Burton Ye

Platforms are in, point solutions are out as the healthcare AI category leaders come into focus this year. In conversation with Shelby Livingston at Endpoints News, I shared: 1. Why AI-first companies have the greatest platform potential and heuristics for identifying these opportunities at the earliest stages, 2. How companies are differentiating through co-development and distribution partnerships with leading healthcare institutions, and 3. Strategies for navigating anemic budgets and constrained market sizes through business model innovation such as AI-enabled services and pay for performance models Read more here: https://lnkd.in/dJWqv_zC Bessemer Venture Partners Abridge #healthcare #lifesciences #AI #generativeAI

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Here’s the No. 1 way a smaller Health Tech startup can compete with companies that have raised $100M+ of VC funding 👇 Become the best subject matter experts on the problem you’re solving. Let me explain… It can seem daunting when you see competitors in your space put out big announcements about how they raised $100M from brand name VCs. Yes it’s gonna help them get meetings with your favourite health system Chief Digital Officers (who you struggle to meet). Yes overnight their team size is going to 10x compare to yours (while you feel like your team is at its limits) Yes lots of people are going to think they’re winning and you’re falling behind (and maybe even your team feels that way too) But here’s the thing… The team that wins is ultimately the company that solves the problems of health system’s the best. Money doesn’t solve this… and very often money makes things worse for startups. Money can be a great accelerant… IF your playbook is proven and working. But very often, Health Tech startups raise lots of money and wild valuations… before that playbook was proven out. So they get distracted with having to spend that money to show progress. To grow fast and justify that valuation. Except pouring accelerant on a model that doesn’t work yet… is a recipe for disaster. Sure it sounds scary if they have a team of 100+ who can meet with health systems… BUT if they don’t deeply understand the problems, clinical workflows and change management needs… it’s a recipe for disaster and unhappy health system customers. When health systems are in the room with you and don’t feel like you truly understand the complexity of their problems… they don't care how much money you raised or how big your team is. Ultimately health systems just want their problems solved by those with the most expertise. So how do you outcompete those companies that have 10x more money and people than you? You concentrate your talent into a smaller, higher performing group. A group that deeply empathizes with, obsesses with and understands the needs of health systems. You get knee deep in the clinical content, workflows and change management challenges customers have. You bring that expertise to all your meetings. You use your smaller size and nimbleness to your advantage because you can share learnings and iterate the product, workflows and change management approach more quickly. And watch as health systems eventually realize your smaller but mightier team delivers where the over-capitalized, over-sized companies that lack true subject matter expertise… just don’t. I know this first hand because over the years SeamlessMD competed with companies that raised 10x more money than us. And at first it spooked us. But then health systems would complain to us about how those highly capitalized companies… “just didn’t get it”. Didn’t truly understand the clinical needs. Didn’t understand how to tackle the crazy workflows. Now many of them have come and gone.

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Sending a team of 5 people to a conference like HLTH in Las Vegas could cost $25K. 5 people at $2500 per ticket = $12,500 5 people's round trip plane tickets = $2,500 5 hotel rooms X 3 nights at the Venetian = $6,000 Ubers, food, miscellaneous = an extra $700-$1,000 per person? Maybe $24,000-$26,000. If you're getting a booth or sponsoring a happy hour, you're likely closer to $35K-$50K. Here's a story of conference ROI. It was 2019, I was just an SDR at my first healthcare conference attending with a great friend of mine. It was our company's first time at the conference. Just the two of us and a booth that was maybe 5 feet wide. Maybe we had one customer at the conference... Was anyone in our pipeline later that month? Nope. Was anyone in our pipeline for 3 months after that conference? Nope. BUT, later that year, I got an email from the CTO of an EHR I met who wanted to embed us as their preferred virtual visit platform....6 months before COVID started. A FULL year after that conference, a community mental health center brought in a consulting firm to evaluate virtual care platforms and the CMHC asked to include us in the evalution. Where'd they hear about us? A conversation I had with the Chief Administrative Officer...and a once a month email I sent him for the following year. A year later I was the AE leading the deal and they signed a 3 year deal worth six figures per year. Having a booth once doesn't make a difference. Sending a follow up email campaign through your marketing department doesn't make a difference. Measuring conferences based on your pipeline a month out doesn't cut it. Two of us turned a conference that cost less than $15K into more than $500K in total contract value. And don't even get me started about the value of actually being face to face with customers in a remote world... If you're debating HLTH and want to talk conference strategy, let's talk. DMs open. #HLTH #Conferences #DigitalHealth

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Hot take on a lot of early-stage digital health companies out there: You're not a tech company. Most tech-enabled care companies I've seen over the past two years are only tech-enabled in the sense that they use telehealth as their delivery mechanism for care. There are exceptions to this, of course - companies who build computer vision and applied AI tools to better the doctor-patient experience, companies who build tooling around risk scoring and stratification to enable more personalized medicine, companies who build truly novel intakes to better route patients to the appropriate care, etc. These companies have real technology chops and, if they sell it right to the market, can get credit for this from investors. But if you're truly a telehealth provider, you need to realize now that the goal post has shifted dramatically from 2021 and you're going to be valued at maturity at something like 3x EBITDA. That's profit. Not revenue. Throw a revenue multiple out the window. That's not the world we live in if you're a virtual doctor's office. Think of how that impacts venture math. If you're raising a seed round at $15M post-money (or $12M pre-money), it means you'll have to generate something like $150-200M in annual EBITDA to be a fund returner for your seed investors. Maybe even more with dilution, since telehealth businesses are not traditionally capital efficient and will likely need to raise material additional capital to reach that scale. You need to be ridiculously profitable (probably on $800M-$1B in annual revenue since you're likely going to be a 40% gross margin business). Here's the good news: you can set yourself up well (and probably be a contrarian founder relative to your peers), by talking about EBITDA growth and how you can grow into a fund-returning outcome based on realistic mature market comps. This will stand out for the investors you're pitching, even at the early stage. This is how you can beat the malaise of the tech-enabled care market. Focus on the right metrics and the right type of growth. You don't have to have all the answers (no founder does), but you need to make sure the ship is headed in the right direction. A focus on profitability for "tech-enabled care" (*ahem* telehealth) businesses is a good first step.

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Someone broke down the estimated costs of a $15 Sweetgreen salad. We need these cost graphics for digital health to help future founders. Especially for tech enabled cos, the greatest cost is labor. Much of the "value created" is in curation and matching, which means the gross margins are reliant on labor arbitrage. Pay someone $X, but get paid $X+Y% per visit. The challenge with healthcare is that you often have to pick one of two business models: 1. specialized, low volume, high cost, low gross margin % 2. generalized, high volume, low cost, high gross margin % I'd argue founders should focus on gross dollars over the lifetime of the customer (like Jeff Bezos said) instead of gross margin %'s, but we'll leave that for another time. The challenge is that many tech enabled digital health cos have high cost of goods sold (labor) and moderately high product, design, and engineering budgets. We must build differentiated solutions for patients, clinicians, and clients to be out incumbents, however, we're realizing that companies are ultimately valued on the discounted value of future cash flows. And the high SG&A costs at most organizations might be inbalanced to the unit economics of the business. I'm not sure the math pencils out for everyone unfortunately. But I'm just a guy on the internet, would love to hear the thoughts from those smarter than I (you!). Comment below. --- p.s. I have no idea the accuracy of the graphic and not an investor in Sweetgreen. Cheers. Credit: David Crowther

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Excited for this one. Congrats to Alex Cohen and Hello Patient on their seed round announcement. Hello Patient stands to change the communication paradigm between patients and providers forever. Their generative AI call agent technology is tackling the tremendous admin burden of patient facing comms (scheduling, follow ups, referrals, prescription refills, etc). Massive opportunity and we think Alex and his team are expertly positioned to become market leaders. Max Ventures is thrilled to co-lead the seed round with 8VC and Bling Capital A great quote below from Alex highlighting the concept of "service as a software". Healthcare is a heavily service oriented industry - so the opportunity for step change is even more profound. The startup's approach is part of a paradigm shift where AI companies are offering service as software. "I'm a big believer that the right way to do this is through a managed services business. We're not building SaaS. I believe we can do this services as software where what was traditionally a services business now has software margins because I don't have to go employ a whole bunch of people to do the services under the hood," Cohen noted. https://lnkd.in/ehNN2AmW

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One conversation we should be having more, especially in healthcare: is this an AI problem or a policy problem? A big challenge in American healthcare stems from the reality that our healthcare strategy changes with every administration. Throwing AI at problems that are well-addressed by policy innovation (e.g., AI for payer-provider RCM war) feels like a gross misallocation of resources. Solution sets are rarely zero sum – in truth, most problems will require policy, tech, and human interventions, but it's worth asking ourselves whether AI is the best solve when we have a multitude of options.

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Couple of weeks ago had the pleasure of sharing my story to Alexander Benkendorf about starting CastPrint and later moving on to join Verge HealthTech Fund and the learning along the way. Some topics we discussed: 💡What does it take to bring innvation in healthcare 💡How did my startup background help me better prepare for VC work 💡How founders can better engage with VCs and what are the tips and tricks from the "other side" Thanks Alexander for having me!

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I've received a ton of BAD advice about building a Health Tech startup. Advice that makes sense for many Tech startups… but NOT for Healthcare 👇 Here were the worst ones: 1️⃣ “You (the CEO) should stop spending so much time with health system customers. Delegate that to other people.” → Turns out that actually hurts companies in highly verticalized, complex spaces (and I think it’s actually bad advice in general). Being in the details matters, and that includes being in the details on what matters to health systems. 2️⃣ “You’re bringing too many team members into meetings with health systems.” → Turns out healthcare is complex, and being able to have subject matter experts across clinical, change management and integrations who can get into the weeds of clinical scenarios and workflows helps build trust with health systems. 3️⃣ “Why are you creating all this clinical content? Just be a pure tech platform where health systems can create their own content.” → Turns out clinicians don’t have time to create content, workflows and algorithms from scratch. Plus, if there are templates, they need to be super high quality and evidence-based for clinicians to use them. 4️⃣ “You’re providing too many services for health systems (e.g. high-touch clinical content and change management support). You should be more of a tech-only platform.” → Turns out those “tech-only” platforms collect dust on the shelf. Yes our support is more resource-intensive and yes we go above and beyond for our health system partners… but it gets the best results in the industry. 5️⃣ “You should go direct-to-consumer and not work with hospitals and health systems.” → Turns out that works great for low-complexity situations (e.g. walk-in telemedicine), but how does that work for highly complex care with lots of clinicians involved (e.g. navigating patients through a cancer journey)? It doesn’t. 6️⃣ “You should hire mostly seasoned folks with decades of experience in healthcare and business.” → Turns out many of our most impactful team members (including many of those that our health system partners love working with) were relatively early in their careers when they joined SeamlessMD. I’ve realized that someone’s self-motivation and potential are far better indicators of success here than years of experience (of course, easy to say and hard to evaluate for!). What would you add?

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The GLP-1 space has continued to explode, with the potential for impact expanding to cardiovascular risk, sleep apnea, and liver disease. So who are the emerging players poised to challenge Lilly and Novo? The incoming players to watch are a mix of startups and incumbents. In the startup realm, Viking Therapeutics, Inc., and Altimmune, Inc. have gained significant attention as their GLP-1 candidates demonstrate solid weight-loss outcomes. For San Diego based Viking, weekly doses of VK2735 delivered weight loss of up to 13% compared to placebo in a Phase 2 trial. Perhaps most exciting, the weight loss did not plateau at any time during the 13 week study, suggesting longer duration doses would result in further weight loss. Meanwhile, Altimmune's Pemvidutide (being studied for both obesity and MASH) is on track for an end of phase 2 FDA meeting in Q3 of this year. Notably, Pemvidutide has showed promise in limiting the amount of weight loss derived from muscle, which is a notable problem with the existing GLP-1s. A recent phase 2 trial showed only ~25% of weight loss was from lean mass, more in line with the ratio seen in typical diet & exercise programs. There are also several incumbents working hard to establish their presence. Roche's $2.7B acquisition of California-based Carmot Therapeutics, Inc. Therapeutics in December and Amgen's MariTide are both notable. Roche recently announced data from a Phase 1B study for CT-388 showing placebo-adjusted weight loss of ~19%, with 85% of participants seeing weight loss of more than 10%. Not to be left out, Amgen has recently advanced MariTide into Phase 2 studies, with Phase 1 results published in February showing weight loss of up to 15% in 12 weeks, with some dosage levels only required once a month. To have a credible chance at challenging the existing market leaders, new GLP-1s will have to demonstrate meaningful improvements on the following: 1. Dosage - most approved therapies today (with the exception of Rybelsus) are subcutaneous injections, given weekly. Having an easier form (tablet) or frequency (bi-weekly or even monthly) would be a big advantage. 2. Preservation of lean muscle mass - helping patients derive weight gain from regular adipose tissue instead of muscle mass. 3. Benefits beyond weight loss. Novo's recent FDA label expansion for Wegovy for reducing the risk of serious cardiovascular events provides a blueprint of how to expand the area these medicines can be helpful in. While there are many companies active in the space, it's worth noting just how large a lead Lilly and Novo have in this future $100B+ market. A recent GlobalData report noted that even by 2029, these two giants will have ~80% of the market between them. That said, 20% of a $100B market is still a sizable prize for other innovators, and continued innovation will only help patients.

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Of note: Your health records are coming to new apps This in an interesting change, and a somewhat Epic change. All puns intended. If you don’t know, the leading medical record storage solution in the US is operated by Epic. A rather critical problem is that if you walk (well drive) between two hospital in the US, the medical records tend not to follow you, unless you carry a large Manila envelope. Having Epic (and others) via TEFCA allow export of records arguably allows you to only carry your phone, which is a very siginificant change. This also (arguably) opens up a huge new innovation sector. Epic is one of the organizations that has been helping the US federal government establish the Trusted Exchange Framework and Common Agreement, or TEFCA. The goal being to iron out both the legal and technical requirements for sharing patients' data at scale. Health-care data in the U.S. has historically been siloed and difficult to move around. Clinics, hospitals and health systems can store their information in a variety of formats across dozens of different vendors, and there hasn't been a trusted nationwide mechanism in place for transporting it securely. This means if a patient moves to a different state or visits a new hospital, their medical records tend not follow. PS. If you want appreciate how profitable the US medical sector is, Epic HQ has a restantant designed to look like Kings Cross from the Harry Potter movies. https://lnkd.in/g8NaWza8

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Presenting at the Senate as part of the Coalition for Health AI (CHAI) "Day on the Hill" wasn't on my 2024 bingo card, but I'm feeling energized by the bipartisan discussions on healthcare AI. The numbers tell a compelling story: while nearly 2,000 healthcare AI startups have received funding over the last two decades, only 1 in 20 provider-facing companies reach late-stage maturity. Beyond natural market dynamics, two critical barriers are holding back AI's full potential in healthcare: unsustainable payment models and inadequate evaluation infrastructure – only 5% of research studies on LLMs in medicine utilize real patient care data, and studies advancing our understanding of performance beyond medical licensing exam benchmarks remain anemic at best. At CHAI, we're advocating for essential foundations: • Rigorous technical model performance evaluations • Comprehensive bias assessments across diverse patient populations • Thorough pre-deployment simulations and prospective studies • Robust ongoing local monitoring The path forward demands strong reporting infrastructure, advanced healthcare AI benchmarks, and meaningful public-private partnerships to drive real-world AI deployment in healthcare. Stay tuned for CHAI's upcoming initiatives in 2025 as we expand our engagements with the startup and investment ecosystem. https://lnkd.in/enw-GQcA

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Hot off the pre-print server – an important publication authored by the Atropos Health team exploring the performance of LLMs in answering real-world clinical questions. LLMs excel at summarizing and contextualizing existing literature, but cannot generate de novo medical evidence today. The results of the study highlight performance gains attributable to injecting novel, relevant, and up-to-date medical evidence into LLM-powered clinical decision support systems. Brigham Hyde Nigam Shah Saurabh Gombar Read the study here: https://lnkd.in/ecuU25Pq

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A playbook for managing the biggest risks in early-stage health tech adapted from Wesley Fogel article on Peerr 🚀 👥 People Risk: Engage users, decision-makers, and clinicians early with prototypes and iterative feedback. 🏥 Clinical Risk: Ensure safety through external evaluations and compliance with standards like DTAC and DCB0129. 🔒 Security Risk: Prioritise data security and compliance with HIPAA, ISO27001, and other standards. 🛠️ Technical Risk: Avoid technical debt and optimse your tech stack with an experienced CTO. 🏛️ Governance Risk: Build a diverse advisory team to guide ethical, legal, and regulatory strategies. 🌐 International Risk: Weigh the benefits of early overseas exploration against potential resource strains. 💰 Financial Risk: Focus on vision, team, and go-to-market strategies at different funding stages. 📈 Commercial Risk: Maintain ongoing customer engagement and seek formal partnerships through accelerators. https://lnkd.in/e8BPBnEv

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🎬 Matt Damon and 🏈 Colin Kaepernick have invested in it, and so has 💰Andreessen Horowitz... Function Health's executive team has "engineered a first-of-its-kind approach that focuses on prevention and empowerment"—very much in line with what we aimed to achieve with Carebook when we started it over six years ago. Could they be the ones to fulfill their lead investors' prophecy (link at the bottom) and Dr. Eric Topol, MD's premonitions in his books "The Patient Will See You Now" and "Deep Medicine"? They have just secured a $50 million grant. Let's hope this is not another Theranos and that we are truly witnessing the rise of the next generation of direct-to-consumer health companies. These companies will be key players in the "transition from reactive to proactive" health care that the system—and we—desperately need. What do you think? Links: 📝 Investment round press release: https://lnkd.in/eUG87qkf 🔗 Andreessen Horowitz's prophecy: https://lnkd.in/eZATCf4f

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I recently sat down with Michael Batko, CEO at Startmate and Founder of Puddle Pod for Episode 11 of Insane Ambition. Startmate has invested in 230+ startups, much of it under Michael's leadership, and now has $3.5b in value across its portfolio companies. In this episode, we discussed: - Michael's journey from consulting, then living in the Amazon rainforest, to leading Australia's biggest startup accelerator - The future of Australia's startup ecosystem - The labour government's very stupid plan to make it harder for people to qualify as sophisticated investors (now thankfully shelved) - Startmate City! Startmate's plan to build Australia's first startup city. Probably the most ambitious idea I've ever heard from a startup accelerator. - The balance between visionary thinking and traditional startup advice (think Elon Musk's plan to colonise Mars, vs Y Combinator's problem/customer obsession) - "The Courage to Be Disliked", and its influence on Michael's approach to life and business. Links in the description below 👇

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🔍 𝐅𝐢𝐧𝐝𝐢𝐧𝐠 𝐏𝐫𝐨𝐝𝐮𝐜𝐭-𝐌𝐚𝐫𝐤𝐞𝐭 𝐅𝐢𝐭: 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬 𝐟𝐫𝐨𝐦 𝐒𝐞𝐪𝐮𝐨𝐢𝐚'𝐬 𝐉𝐞𝐬𝐬 𝐋𝐞𝐞 🔍 Sequoia's Jess Lee on identifying product-market fit for early-stage startups: - Understand customers' needs deeply. - Iterate based on feedback. - Solve real problems. - Observe user engagement. - True product-market fit: Consistent user returns and recommendations. #StartupSuccess #ProductMarketFit #Entrepreneurship #CustomerFeedback #Innovation #Sequoia

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What do bio and health applications mean for the next wave of AI -- specifically about compute? (I'm talking to you NVDA longs!) LifeX Ventures is hosting a super roundtable with some serious techbio leaders tomorrow along with Analog Century Management's Val Zlatev -- come hear Thomas Clozel Sean McClain Chetan Patel at 11am ET For the survey results based on asking 100 techbio CTOs and CEOs, join the call. Here, my own speculations after wrapping up the report: -- Amazon needs to have a GPU program on warp drive right now -- Nvidia needs to have a data center / cloud business in the works -- Edge AI chips are about to be everywhere -- in your watch, car, sneakers, thermostats, gene sequencers, spectroscopes -- All this compute needs way more data: expect a boom in sensors of all types -- Remember human genome moonshot that sequenced one person once? Now you can sequence your every cell one by one. Expect that for protein folding (AlphaFold was that moonshot) and other simulation uses, a full "twin" model of you, cell by cell -- Google has no angle here -- worse chips, worse cloud, worse models, worse phones / edge devices -- Specialty silicon for unique use-cases, lower-power, lower-memory are surely coming fast - like back in the day for mobile phones when Qualcomm, Broadcomm, Infineon, Mediatek, etc duked it out.

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Generally surprised to not see more hardware vendors in healthcare and life sciences partnering with AI-first companies. When the zone of genius of a company is hardware, it's difficult to imagine that same team achieving parity on an AI product – Apple may be the greatest example of success in this realm, and still has secured many AI capabilities via targeted M&A (Siri, Turi, Xnor.ai, Voysis, Inductiv). Given the importance of leveraged distribution models in the ossified industries of healthcare and life sciences, it seems there is untapped opportunity for more hardware manufacturers to partner and co-develop AI products with startups. Control over the way data is captured and processed is critical for building high quality training data sets, which creates an interesting feedback loop between hardware companies and potential AI-first startup partners. Interested to explore this further with folks in healthcare and life sciences hardware!

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