Health Sector Investment

Doing Good while Doing Well There are different ways to play Healthcare. Here is food for thought, and three key considerations. - Healthcare’s weight in the S&P 500 is at its lowest since March 2000. The Healthcare sector has a diverse array of companies from Biotech, Pharma, Medical Devices, Services, Insurance/Managed Care, Hospitals, Pharmacy, Manufacturers/Distributors. Despite the growth in annual healthcare in the U.S., which now exceeds $5 trillion, it is interesting to note how out-of-consensus the healthcare sector is. - Private Credit healthcare loans represent great value. PE sponsors are active in roll-ups and to corporate spinoffs creating significant need for financing. It is notable that Marathon Asset Management has never been busier in healthcare direct lending, sourcing, and originating more healthcare deals this calendar year than any other industry sector. - Compelling value exists within the senior living housing sector, which includes independent living communities and assisted living facilities. Providing senior financing to established sponsors/operators, helps fill the capital need for new construction and existing properties. The senior citizen population has increased 40% during the past 15 years creating an unprecedented demand for senior living facilities. With people living longer and requiring specialized care, the healthcare system faces critical capacity shortages in assisted living, skilled nursing facilities, and independent living. Together, this drives significant investment and development needs across the senior care Real Estate sector with an estimated total annual living expenses of $120 billion annually. Operators are generating strong cash flow as the national medium monthly cost for a senior resident is approaching $5,000 for independent living, $6,000 for assisted living, and $9,000 for nursing home (all single rooms). Backing healthcare is where alpha meets impact—proof that investment returns, and social responsibility go well together.

HealthTech AI is no longer exciting. It’s expensive. And the market has re-priced itself for performance. The first half of 2025 solidified a new reality in digital health. US-based digital health startups secured $6.4 billion across 245 deals (Rock Health). While total funding is up from H1 2024, the trend of fewer, larger checks persists. Rock Health pegs the average deal size at a robust $26.1 million, a significant increase from $20.4 million in 2024, signaling a concentrated investment in more mature, impactful companies. Investors are no longer buying potential. They're buying precision and demonstrable value. They care if your AI: Saves hours, not just clicks: The focus is on quantifiable time savings for clinicians and administrative staff, directly addressing burnout and efficiency gaps. Cuts costs, not just code: Real-world cost reduction is paramount, whether through optimized operations, reduced errors, or improved resource allocation. Embeds in real workflows, not pitch decks: Solutions need to be seamlessly integrated into existing healthcare systems, proving their utility in daily practice. McKinsey calls this the "productivity premium," and it has become the new funding filter. A significant portion of VC dollars continues to flow into AI-enabled startups, not because they're novel, but because they perform and deliver tangible returns. Abridge: This AI note-taking startup for doctors raised a staggering $316 million in June 2025 (Series E), bringing its total funding to over $770 million. Its value proposition is clear: giving clinicians hours back by automating documentation. Innovaccer: Secured $275 million in Series F funding in January 2025 to expand its AI and cloud capabilities, aiming to be a "one-stop shop" for healthcare AI solutions. They focus on data aggregation and intelligence to optimize value-based care programs and reduce administrative burden. Truveta: Raised $320 million in Series C funding in January 2025, solidifying its position in health data and analytics. Their mission revolves around leveraging data to drive insights and improve care. Hippocratic AI: Completed a $141 million Series B financing round in February 2025, valuing the company at $1.64 billion. Their focus is on developing safe, patient-facing AI for non-diagnostic tasks, addressing healthcare staffing shortages. These companies optimize operations, not optics. The delta? Execution. This is not a hype cycle. It’s a competency correction. The end of vision-only founders. The rise of operator-founders who understand: Unit economics: The true cost and value generated by each patient interaction or service delivered. Integration latency: The speed and ease with which new technologies can be embedded into complex, often legacy, healthcare IT infrastructure. Reimbursement drag: Navigating the intricate and often slow process of getting innovative solutions covered by payers. What part of this feels uncomfortably true?

Gavi has published a new report to outline how our partnerships with multilateral development banks including The World Bank, European Investment Bank (EIB), Asian Development Bank (ADB) and Asian Infrastructure Investment Bank (AIIB) unlocks innovative solutions to reach millions more children with life-saving vaccines. With countries’ health systems already straining to meet the demands of their growing populations, the need has never been greater for smart, sustainable investments that deliver benefits to public health and economic stability: https://bit.ly/43I3E8Z

The AI in cardiology market is forecast to reach $4.52B by 2033. Most of that projection is built on imaging, ECG analysis, and workflow optimization. Here is what the forecast misses: the operating room. Cardiac surgery generates more data per minute than any other clinical setting. Hemodynamics, electrophysiology, perfusion parameters, tissue characterization, continuous ECG, real-time imaging. A single CABG case produces a dataset that would take a cardiologist months to generate from outpatient encounters. Yet the vast majority of AI-in-cardiology investment targets the clinic, not the OR. The reason is simple: OR data is harder to capture, harder to structure, and harder to validate. The regulatory pathway is steeper. The liability questions are sharper. That is exactly why the opportunity is largest in the OR. At ATARI AI, we are building the cardiac surgery foundation model. Not for one procedure. For every operation, every patient, every decision point from anesthesia induction to ICU discharge. The 18 robotic AF ablation cases in our ROK-AF pipeline produced more actionable data on fibrosis burden prediction than any imaging-only AI study I have seen published this year. The $4.52B forecast is conservative. It will be revised upward when the surgical AI companies begin reporting clinical outcomes. That inflection point is 18-24 months away.

I would like to flag a strategic imperative for both Medical Affairs and Commercial leaders to drive innovation and market leadership. AI's full potential requires a strategic approach that addresses key challenges and capitalizes on emerging trends. Leveraging interdisciplinary collaboration and human skills to overcome barriers in AI-driven research, ultimately will enhance both scientific integrity and market competitiveness. I: A Competitive Advantage Reproducibility in AI-based research is not just a scientific imperative—it's a commercial necessity. The "black-box" nature of many AI models can lead to skepticism among HCPs and regulatory bodies, potentially impacting product adoption and approval processes. By championing transparent, reproducible AI methodologies, medical affairs leaders can: 1. Build trust with key opinion leaders and healthcare providers 2. Streamline regulatory submissions and approvals 3. Enhance the credibility of marketing claims and scientific communications Business leaders should recognize that investing in reproducible AI research can differentiate their products in a crowded market, providing a strong foundation for marketing strategies and stakeholder engagement. II: Interdisciplinary Collaboration To unlock AI's transformative potential, medical affairs and commercial teams must foster collaboration between AI specialists and domain experts. This interdisciplinary approach can: 1. Accelerate drug discovery and development processes 2. Identify novel biomarkers and therapeutic targets 3. Optimize clinical trial design and patient selection 4. Enhance real-world evidence generation and analysis By breaking down silos between departments and encouraging cross-functional projects, business leaders can create a culture of innovation that drives both scientific advancement and commercial success. III: Investing in Your Team's Skills To stay competitive in the AI-driven healthcare landscape, medical affairs and commercial leaders must prioritize skill development within their teams. Key areas of focus should include: 1. AI literacy and data science fundamentals 2. Ethical considerations in AI-driven healthcare 3. Regulatory compliance in AI-based research and applications 4. Effective communication of AI-derived insights to diverse stakeholders By investing in these skills, business leaders can ensure their teams are equipped to leverage AI technologies effectively, from early-stage research through to market access and commercial strategies. IV: Conclusion For medical affairs and commercial leaders, embracing AI-driven research is not just an option—it's a strategic imperative. By addressing reproducibility challenges, fostering interdisciplinary collaboration, investing in emerging skills, and enhancing the employee experience, leaders can position their organizations at the forefront of scientific innovation and market leadership. #CommercialExcellence #MedicalAffairs #GoToMarket #pharma

AI in the OR is cutting costs—and complications. Here's how! Surgeons partnered with AI algorithms see 32% fewer complications during complex procedures. Every case without complications means one less extended hospital stay. Consider the financial impact. A single avoided complication saves hospitals approximately $8,300 per patient. Multiply this across thousands of procedures annually and the numbers become significant. Beyond cost savings, AI-assisted tools enhance surgical precision. They provide real-time feedback on instrument positioning, tissue identification, and critical decision points during procedures. Efficiency increases as well. Operating rooms utilizing AI systems report 18% faster turnover times between cases. This translates to more procedures performed daily without sacrificing quality or safety. Patient recovery accelerates with AI-optimized surgical approaches. Data shows an average reduction in hospital stays by 1.4 days when AI tools assist in surgical planning and execution. Medical device companies recognize this shift. Those integrating AI capabilities into their surgical tools gain market advantage as adoption increases across healthcare systems. For surgeons and OR staff, the learning curve proves worthwhile. Initial training investment yields consistent improvements in outcomes, ultimately reducing workload through fewer complications. Hospital administrators take note: implementing AI-assisted surgical platforms delivers return on investment typically within 14 months through combined efficiency gains and complication reductions. The future of surgery involves human expertise enhanced by artificial intelligence. Early adopters will benefit most as these systems continuously improve through machine learning from each procedure performed. Will your surgical team embrace AI tools to improve patient outcomes while reducing costs? The technology exists today, waiting only for implementation.

In March 2020, EIT Health and McKinsey published their AI healthcare analysis. Five years later: what materialized vs. what exceeded expectations. VALIDATED PREDICTIONS: • 74% reduction in physician burnout via ambient AI scribes [1,2] • VC funding: $8.5B → $23B by 2024 [3,4] • FDA AI devices: 223 → 1,250+ [5,6] • Radiology: 76% of AI device approvals [7] SLOWER PROGRESS: • Data interoperability remains a barrier [8] • 22% organizational adoption; payer sector: 14% [8] EXCEEDED PROJECTIONS: • Healthcare AI adoption: 2.2× broader economy [8] • Market: $29B (2024) → $500B+ projected (2032) [9] • Procurement cycles: 18-22% faster [8] UNFORESEEN PARADIGM SHIFTS: • Foundation models (ChatGPT, 2022): Generalist medical AI [10,11] • AlphaFold: Nobel Prize 2024, AI drugs in trials [12,13] • Multimodal AI integration [14] • Ambient documentation dominance [2] KEY INSIGHT: The 2020 analysis correctly identified AI’s transformative potential and core application domains. However, the technological mechanisms driving this transformation—particularly foundation models and breakthrough scientific AI—emerged after publication. The fundamental barriers identified (data governance, interoperability, ethics, workforce development) remain central challenges, though the tools available to address them have evolved substantially. FINAL TAKE-AWAY: The healthcare AI revolution is not following a linear path—it’s characterized by exponential technological breakthroughs intersecting with persistent structural barriers. Success requires balancing rapid innovation adoption with rigorous attention to the foundational challenges of data quality, governance, and equitable access. References: [1] Olson et al. (2025). JAMA Network Open - Ambient AI scribes and physician burnout [2] Topaz et al. (2025). PMC - AI scribes in clinical practice [3] EIT Health & McKinsey (2020). Transforming healthcare with AI [4] Silicon Valley Bank (2025). Healthcare VC Investment Report [5] Bipartisan Policy Center (2025). FDA AI Device Oversight [6] Stanford HAI (2025). AI Index Report [7] Goodwin Law (2024). FDA AI Medical Device Approvals Analysis [8] Menlo Ventures (2025). State of AI in Healthcare [9] Fortune Business Insights (2025). AI in Healthcare Market Report [10] Mass General Brigham (2023). ChatGPT Clinical Decision Making Study [11] Nature (2023). Foundation models for generalist medical AI [12] Drug Target Review (2024). Nobel Prize AI protein structure [13] Nature Medicine (2025). AI-enabled drug discovery clinical milestone [14] PMC (2025). Multimodal AI for integrating imaging and clinical metadata #HealthcareAI #DigitalHealth #ArtificialIntelligence #HealthTech #MedicalInnovation #ClinicalAI #HealthcareInnovation #AIinMedicine #DigitalTransformation #HealthcareLeadership #FutureOfHealthcare #PrecisionMedicine #HealthIT #AIResearch #HealthcareData

Think AI adoption is moving fast? Look at Healthcare. Healthtech used to be a tough category in venture: long sales cycles, pilots that dragged on, and hospitals and doctors slow to adopt new tech. Not anymore. With AI, the pace has completely shifted and 𝐇𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 𝐡𝐚𝐬 𝐛𝐞𝐜𝐨𝐦𝐞 𝐭𝐡𝐞 𝐡𝐨𝐭𝐭𝐞𝐬𝐭 𝐀𝐈 𝐯𝐞𝐫𝐭𝐢𝐜𝐚𝐥 𝐢𝐧 𝐕𝐂. Next week I’m doing a fireside chat with my friend Edward Kliphuis from Sofinnova’s $200M Digital Medicine fund. During our prep, we commented on 4 stats about the growth and adoption of the category that are truly mind blowing: 1. AI medical scribes (like Abridge, Ambience Healthcare, Nabla) reached 50% hospital penetration in <2 years. For comparison: EMRs took 7 years to hit the same mark (Source: 2025 Healthcare AI Adoption Index) 2. In 2024, Healthcare had the highest enterprise AI spend, far outpacing legal, finance, and media. GenAI spend in Healthcare was 5x greater than in Financial Services (Source: The State of GenAI in the Enterprise Report). 3. OpenEvidence, a 3-year-old AI copilot for doctors that reached unicorn status this year, is now used by 25%+ of all US physicians and is adding 25K verified doctors per month. It’s on track to hit 50% of US doctors by end of year. One of the fastest tech adoptions in medical history. 4. AI Health startups dominate the new unicorn list in 2025: Abridge ($5B), Hippocratic AI ($1.5B, just 2 years old), Neko Health, OpenEvidence, ... together they represent ~50% of all new unicorns in Q1 (Source: PitchBook). Healthcare (20% of US GDP) is a data discipline. Scattered, massive amounts of unstructured data and docs that need to be aggregated, synthesized, and moved. GenAI was made for this. The revolution isn’t coming. It’s here. And at LifeX Ventures we are proud to be part of it.

💥NURSING EXCELLENCE & ROI💥 Investing in Quality and Sustainability in Healthcare ✅ What is ROI (Return on Investment)? ▪️A performance measure used to evaluate the efficiency or profitability of an investment. ▪️In healthcare, ROI includes both financial gains and non-financial returns like >improved quality >patient safety >staff engagement >reputation >better ratings >financial profits ✅ What is Nursing Excellence? ▪️A culture and standard of care that promotes high-quality, evidence-based nursing practice. ▪️Involves >empowered nursing leadership >professional development >shared decision-making >innovation >continuous improvement in patient outcomes. ✅ How are ROI and Nursing Excellence Connected? Nursing excellence leads to: ▪️Better patient outcomes and safety ▪️Lower turnover and vacancy rates ▪️Increased patient and staff satisfaction ▪️Improved quality metrics and regulatory compliance These outcomes directly and indirectly contribute to financial sustainability and organizational reputation — key components of ROI. ✅ Why is Nursing Excellence Critical for Long-Term Sustainability? ▪️Elevates the organization’s brand and recognition in the healthcare market ▪️Attracts and retains top nursing talent ▪️Strengthens interprofessional collaboration and care coordination ▪️Aligns with value-based care and quality reimbursement models ▪️Promotes resilience, adaptability, and innovation during healthcare challenges ✅ How Can Healthcare Leaders Support Nursing Excellence Initiatives? ✔️Prioritize and fund nursing-led quality improvement projects ✔️Engage frontline nurses in decision-making and strategic planning ✔️Invest in leadership development and professional certification ✔️Champion the value of nursing excellence at the executive level ✔️Align nursing goals with organizational mission and strategic objectives ✅ Nursing Excellence Accreditations Leads to long term success and greater ROI as it enables to ▪️Share success stories and measurable outcomes ▪️Highlight the connection between accreditation and improved clinical performance ▪️Involve multidisciplinary teams in readiness and planning ▪️Create a compelling vision for how excellence benefits staff, patients, and community ▪️Celebrate milestones and recognize contributions throughout the journey 🟢 Nursing is the largest workforce in a hospital setup and most patient care services sought in hospitals are dependent on skilled nursing care. Nursing excellence is not just a badge of honor — it’s a strategic investment with measurable ROI that drives ▪️safety ▪️quality ▪️satisfaction ▪️culture, ▪️and long-term sustainability in healthcare. Disclaimer: The views expressed are solely my own, gathered along the learning journey and intended for professional learning and reflection. They do not represent any organization, group or individual directly or indirectly affiliated. This should not be taken as clinical or legal advice.