How Advanced Therapies Are Transforming Healthcare

Last month, a team of scientists and physicians achieved something extraordinary: they developed and delivered the first-ever personalized #CRISPR therapy to treat an infant with a life-threatening #raredisease — in just six months. A one-letter change in the baby’s DNA was corrected using a custom-built gene editor. The child, who was once facing the prospect of a liver transplant, is now steadily improving. It’s a powerful example of what’s becoming possible at the intersection of #science and #technology, urgency and purposeful ambition. And this isn’t an isolated win. Across labs, clinics, and companies, CRISPR is being used as a therapeutic modality to correct inherited disorders, engineer immune cells, disable viral DNA, and even edit entire chromosomes. New gene-editing systems—like TIGR-Tas, unveiled earlier this year—are expanding what’s possible in tissues or conditions where current tools fall short. Clinical results are emerging fast—and the pace of #innovation is only picking up. At Recursion, we’re also applying #geneediting tools like CRISPR beyond therapeutics—using the technology as a tool to better understand #biology at scale. By systematically “knocking out” thousands of individual genes and measuring how those changes affect cell behavior, we’re generating large, structured datasets that feed directly into #AI models. This is helping us uncover new biological relationships and power #drugdiscovery in ways that were previously unimaginable. What ties all of this together is a commitment to applying game-changing #innovation in service of real, urgent human needs. It signals a much-needed mindset shift in #healthcare and #biopharma: to move faster, think bigger, and tackle challenges once considered out of reach—and to truly deliver on the promise of #precisionmedicine. And we’re seeing this ambition in many other areas as well – just last week, for example, GRAIL announced more promising than ever performance stats for its #Galleri blood test for the early detection of 50+ types of #cancer. There’s still work ahead to ensure breakthroughs translate into broad, equitable impact. But this moment – this momentum – is worth pausing to recognize. We’re no longer just imagining a future where science works smarter and faster for patients. We’re building it.

𝐀𝐈 𝐢𝐬 𝐜𝐨𝐥𝐥𝐚𝐩𝐬𝐢𝐧𝐠 𝐭𝐢𝐦𝐞𝐥𝐢𝐧𝐞𝐬 𝐢𝐧 𝐦𝐞𝐝𝐢𝐜𝐢𝐧𝐞, 𝐚𝐧𝐝 𝐫𝐞𝐰𝐫𝐢𝐭𝐢𝐧𝐠 𝐭𝐡𝐞 𝐞𝐜𝐨𝐧𝐨𝐦𝐢𝐜𝐬 𝐨𝐟 𝐜𝐮𝐫𝐞𝐬 A few years ago, predicting a protein’s structure took months or even years. Then came AlphaFold, DeepMind’s Nobel-winning breakthrough, unlocking the ability to understand proteins and disease mechanisms at scale and speed. This led to Alphabet’s spin-off, 𝐈𝐬𝐨𝐦𝐨𝐫𝐩𝐡𝐢𝐜 𝐋𝐚𝐛𝐬, now using AI to design therapies with $600M in funding and its first human trials underway for cancer and immune disorders. ▫️ The speed of progress: Every six months, AI advances like a full human year. What once took decades now unfolds in quarters. ▫️ The cost collapse: AI is driving the cost of drug discovery and testing so low that researchers can now explore thousands of drug candidates and disease targets at once, including treatments that would have been dismissed as too niche or unprofitable just a few years ago. ▫️ The scale of exploration: AI has already helped identify or repurpose over 3,000 drugs currently in clinical trials. We’re already seeing the results. Northwestern researchers, for example, used AI-enhanced screening to repurpose 𝐩𝐢𝐩𝐞𝐫𝐚𝐜𝐢𝐥𝐥𝐢𝐧, a decades-old FDA-approved antibiotic, for Lyme disease. In mouse studies, it cured infection at one-hundredth the dose of standard treatment without harming gut microbiota. That breakthrough emerged in days, not years, at a fraction of traditional costs. 🔺 𝐖𝐞 𝐚𝐫𝐞 𝐰𝐢𝐭𝐧𝐞𝐬𝐬𝐢𝐧𝐠 𝐚 𝐟𝐮𝐧𝐝𝐚𝐦𝐞𝐧𝐭𝐚𝐥 𝐬𝐡𝐢𝐟𝐭. AI isn’t just speeding up medicine, it’s enabling exploration and validation at scales and price points previously unthinkable. And every six months, the landscape tilts even further. This is what leaders need to see: the weight of the opportunity, and the urgency to align their thinking to the pace of this change. #AI #Healthcare #DrugDiscovery #GenAI #FutureOfWork #mindsetchange Forbes Technology Council Gartner Peer Experiences InsightJam.com PEX Network Theia Institute VOCAL Council IgniteGTM IA FORUM 𝗡𝗼𝘁𝗶𝗰𝗲: The views within any of my posts, or newsletters are not those of my employer or the employers of any contributing experts. 𝗟𝗶𝗸𝗲 👍 this? feel free to reshare, repost, and join the conversation!

As I work at the intersection of healthcare design and technology, certain patterns are emerging that suggest profound changes in how we'll deliver care. Here are five shifts I believe we'll see: First, AI won't just assist with decisions - it will transform how we make them. Providers will move from reviewing individual data points to understanding complex patterns across time and populations. Imagine specialists across disciplines having the time and insight to truly collaborate on complex cases: an oncologist and cardiologist deeply discussing treatment implications, supported by AI-surfaced patterns from thousands of similar cases. These rich, cross-disciplinary conversations will lead to more nuanced, coordinated care decisions. Second, as AI manages standard protocols and data analysis, provider time will shift dramatically. Instead of spending hours on documentation and routine analysis, clinicians will focus on the nuanced work of understanding patient contexts and goals. Conversations will deepen. Treatment plans will become more personalized. The human elements of care - understanding individual values, circumstances, and preferences - will take center stage. Third, care delivery will become more proactive and precise. AI will help identify subtle signs of health changes before they become critical, enabling earlier interventions. Care teams will shift from reactive response to proactive planning. Preventive care will become more targeted and effective, based on sophisticated understanding of individual risk factors and social determinants of health. Fourth, the technology itself will continuously evolve based on real-world outcomes. Treatment protocols will adapt in real time based on emerging evidence and individual patient responses. Care pathways will become more dynamic and personalized, learning from each patient interaction to improve future care delivery. Finally, these changes will reshape the physical and operational structure of healthcare. We'll need different kinds of spaces - ones designed for deeper conversations and collaborative decision-making. Workflow patterns will change as routine tasks become automated. Team structures will evolve to support more integrated, proactive care delivery. The future of healthcare delivery will require fundamentally rethinking how we provide care when technology can handle routine tasks and help us see patterns we might otherwise miss. This transformation offers an unprecedented opportunity to make healthcare more human, more proactive, and more effective.