolescence to your 50s and 60s, on average people are going to pick up about 5 BMI points.
Being able to take a medicine, even at low doses, even though they haven’t been tested in those populations, I’m willing to bet would help protect people from that 5-point increase that puts them in harm’s way and puts that to bed. But when we look at the market today, pretty much from that BMI of 25 to 39, people are well served with any of the available options on the market.
Where we still need some help, and where I think there’s a right to win, is really in that BMI zone of 40 and above. Sadly, these people are at a level of body weight that requires incredibly long titration to get up to these high levels of the hormone. They need a much more dramatic reduction in their food noise to be able to bring their weights down from a zone that is incredibly dangerous, given the amounts of visceral fat that they’re carrying around, to levels that are going to give them much more sustainable life and a much longer life.
I have a very basic question. Would there be any difference in outcomes if we simply ate the same exact input that we eat on these medicines? If, instead of taking the medicine, I just ate exactly what I would eat on them, but figured out a psychological way to deal with the food noise and just didn’t eat when I was hungry, effectively, is there any difference in outcomes, do we think?
I’m especially thinking here about alcohol addiction. It seems to be one of the things that gets addressed by these drugs, and that seems unrelated to how much I eat. It seems like an independent thing that’s being positively affected by the drug beyond just which calories I’m putting into my body. Is there something else going on here beyond just literally what I’m eating as a result of taking these drugs?
Alex Cornell
Eating is definitely a part of it, and it’s a major part of it. If we could all be disciplined and get on a proper diet where we’re selecting the right foods, eating the right amounts of them, and staying disciplined to that, you wouldn’t really need these medicines for the purposes of managing our weight.
But I think that’s only going to cut at the weight part of it. Unfortunately, if your biology is wired such that you have a family history of diabetes and you’re prediabetic and on the precipice of turning diabetic, we’re starting to be in a place where we’re just not producing the insulin that’s required to be able to take up that glucose that’s coming from the food that we’re eating.
By consuming fewer calories and less food, we can hit part of that, but I think it’s unknown as to whether that’ll be enough to be able to undo your progression to diabetes. I might say you probably still need those medicines for that. On the other side of the equation, connected to that, has to do with addiction.
4. Overcoming Frictions in Healthcare
In some sense, you could say that food is a form of addiction. While consuming fewer calories will help protect us from the vicious cycle of overconsuming food, I would say that, in terms of the addiction data that will start coming out over the next year or so, you would lose that benefit. You would lose the free gift of protecting yourself from being addicted to drugs, alcohol, or gambling.
That comes from the signaling in the brain—the satiety axis in the brain—that cuts across both food and some of these other not-great behaviors. I think there's also an open question about what just consuming food would do for cardiovascular outcomes. We've got compelling data from Novo Nordisk over the last year that basically shows that, by taking GLP-1 medicines, there is a reduction north of 20% in our risk of having a heart attack or a stroke.
What I thought was pretty profound about the full data that they put out is that this was independent of weight loss. I think that speaks to me that there's just another axis and another biological driver that's driving this cardioprotective result. We might forfeit that, but without a doubt, if we could actually get access to great food, eat the right amount of it, and stay disciplined, that would take us a long way.
But it seems like, summarized, there is more going on than just that. The data seems to suggest that even if I could eat perfectly, I might still reap benefits in these other ways from these drugs.
I want to talk about the next layer—the first layer you listed—in cardiovascular and PCSK9 drugs, to really drive home the point of existing drugs before we get to all the exciting new stuff, which we'll talk about as well. There are existing drugs that could have a radical impact if everyone were on them.
Alex Cornell
There are basically 3 different dimensions that are preventing people from getting the maximal benefit of a breakthrough medicine that exists and is right here for all of us. In my mind, those break up into complexity, cost, and convenience.
I think all of us have had the experience of learning that we have some health problem and wanting to go do something about it. I've kept you up to date along the way, but it was amazing to me to actually realize—to practically have to deal with our health system—and all of the different branches that it took from recognizing that I had a cholesterol problem to, 2 years later, finally getting access to the medicine that could help protect me from that problem.
It's everything from wanting to go see a doctor because you get a blood test that says, “Hey, I have a problem,” to learning that the next appointment is only 6 weeks out. Then I go, and of course they want to redo the blood test. You can just see the friction in our system mounting and mounting and mounting. Eventually, I think a lot of people just give up. It is really hard to navigate that system.
Given what we're seeing with GLP-1 medicines, and the fact that the direct-to-consumer side of that is driving most of the adoption today, I think we have to start asking ourselves, “Why is it that I can go on my iPhone, go to Amazon, click a button, and the next day have toothpaste, but it takes me an incredible journey—hundreds of phone calls, multiple doctor visits, being pricked and prodded multiple times—just to protect myself from having a heart attack?” That doesn't make sense.
5. Cardiovascular Disease
I think we have to balance the opportunity for health impact of this amazing medicine that we have with the reality of how darn complicated it is to navigate through our system. Next is cost. Most medicines that we need to be on for the rest of our lives—those that are going to provide the chronic care and the different layers of that defensive health stack that will protect us from these diseases—are priced similarly to acute treatments today, yet they need to be taken over decades.
We have a timeline problem. We have a horizon problem. I think that there's a lot of innovation that can occur around pricing models if the world moves from where we are today—which is waiting until there's a problem, waiting until it's almost too late, and reactively treating it—to proactively getting out ahead of disease.
The final part of that is compliance. We all know that medicine only works if we take it. Because of the complexity of the system in getting it, because of how expensive these things are, and, at the end of the day, because we're all human, the more frequently we have to take a medicine, the harder it is to go get it. The more times we have to go to the pharmacy, the more times we have to make that decision over the course of the year, the higher the probability that we're just going to quit.
That's just human nature, myself included. Compliance is this invisible barrier to all of us realizing our best health outcome. On one hand, GLP-1 medicines are miraculous. We went from twice a day to once a week, and now we've got versions that are once a month, maybe once a quarter. That's a huge unlock, in my opinion.
Maybe now's the time to tell a second drug story, a far less well-known one than GLP-1, which is PCSK9. I find this story to be so interesting for so many different reasons, but maybe most of all because it seems closest to what I'll call a free-lunch drug that exists.
Because it helps deal with cardiovascular disease, which is something that everyone has probably dealt with in their family or personally at some point, it seems incredibly important—close to as important as the first one we talked about. Can you tell the story of this specific drug—what it does, how it works, and the impact it might have?
Alex Cornell
The headline here is that PCSK9 medicines are amazing because what they do is, today, they can lower our bad cholesterol—that LDL cholesterol—by 50%. We now have outcome studies in patients at different degrees of having high cholesterol showing significant protection from ever developing or having a heart attack or a stroke.
In patients who have previously had a heart attack or stroke, we can reduce that risk by over 20% in the future. For people who are at high risk of having a heart attack or a stroke, the medicines that are approved and on the market today can lower that risk by about 25%. These are incredible medicines, particularly because heart disease is still the number-one killer in the U.S. today.
The way these medicines were discovered is through human genetics. From a human-genetics perspective, we can go around the world, look at different populations of people, and study some of the attributes and advantages of those different populations. It turns out that there's a population of people in the world that has a genetic mutation conveying a massive advantage. They have a mutation in their PCSK9 gene, which means they don't produce the PCSK9 protein.
What we've learned from observing that village and understanding the cardioprotective nature of that genetic defect is that the production of this PCSK9 protein actually interferes with our body's own ability to clear LDL cholesterol. The more PCSK9 we're producing, the fewer particles of LDL we can clear. Our cholesterol grows higher over time, and more of those little particles invade our vasculature and start to mount up until we get to a point where there's a blockage.
Recognizing the importance of that PCSK9 protein—driven by the observation of human genetics and by data from longitudinal studies over 15 years showing that people in these populations were genetically deficient in producing the PCSK9 protein—led to the finding that they had an 88% reduction in the risk of ever developing cardiovascular disease. That was miraculous.
What the pharmaceutical industry sought to do was, “How can we replicate this?”
Exactly.
Alex Cornell
How do we get that advantage into the hands of people? They came up with injectable biologic medicines at first that you could inject and that would find their way through your body to that PCSK9 protein, bind to it, and prevent that protein from binding to your LDL receptor.
That was the beginning of those medicines. What innovators then sought to do next was, “How do we make it easier for people to take those medicines and get the benefit?” The next big innovation in that space was moving from injectable biologics, or monoclonal antibodies, to a new modality called RNA interference.
These are another form of subcutaneously injected medicine that makes its way down into your liver. They have the attribute of being very long-duration molecules, making it so that we don't have to inject ourselves 26 times a year, but maybe only twice.
It's incredible when you think about seeking out a population that has a natural advantage, figuring out what it is, and then conferring it to others through a drug like this. The dramatic reduction in cardiovascular incidence in people—the genetic group had an 88% reduction, but the people who take this drug also see a dramatic reduction—is so interesting.
I always wonder: The body is such a complex system. There seem to be very few things in biology that are just one use or have one explanation. There's all sorts of stuff going on.
What are the trade-offs? I’m interested in both PCSK9 and GLP-1 since we’ve talked about both. It just seems like there’s always a trade-off. There really aren’t usually free lunches in markets, in nature, and in biology.
So, what’s the skeptic’s point of view? If I could somehow fly in the smartest, data-driven scientific skeptic of the use of these drugs, what would that person say?
Alex Cornell
PCSK9s are much more of a free lunch than GLP-1s. GLP-1s are easy. GLP-1s have real toxicity associated with them. Without a doubt, we see in the clinical studies significant rates of nausea, vomiting, and diarrhea. Those are the first symptoms that emerge, and they cause a lot of people to quit these medicines early.
If you look past that and look at people who have been on these medicines for longer and longer periods of time, you look at the labels of these medicines and the clinical studies, and there’s a risk of developing gallstones and pancreatitis. Of course, these are issues that would emerge just from having weight loss in general, which adds muscle decline to that list as well. These are all consequences of losing weight and losing weight quickly over a period of time.
But when you look at the other side of the equation—the benefit that you get, the fact that these are so protective across so many different axes—the data is pretty clear. Not only will they protect us from developing diabetes, obesity, and cardiovascular disease, but when you look at the implication of those diseases on expected human lifespan, we’re talking about the aggregate of those diseases costing us 5 to 10 years.
It’s very much well worth it for people to take the risk of developing these other liabilities that you can do something about by just stopping the medicine, for the benefit. I think there is a real trade-off. Without a doubt, it is not a free lunch for GLP-1s. But for PCSK9, it is pretty much a free lunch.
There was a ton of concern in the early days: What happens if your LDL goes down to zero?
Doesn’t LDL do good things, like—
Exactly. It’s there for some reason. It turns out that LDL is produced in lots of different places in our bodies. It turns out that you can basically pin that PCSK9 bad protein down to zero.
The best we can do in terms of reduction of our LDL—not even in humans, but in animal models—is something in the 80% to 90% zone. Because we have people walking around with mutations where they don’t produce any PCSK9, and they live incredibly long, healthy lives and don’t have the vicious fate of having a heart attack or stroke, I think we’ve got a combination of animal model evidence that suggests we really can’t get LDL to zero, combined with the fact that we’ve got genetically advantaged people walking around who aren’t even producing the protein to the same degree as others. This one is very much a free lunch in that—
Do you think everyone in the world will be on this particular drug at some point?
Alex Cornell
I would. That would be a dream for me. A big dream for me is that everybody, anywhere, who wants to have the maximum level of cardio protection could get access to this medicine and could stay on it.
I would argue that because it is more asymmetric, more in the degree of that free lunch, if you just project down the road longer term, this medicine should be far bigger in terms of the number of people that are on it and the revenues that are associated with it than GLP-1s.
6. Addressing Alzheimer's
That’s not what’s playing out right now. It’s not playing out right now really for 2 reasons. One, GLP-1s have this amazing attribute to them: You take them, and very quickly you start to have some side effects, so you know you’re on them, and you start to see the benefits.
When you compare the 2, it’s easier for medicines where there’s an acute, clear, easily measurable benefit for people to stay on them. Unfortunately, in the setting of cardiovascular disease, and particularly thinking about bad cholesterol, this is to me the most dangerous setup because you don’t feel anything if you have a high level of cholesterol.
You could think of it as a silent killer that’s just working in the background, slowly accumulating in our bodies. You can be doing everything right and be at your peak physical shape, and then all of a sudden, out of nowhere, you can have a heart attack or a stroke. If we don’t pay attention to the levels of this bad cholesterol in our body, they can sneak up on us and claim our lives.
To me, because the reward is so asymmetrically favorable versus the risk, because the earlier we can intervene with the accumulation of cholesterol in our body and keep that at bay, the greater the likelihood is that we’re going to get through the rest of our lives. Even if other things manifest, like diabetes or high inflammation, or our blood pressure goes up, we’re going to be right at the core of the problem and keep that as low as possible, meaning that we’ve got the lowest level of accumulation across our vasculature.
I think the number 3 and 4 killers, after we talked about metabolic disorders and cardiovascular disease, are neurodegenerative diseases and cancers. I’d love to spend a couple of minutes on each of those.
Neurodegenerative disease in particular—Alzheimer’s drugs seem to have been this wasteland. We really don’t understand what’s going on, and as a result, we haven’t made a lot of progress at either protecting against or treating something like dementia or Alzheimer’s.
What is going on in the world of science and in the business of pharmaceuticals to address this specific problem?
Alex Cornell
It’s been a wasteland for decades, and I think we finally cracked the beginning of the code, but not the full answer. What we’ve found today is that in patients who have confirmed levels of plaques that have developed over decades in their brains, we now have medicines that people can take that will start to break up those plaques and remove them.
Unfortunately—and this will be intuitive—if you get to the patient that late in the disease, a lot of damage to the brain has already happened. You can imagine that these plaques are building; they have to go somewhere, and they’re causing death and destruction of the tissue around them.
7. The Future of Cancer
Today, we’ve got some amazing medicines from both Biogen and Eli Lilly that, if you are late in the disease progression of Alzheimer’s, can start to slow the decline. We can slow that decline by about 30%. Intuitively, that gives us a lot more years at the baseline level of cognition that we have versus declining much more rapidly.
It turns out that if we can identify a patient who’s at risk for Alzheimer’s disease earlier and earlier and earlier—if we had a test available to do that—then it makes perfect sense that, if we can start giving people these medicines as early as possible, not only will we be there in the early stages before a lot of damage is done, but we can think about it as turning off the faucet.
As these new amyloid plaques are produced, you can be attacking them with a medicine that helps to accelerate their clearance. Oh my goodness, maybe that has a dramatic effect on long-term decline. Maybe it reduces those rates by 40%, 50%, or more over a longer period of time.
The earlier we can get them, the better those medicines are at interacting with those plaques, and the easier it is for people to stay on those medicines, the more we might be able to wake up in a world where we live without this disease.
We know that’s possible with GLP-1s for diabetes and obesity. If you take them early enough, you will not become diabetic; you will not become obese. We know that’s possible for cardiovascular disease. If you start taking a PCSK9 inhibitor earlier in your life—which, by the way, I think has a risk-reward profile that’s actually even more favorable than statins in terms of human health—we know that you won’t progress to cardiovascular disease. The same is true for Alzheimer’s.
So, up to this point, we can imagine a future world, as I know you do, where everyone can enjoy the benefits of protective, defensive measures in our health stack for these 3 specific killers. What about cancer? Cancer is the last one that, in some ways, feels the most visceral and the scariest.
Alex Cornell
If we are successful in mobilizing people around a health stack and can move from reactively treating a disease to helping people be as proactive about their health as possible, I think the unintended consequence of that is that, because people live longer, eventually something is going to get us. I think what we find is that the incidence of cancer—the disease that brings us down—could rise. So I think we would be remiss not to talk about where we are with cancer and what needs to be treated to really start beating it in a way that matters.
Cancer is hard both because we often identify it too late and because, when we do, cancer is like a sneaky devil. You might have an angle of attack to go and beat that cancer that presents itself early, and as soon as you’re making progress with a medicine against that angle of attack, all of a sudden the cancer has a survival instinct and redirects.
Now, the medicine that was working incredibly well, that had shrunk a tumor completely to zero, is having no effect because, while that medicine eliminated the cells that were most vulnerable to it, the cells that were left behind—even if it’s just a few—now have the advantage in growing rapidly, causing a new set of harm, and setting a patient on a horrific direction. So it’s hard because we tend to identify cancer too late, and then, when we do, it’s shifty.
I think there’s also the opportunity for optimism around it, and I think it gets to the topic you and I have spent some time talking about, which is testing. I would say the areas of testing today that I find most exciting are being proactive and identifying the risk early, and then, once a cancer emerges, what we do about it. So let’s talk about both of those modalities and then come back to the medicines that are associated with them.
In terms of identifying cancer early, there are companies like Exact Sciences and Guardant Health that have gone really hard at breakthrough innovations to help us screen for colorectal cancer. Of course, we have the gold standard that’s available, which is a colonoscopy, and I have to go get one next year. None of us are ever looking forward to that, and because it’s something people don’t look forward to, even though everybody should be getting them with regular periodicity, most people don’t. I think that’s really tragic because, by not getting your colonoscopy, you’re putting yourself at risk for colon cancer, which is an incredibly slow-growing cancer. If you just got the colonoscopy, I think we could very much live in a world today with a very low incidence of colorectal cancer.
Guardant Health and Exact Sciences went directly at this problem. Exact Sciences has a stool-based test with an incredible ability to predict people being at risk of cancer. The same thing is true for Guardant Health. Guardant Health took it to the next step, knowing that you can go after markers that would predict colorectal cancer but recognizing that the commercial model around getting people not just to receive the prescription for a stool-based test, but also to complete the test and get that sample back, was one that could never have the scale of a simple blood test.
Guardant learned from Exact Sciences’ advancement and then came up with a next-generation version that’s a simple blood test you can get done just about anywhere. It’s amazing to see that not only are both of those markets continuing to grow, but the blood test is inflecting. That, to me, is exciting because it means that people care, doctors care, and people are getting it done. That means we’re going to be safer and safer from these cancers.
I think it’s important for people to realize that not all tests are created equally. When I look at a new diagnostic in the space, I care deeply about 2 metrics. One is sensitivity, and the other is specificity.
One of them tells us, of all the people who could have cancer, what percentage of those samples actually come back with a direct and accurate diagnosis of cancer. If there are 100 cancers in a sample, what percentage of them actually get picked up as cancer? That’s the sensitivity. Specificity is, if there are 100 samples that don’t have cancer, what percentage of those give us a false positive, saying that you have cancer when you don’t? I think both of those are really important metrics.
At the same time, I think there’s a whole other industry around multi-cancer early detection that’s evolving right now and unfolding right before our eyes. These are companies moving from not just having single-cancer tests to having multi-cancer tests across large numbers of tumor types that can be really dangerous.
When you think about how I described the offensive and defensive sides of the health stack, the defensive medicines that we can take to keep us maximally protected don’t include anything to protect us directly from cancer. That’s because I tried to attack cancer from the screening perspective. I made that part of offense.
Over time, I think, at a minimum, people should be doing a colonoscopy. I think the next best-in-class version of that is a colonoscopy married with either a blood test or a stool-based test with some regular periodicity to it. Over the next 3 to 5 years, particularly with how AI and the evolution of these tests are really converging to help them move faster and faster and be better and better, I think we’re going to wake up within the next 5 years with really awesome multi-cancer early-detection tests.
When we have them, shame on us if we’re not getting them, and shame on us if we’re not acting on the learnings that come from them. This will be obvious, but the earlier we know that we have a cancer, the greater the range of options we have to do something about it. I think we’re finding that across lots of different cancers, there are opportunities to have amazing results.
Sadly, my brother-in-law’s father passed from multiple myeloma maybe almost a decade ago. If he had been diagnosed today with multiple myeloma, his outcome—his prognosis—would be dramatically different. Not only is our ability to test and identify that people are developing cancers getting better, and not only do we have other types of tests that can show us the mutational drivers of that cancer and help connect not just the cancer but the type of cancer to the best medicine we have today to treat it, but the medicines are getting better and better.
8. Drug Discovery
Cancer medicines began as many medicines do, with pills and injectable biologics. Today, we have an entirely new class of medicines: CAR T cells. These are either cells that we take out of a patient’s body and arm with the ability to attack the cancer directly, or, as Capstan just came up with in the next-generation version, cells that can be injected on an IV basis and attack the cancer cells directly without even having to take cells out of a patient’s body. That can happen within the patient’s own body.
What we’re seeing from these medicines is dramatic efficacy. We’re seeing that they have the potential to reduce tumors by 100%, do that in 70% plus of patients, and keep them at bay for really long periods of time. While we haven’t yet cured cancer, to me, the slope of the line is really exciting, both from the testing angle—the earlier we can identify these cancers—and from the increasing range of modalities and options we have to go after and destroy them.
What about imaging? There are interesting companies doing skin imaging, like Neko, and deep-body imaging, like Prenuvo. It’s quite expensive, but as I think about the health stack as something that we could do that’s preventative, how do you feel about those technologies, which are relatively new but do try to take a picture—if a picture is worth a thousand words—inside your body and identify a tumor earlier? Do you think that’s worth it?
Alex Cornell
To me, more data is worth it so long as you can put it in the right context. When we get the result of a colorectal cancer screening test, we know the context for that, and we actually know whether we have something that’s useful or not.
I think the pictures we can get from groups like Prenuvo and others are powerful because we can see progression over time and use that data. Particularly as AI is increasingly going to become our medical home, arming our AI system with that information will be super helpful.
The thing I worry about, though, is that as you measure more and more different dimensions, with each of them having a material false-positive rate, the odds that you come out of that experience with a false positive that can be disruptive in life becomes material. It’s not to discourage anybody from doing these; it’s just to make sure that any data we’re collecting is put into the right context so that we can have a framework for how we deal with whatever information comes from taking that test.
For me personally, I’m not yet pursuing those. I’m very much focused on areas where, if we’re going to do a test, it’s going to have a high probability of capturing what I’m testing for and a low probability of giving me a false reading.
And I think the more information that we can accumulate with really high fidelity, the better we'll be at being proactive about our health.
Everything we talked about today was discovered and developed by incredibly talented people—scientists, people in the medical field, and business builders who turn these things into great products and great companies. Maybe just describe, so as not to take it for granted, what that process is in the first place.
But biology is complicated. It is unfreaking believable that we can do the things you've been describing so far in this conversation, and that we're on a trajectory to do even more. The granularity with which we can make edits, for lack of a better term, into what's going on in biology is probably just going to continue to accelerate. So I want to understand that process itself, and then we can talk about how AI figures into that discovery process.
Alex Cornell
First of all, what are the 2 key ingredients for discovery to happen?
Yep.
Alex Cornell
You need scientific instinct married with tremendous amounts of capital. And I think you need both of those to converge in order for there to be a breakthrough that allows us to live healthier and longer lives.
So let's break those into their pieces, with the science of medicine and the business of medicine, because I think they're both independently interesting. Oftentimes, what ends up happening to discover a medicine is a scientist, for whatever reason in their journey, gets inspired to spend their lives trying to crack the code in a certain disease.
And what tends to happen is, as you've identified a problem that you want to solve, just like in any consumer tech product, what's the problem we're trying to solve? You then have to go through a tremendous amount of research to understand every single thing you can about that problem, and most importantly, what could be driving it.
And so what's developed over time is a method, probably one of the most important methods in the history of humanity, called the scientific method, which is the systematic way by which a scientist moves from focusing on a problem they want to solve to actually solving it. And there are a couple of discrete steps in that scientific method, and a tremendous amount of iteration, at least to cracking that code.
And so, once you've identified the problem that you want to solve, the first step to solving that is to come up with a hypothesis for what could be driving that disease. And the way scientists tend to do that is everything from the PCSK9 example, where scientists are observing nature: Where are there populations of people that have an advantage? Okay, let's go figure that out. That's cool. Let's go understand it.
All the way to combing through thousands and thousands of pages of the literature to understand what people have tried to crack—a code that still exists today that you want to go crack. And that's a deep literature review. Fortunately, there are tons of papers that exist on successes or tiny steps to successes that are available for anybody. I think the unfortunate part of the literature is that what's often missing is all the failures, which would be even more informative than successes.
Generally speaking, when a scientist wants to go solve that problem, they're either going to observe a population, they're going to start reading a ton of research, or they're going to put both of those insights together and use that foundation to form their first hypothesis for what could be the solution to the problem.
Okay, so from having a hypothesis, the amazing scientist can then go figure out: What experiments do I need to run to test that hypothesis? And even more, what's my prediction for what should happen in those experiments? Those are really important steps, because the design of the experiment and the quality of the data that comes out from that experiment will either confirm your hypothesis and you move forward, or it will reject your hypothesis and then you go back through and loop to your next hypothesis and your next set of experiments, and you continue to loop and loop and loop.
And so what the scientific method generally looks like is: hypothesis, experimental design, execution of that experimental design, review of the data that comes from that experiment, reading out and testing that data result versus your original hypothesis, either confirming the hypothesis or re-looping and re-looping and re-looping and re-looping.
And so there's this iterative process that tends to begin its journey from the literature, very quickly move into what we call in vitro experiments, or experiments that are done in petri dishes. And as we start to develop evidence in support of a hypothesis in cell-based experiments, it tends to move on to small animals and then larger animals.
And then it gets to the point where the totality of the data and the evidence that you've collected, from a hypothesis perspective to cell-based experiments to the animal-based experiments, you put that all together in a beautiful package that you present to regulators, and you say, “I think I've cracked the code. I think I can move us forward against disease A, B, or C. And here's the hypothesis that we had. Here's how we tested it. Here's all of the data we've generated that helps me, the scientific team, to believe that we might have cracked this code, and now we would like your approval to go start and agree on what studies should look like to test how toxic or how dangerous this breakthrough could be for somebody.
9. AI and Scientific Super Intelligence
“And if we can show that there's good margin between really high doses and where that toxicity starts to come in, and the doses that we've proven from our experiments are likely to help somebody live a longer, better, healthier life, we want your permission to then go and actually test that in a person for the first time.”
This is incredible. And in that process that I just described, you can imagine most of them fail. But for the ones that do succeed and get the chance to then go into toxicity studies and then ultimately into humans, those are the ones that get really exciting. They take years and years of iterating and looping to go from that beginning idea through the literature, ultimately to the animal study that makes you believe you've actually cracked that code.
And then, of course, from there, this is so much more of a marathon than a sprint, because you've spent years trying to crack the code, and now that you have, guess what? Now you've got another 5 to 7 years' worth of clinical studies you have to do to prove that, in people, the idea you had for a medicine actually has the effect that it's intended to, and that, per our discussion earlier, that benefit-to-risk equation is favorable to the point that the regulator should approve it and let it come to the market.
I have 2 questions here.
Yeah.
The process itself is beautiful and has driven so much discovery and progress, not just in medicine, but in scientific-method-driven progress everywhere. But I'm curious about 2 dimensions of shortening that feedback loop or increasing the velocity of new discoveries and progress.
One is AI, and the second is what I'll call citizen pharmacology, which is people—this is becoming really prevalent in what I'll call the peptide community. People love talking about peptides these days. Gelatin is a peptide. Collagen is a peptide. There are well-known things that are peptides, but there's this whole class of things that we can talk about.
But it seems like if you take to Reddit, for example, you will find groups of people organizing to test new things on themselves outside of the normal RCT, FDA-approved process. And if you shorten it, you probably increase the danger, but you decrease the time to learning or something. So you've got both of these things as interesting aspects to me of what will drive forward progress in drug discovery.
I want to riff on each, maybe starting with AI. What is real already? What do you think will become real by virtue of the increasing skill level or reasoning level of the models?
Alex Cornell
What you're basically describing on the AI side is our quest to try to get to a level of scientific superintelligence. You can imagine that, from an AI perspective, if scientists are armed with an agentic infrastructure that has a scientific intelligence that's at an Einstein level or a multiple of Einstein's level, oh my goodness, the force multiplication that can occur between a superstar scientist armed with that agentic resource means that they will do science faster and with higher probability, for lower cost, and have greater impact.
So I think that's an important conceptual framing. And you can imagine that any human scientist on their own, tinkering in the way that I just described—the scientific method and that wheel of science spinning and spinning and spinning—will always be constrained by what we can retain in our human minds and by our ability to use our human hands to go run those experiments.
And so there are super-talented, incredibly smart people that can retain volumes and volumes of scientific papers. They can't retain all of them. AI can. If humans are running experiments, not AI-driven robotics, there's just a certain throughput that is going to be limited by human hands that would be unlimited if you had an agentic, robotically driven system.
And so at the simplest level, I think AI coming into the discovery of medicines is one of the biggest unlocks that we will see in the history of medicine, because it means that we're no longer constrained by our minds, we're no longer constrained by our hands.
We can generate not just a few hypotheses for what the answer can be from the total sample set of knowledge that exists. We can identify all N number of hypotheses that could exist and should exist, and then figure out what is the greatest and best next experiment to run, and run those in real time, 24 hours a day, 7 days a week.
The sheer ability to be more comprehensive and complete in our hypothesis set, and then the sheer ability to run experimentation at a scale that's unprecedented, practically means we are going to be able to speed breakthroughs from timelines that would typically take 3 to 5 years to timelines that can take less than a couple of years. I think the other important element when we think about AI and its impact on drug development is not just the potential of what could be from that conceptual frame, but where are we today?
I think it's really exciting. Today, I would say we're in the early innings of being able to discover novel targets, and I would say that we have not yet, in a systematic way, been able to discover a target that didn't exist yet. But what we can do is, for targets that we know exist but that we have really struggled to develop medicines against, we're starting to see that code be broken by AI. AI is a big force multiplier in enabling that to happen.
What we have today are companies that can go from what would historically have been running these massive screens that are incredibly time-consuming to doing that screening work in silico, and can go from model to molecule in a month's time, when it would have taken a couple of years.
That's a lot. That's already true today.
Alex Cornell
Already true today. Yep. There are companies like Lila Sciences and Enabla. You can basically ask the agentic system to develop a molecule against a certain target, and it can crack that code and give us something that we can work with and start running in experiments in a month's time.
Is it your impression that this is just going to happen? Is there no major risk left that AI will not have a major impact on the entire target and therapeutic discovery process? Are we now on a curve that just feels inevitable to you?
Alex Cornell
To me, we're on that curve.
When did that flip?
Alex Cornell
Very recently. I think for most of my career, there's been some version of machine learning and the hopes of AI really driving drug discovery and the development of novel medicines against those discoveries. I always worried that, in order for that paradigm to be true, it required data that didn't actually exist in any easy place.
If all you do is train AI models based on the research that's available, you unfortunately have a paradigm of garbage in, garbage out. One of the things that people don't appreciate when I start talking to them about what data exists is that, unfortunately, a lot of the recorded literature is actually incorrect. There have been tons of studies that show if you go try to replicate the experiments that are in the literature, you don't even get the same results.
Definitionally, if that is true and these AI companies don't have a source of creating novel data, what are you going to do? How are you going to train? We've seen just how powerful LLMs have been and how impactful they are across so many different areas of life because they've been trained on trillions and trillions of novel tokens.
And so data ends up being a big part of what drives advanced levels of intelligence and drives an intelligence revolution. The same has to be true in science. The AI companies that I believe are going to be most set up for success are the companies that have incredible AI talent, have access to significant amounts of capital, and can combine both of them in a novel way by which they can generate science tokens that don't exist in the public domain.
10. Citizen Pharmacology and the Peptide Movement
In fact, the generation of those tokens becomes a big driver of their moat, and not only the driver of the moat but actually what enables them to get to an increasing level of scientific intelligence that starts to separate from what can be achieved with LLMs without the benefit of those tokens. We're starting to see that. We've got one company that we're really close to today that's actually starting to show the bending of that curve and helping us to see that the idea of getting to scientific superintelligence is likely to follow a pretty deterministic set of scaling laws.
I think it was OpenAI that came out with this announcement, maybe working with Ginkgo or somebody, where they've created a closed-loop, automated lab and discovery process, and not just models but physical-world testing as well. If you close your eyes and think 5, 7, 10 years from now, what do you think the discovery process will look like at that point? I know it's hard to predict the future, but what's your best guess, knowing what you know?
Alex Cornell
I expect it to be completely automated. I was up at Lila Sciences the other day, and you go into their labs and what you see is all of these robotic arms. You see Petri dishes moving around in an automated fashion, moving from one spot to the next spot.
To me, I think what that means is the scale of data that's going to be required to be able to train these models—the trillions of tokens that are required—has got to move beyond the constraints of human hands, because it would just cost so much money to do it in a human-capital-driven manner. It has to be done robotically, and for that to be done, it has to have an agentic engine behind it and needs to produce data at a scale that's kind of unprecedented.
What I think the future of discovery looks like is agentic systems that can drive robots to do most of the experimentation that we're doing today with human hands.
That's the top of the funnel, right?
Yeah, exactly. Superstar, brilliant, amazing scientists who go down their life journey to become scientists that want to fight against disease and want to do work that matters are no longer going to spend 2/3 of their careers at the side of a bench, pipetting all day long. They're going to have all that time back to point their energy, enthusiasm, and optimism toward trying to figure out, “How do I use the systems and machines that I have and point them in the right direction, at the codes that we should be cracking?”
That's really enabled when you have the combination of brilliant human scientists force-multiplied by the agentic power of these systems that are being built. The more those agentic systems can be fully automated, where all of that lab experimentation is happening in real time and without the need for human interaction, I think the quicker and quicker it can scale, and I think the quicker and quicker we can achieve that level of scientific superintelligence.
What do you make of this whole peptides-plus-citizen-pharmacology side of things? I think they just came out and said there's going to be 14 or something peptides that are allowed to be compounded, and it seems to be a kind of deregulation happening in this space. People say “peptides,” I think, not really knowing what that even means, so maybe define it. I'm just curious what you think of this.
It really plays to your earlier point about these younger generations especially seeming to have a new attitude toward all of this stuff, which is, “I want to own this.” Part of owning it is a willingness to take risks that are above and beyond what I'm allowed to take. I'm just curious for your take on this subculture. It's fascinating to me.
You read about BPC-157 or these different kinds of—I think that's the number—all these interesting, different things that are being tried. Do you have a take on the impact that this will have?
11. Background and Career Journey
Alex Cornell
I think it's hard to know. The reality of it is, whether you look to the commercial success of GLP-1s or the massive movement around peptides, it's honestly not even limited to just peptides. You can go on Reddit and see people experimenting across all sorts of different dimensions.
I think what's happened is we live in a world where people want to go and figure things out that help other people, and now we've got platforms that allow people to share that. So we see the creation of groups that can exist today that couldn't exist in the past, before we had the technology we have today, and the communities that can get formed.
Whether you're looking at it from the perspective of people coming together under shared missions, that's happened throughout the history of humanity. This is a shared mission where people are saying, “I want to take my future health into my own hands, and I'm not willing to wait for scientists to take on this problem independently and for it to go down the traditional pathways. I don't have the time. I need to know the answers now, because I think for myself this is going to really matter.”
People have a hypothesis and they want to test it, and so they're fighting really hard to get those hypotheses tested. At the same time that you see what I would call that grassroots peptide movement, you also have a recognition by the FDA that we've got to move a lot faster.
So long as we have all these frictions in the system of going from a hypothesis for a medicine to the testing of a medicine in people and then ultimately to an approval, disease is going to keep winning. I think we're seeing, under Marty Makary, real leadership in wanting to break down those barriers and frictions that make the drug discovery and drug development process incredibly time-consuming and complex.
Some of the manifestations of the real-world impact of that span everything from Marty bringing in an AI system to help them comb through the thousands of pages of filings that sponsors behind medicines have to submit in record time, versus the armies of people that would have to comb through that and the days and days of time that are wasted. That goes all the way through to challenging every aspect of the process: In what settings do we not need nearly as much evidence in animals and can rely on cell-based experiments? In what settings do we no longer need multiple redundant studies that show us the same thing? We can cut through it with 1 study. Anywhere you look, we are seeing a movement to be able to do things more efficiently and faster, and have a greater impact.
I've had this experience with you countless times where I'll introduce you to somebody, we'll have a conversation like this, and somewhere between 30 minutes in and 230 minutes in, the person has a thought, which they rarely say, which is, “Who the hell is this guy?” We've done the same thing yet again, which is gone hours into the conversation without laying any sort of groundwork for your background. Can you just tell us your
Sure.
personal story a little bit?
Alex Cornell
I've just been super lucky. It's funny, now that you ask the question. I think, reflecting back on my childhood, I guess my parents were training me to be a biotech builder and investor since the time I was 5, but I had the greatest childhood ever.
I grew up in a typical American home. My dad was this relentless entrepreneur. He was the type of person who worked harder than anybody I knew, and he was so all-in on any business endeavor he was pursuing. Our entire family was all-in on it. Mom was doing the billing. My brother and I were in the garage refinishing furniture. I kind of grew up around business by being around my dad, and he was such an inspirational force in my life.
Despite the fact that he was such a relentless businessman, he was never really successful at any of those businesses. I think if he were sitting here today—and sadly, he passed from Parkinson's over a decade ago—one of the things he told me in those last few days was that he felt like he never stuck with anything long enough to see it through the tougher moments, and we'd quickly move on to the next thing and the next thing. I learned that lesson from watching him in real life and being in business with him.
You pair my dad with my mom, who's been an absolute force in my life. My mom is this incredible optimist, and from my earliest memories of my mom, I can remember her drilling into my mind, “We always commit and we never quit.” She pretty much convinced me that I could do anything I wanted if I put my mind to it.
I feel like from my dad, I got to experience and see what it means to take risks, and that you can fail and life goes on. From my mom, I developed this sense of resilience, and I think both of those attributes are probably very much connected to why, when I found medicine, I fell in love with it, particularly the discovery and development of it.
From that early childhood, I was the first in my family who got a chance to go to college. I graduated from MIT and had an amazing experience there. For me, being at MIT, learning more and more about business, economics, and science, and connecting it back to my early days of working alongside my dad and getting a chance, at the time not realizing it, to put money into some of the deals that my dad was doing was really meaningful.
I could put $2 into a rocking chair that we bought, and if we sold it for $200, I thought that was amazing. If we didn't sell it, I was pissed. I didn't realize I was learning in those early days about risk and reward from my dad. Then, when you get to a place like MIT and start to see the black-and-white version of the equations associated with that, it was a major step forward for me.
That inspired me to want to go on to New York City and Wall Street. I thought to myself, “No better place to really learn about business and how capital connects to business and what it takes than to come to the epicenter of that here in New York City.” So I ended up at Merrill Lynch and had some amazing mentors who were really inspiring to me.
I had 2 major stops at Merrill, 1 on the capital-markets side, and then, after doing that for a while, I wanted to go see how these crazy derivative securities traded. I had a chance to move to the Merrill Lynch derivatives desk.
What was so fun for me about reflecting back on that time is that I actually never picked biotech. When I got moved over to the derivatives desk, I was just put into biotech. I was assigned to the biotech subgroup of the derivatives desk and knew nothing about it, but I fell in love with it so quickly because the risk-reward in that setting was about life and death.
When I was looking at what was going on and the companies that I needed to understand to be able to price risk, it was wild to me. I had no idea about this entire field of the development of medicine. I had no real appreciation for the sheer amount of capital that's required to move it forward.
Here I am, through total serendipity, finding myself at the epicenter of needing to understand these companies deeply enough to price risk and getting a chance to be in front of all of the buy-side investors who were building and backing these companies. I became inspired by the work that they were all doing.
I was so inspired by it that, in my seat, I got to be out with these people a lot because they were curious about what activity was going on on the trading desk and what it meant for them and their investments. I was always interested in learning more about how they built and backed these companies.
What I quickly realized, in talking to all these people from all these different investment firms, was that their strategies were actually very similar. I said, “Huh.” Knowing what I knew about derivative securities from my days at MIT and my time at Merrill Lynch, and recognizing that most people in the life-science investment world were just using equity securities, it struck me that there was a better way to either build these portfolios or select securities.
There might be ways in which we could either maintain the type of return that they needed for their investors but at lower risk, or maintain the risk and produce a higher rate of return. So I went off and spent my nights and weekends writing this beautiful deck that I thought had really cracked the code on what portfolios needed to look like in the life-sciences sector that would allow a scale of capital to get behind these amazing medicines that had never before been achieved.
When it was done, I could not wait to send it out. I remember telling my roommate, Tom, “Tom, I'm ready to send this out. I'm going to send it to everybody, and you just watch. My phone is going to be ringing off the hook. Everybody in the world is going to want to do this and put this strategy to work, and my days at Merrill Lynch are numbered. I'm going to be out of here soon enough.”
I sent it out. Crickets. I didn't get 1 single response, and I couldn't believe it. I was like, “How does nobody want to do this? How does nobody want to run a portfolio that can produce the same amount of reward with lower risk, or produce more reward for the same risk?” It didn't make any sense to me.
It turns out that months went by before my phone finally rang, but then 1 day it did. It was Jeff Kaplan, who is today a dear friend and mentor of mine. He was the head of trading at that time, in 2005, at a tiny little firm named Deerfield Management, in its early days, when Jim Flynn had just taken over as general partner.
Jim was a really unique leader of Deerfield, because one of the things that I learned from spending time with him was that he obsessed over every way in which our investment firm could have every type of advantage in producing our returns, so that we could attract more and more capital and have more and more impact on the future of human health. How do we create advantages that would allow Deerfield to become the epicenter of capital to move innovation?
I got lucky. I found the 1 person in the world who cared about the things that I had to say. After going and presenting my ideas to what was, at that point, a tiny team of about 12 people, I got hired to join Deerfield.
I spent the next 15 years of my career helping to build Deerfield into that dream state of being the go-to source of capital for the industry. I didn't realize it at the time, but I guess I was 24 when I joined, and I think the next-youngest person at the firm was probably 40.
These were all people who were super-seasoned and had incredible experience. I think I was a bit of a novelty in the room because I would ask almost 1,000 questions every single day, and these amazing people would spend the time to teach me. The apprenticeship that I was able to get from my time at Deerfield was like nothing I could have ever imagined.
And I was all in. I was fully in love with investing in, building, and backing anything—whether that was a medical device, a diagnostic, a medicine, anything that could move human health forward. That spanned everything from helping these companies figure out how to finance their innovation all the way through to spending time with our team on how to design and help a company design a clinical study in a way that would give them an advantage in showing something that’s really special. And that stayed true for about the first decade of my time at Deerfield.
Then something really tragic happened. At Deerfield, we were constantly building capabilities and constantly wanting new sources of data. One of the sources of data that we had acquired and built out was taking us deeper and deeper into understanding a patient’s journey, from the moment when they are prescribed the medicine to when they actually get the insurance approval to get that medicine, and then how long they stay on the medicine. What I was quickly learning about a decade into my obsession with all the amazing work that was going on around me is that, yes, medicine only works if people take it, but they weren’t.
That was a really dark period for me in my own journey, because as I was reflecting on all the time and effort and capital that I was a part of putting behind innovation, it became pretty quickly evident to me that you have to start asking the question: For what purpose? If people need to be on a medicine for the rest of their lives, and they’re taking it for a year on average and then quitting, are we just optimizing for maximum expected returns, but no impact on public health?
12. Braidwell's Investment Approach
I had been married at the time. I got married in 2012, so I’d been married for some number of years. I started thinking about what my life means, and how I am as a partner to my wife if I’m spending my time just focused on making money and not actually doing something that can move the world forward. We had had our first baby at that point, and I was reflecting on just how impactful my parents were in terms of teaching me and what they armed me with as I went forward. I thought, well, what lessons would I be teaching my daughters?
I got to the point where the combination of thinking across all of those dimensions made me question: Am I just doing the wrong thing? Do I need to go in a different direction? The answer was no. What I needed to do was take the innate entrepreneurial energy that comes from my upbringing and my childhood, along with the skill set that I was able to develop from this amazing apprenticeship that I had at Deerfield, and point those talents not just at the discovery side of invention, but at the impact that’s required to actually see these medicines have the impact that they’re intended to have.
A lot of that was my inspiration for leaving Deerfield and wanting to go build Bridgewell. I’m so fortunate because one of our dear friends, Brian Kreiter, who is an incredible person—an amazing husband and father, and an incredibly talented businessperson—was also just as inspired as I was about where we found ourselves in the world and the type of impact that could happen but wasn’t yet happening. He was the chief operating officer for Bridgewater. I was co-running Deerfield, and we decided to spend some really deep time trying to put our lessons learned and our insights together and try to design, from a first-principles perspective, what the operating system for human health would look like. And what could we do to be the driving force behind making that happen?
13. The Kindest Thing
How could we be the force that is not just okay with a once-in-a-decade, $100 billion GLP-1 revolution, but become the force behind making sure that this once-in-a-lifetime, trillion-dollar cost-savings revolution happens? We can be the force behind medicines having their moment, where they could prevent diseases that are already preventable today. That really inspired us, and after seeing it, we couldn’t unsee it. We spent many more months thinking about how we would do it and how we would build it, and that became Bridgewell, where I’m spending my time today. We’re having the most fun that we’ve ever had.
And if you could sum up the investment approach in its simplest form, how would you do it?
I think I’d just bring you into what we call our morning meeting. At Bridgewell, we get the team together every morning from 9:15 until we’re done. I want you to imagine that you’re in this room—you’ve seen it—so, in this room, it’s a big room, and we’ve got an amazingly talented team of scientists, biostatisticians, commercial experts, AI experts, investors, operating people, traders, and structured finance people. We have a pretty significant team, and everybody on the team has some special superpower that they contribute to helping us figure out what companies have amazing technologies that we should be getting behind, backing, and helping to go as fast as possible to have human impact.
That cuts at some of those big unlocks that would be the difference between having something and having it make an impact. As we look across the ecosystem of everything that is moving forward today, where do we also see the major gaps where medicines should exist but don’t yet? To me, being in that room is the most fun part of the day, and I think it very much epitomizes what our philosophy is: In order to be a great backer of innovation, we essentially need to be able to answer 3 questions.
Are the innovations we’re getting behind going to work or fail? Are they ultimately going to be relevant from a market-potential perspective or not? And is there a way by which we could back this company, invest in this company, and enable this company to move forward faster with capital that produces a return that’s attractive enough for the investors who are trusting us with their capital?
We want to bring together the most talented minds in each of those different areas of domain expertise to give us an advantage that we can deploy in a replicable manner, day after day after day, to both back the companies that should be moving forward faster and make the companies that don’t exist but should exist.
It’s an incredible room to be in. It makes me wonder: If everyone could design their own room to be in from 9:15 to whatever every day, it’d be a fun exercise. Unfortunately, we’re out of time. I could literally—I have pages of notes. You and I do this every time we talk. We set aside an hour; we should have set aside a day.
I’ll go to my traditional closing question for this session, and I’m sure we’ll do this many times together over the years to come. What is the kindest thing that anyone’s ever done for you?
That’s my wife. I’m pretty darn hard at it every day. Every minute of the day, I can be hard at it, and that drives me to different levels of stress. I can get so myopically deep into trying to figure something out that I lose track of everything else around me. My wife, Cass, has this amazing ability to just know when I’m at that point, just on the precipice of a breaking point, and she can find some way to distract me, make me laugh, and get me back to neutral.
I think that’s a big force and an advantage for me, because I don’t have to worry about going so hard when I’ve got a partner who’s right there by my side and can help make sure that I can not just be going after things I really care about doing, but can have some fun along the way.
Knowing Cass, I know that’s true. Alex, thanks so much for your time.
Thank you. I had a great time.