Beghou

As anyone who works in CGT or rare disease knows, longer selling cycles are a reality. Logistical hurdles abound. By ensuring logistics are “ticked and tied” and that commercial infrastructure is in place “right out of the gate,” companies can design for that complexity, suggests Lori Nemyier 🎙️ Listen and read the key takeaways here: https://hubs.ly/Q04hgmc10 #TheSpacePodcast #LifeSciences #Biopharma #CellAndGeneTherapy #RareDisease #Biotech #CommercialOperations

Tools built to support field integration may be the very things slowing it down.  Pharma organizations have invested heavily in AI, omnichannel and analytics infrastructure. Yet execution can still feel surprisingly disconnected across teams and functions.  At the Reuters Events Pharma USA 2026 panel "From Silos to Synergy," moderated by Marcos Mendell, three design issues stood out:  ✔ Systems built for organizational visibility don't always support field decisions.   ✔ Omnichannel and field engagement are often treated as separate endeavors.   ✔ Compliance has more impact when involved earlier in strategy development.  As commercialization timelines compress and the pressure on field teams grows, these conversations are becoming more urgent.  👉 Swipe through to explore the design issues and what the reframe looks like.  #MedicalAffairs #PharmaCommercialization #Omnichannel #FieldIntegration

Rare disease commercialization often starts with the question: Where are the patients? But a more foundational question is what infrastructure we need to reliably see patients earlier, understand their journey, and enable field teams to act. At the Veeva Commercial Summit 2026 in Boston, Beghou Partner Kevin Frymire will share insights and practical design principles for evaluating rare disease data, contrasting common pitfalls with the pillars to drive successful commercialization.  ➡️ Session: Building a Patient Data Infrastructure for Rare Disease  📅 May 19 – 20 | Boston    If you are attending, don’t miss out.    #VeevaCommercialSummit #Beghou #RareDisease 

Do you feel like you’ve hit a wall with your data stack? Your data foundation appears solid, but the story it’s telling doesn’t fully reflect market reality: missing patients, plateaued targeting, incomplete account prioritization... If this sounds like your situation, join our webinar on June 10, when Adrienne Lovink and Vishal Singal will share a practical framework to identify what’s missing from your data stack and ensure that your investments deliver the right outcomes. 📅 June 10 at 11 AM ET 👉 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐧𝐨𝐰: https://hubs.ly/Q04g-2rS0 On the agenda: ➡️ 𝐃𝐢𝐚𝐠𝐧𝐨𝐬𝐢𝐧𝐠 𝐭𝐡𝐞 𝐫𝐞𝐚𝐥 𝐠𝐚𝐩:How to distinguish between data limitations, analytical limitations, and use case issues ➡️ 𝐈𝐝𝐞𝐧𝐭𝐢𝐟𝐲𝐢𝐧𝐠 𝐲𝐨𝐮𝐫 𝐝𝐚𝐭𝐚 𝐩𝐫𝐨𝐛𝐥𝐞𝐦: Knowing when you need more coverage (e.g., additional claim sources) vs a different data type ➡️ 𝐌𝐚𝐤𝐢𝐧𝐠 𝐭𝐡𝐞 𝐫𝐢𝐠𝐡𝐭 𝐝𝐚𝐭𝐚 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧𝐬: How to prioritize gaps and narrow the list to investments that will move the needle ➡️ 𝐑𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐬𝐜𝐞𝐧𝐚𝐫𝐢𝐨𝐬: Q&A addressing common situations and examples Can't make it live? You'll still get the recording and slides if you register. #BeghouWebinar #Data #LifeScience #Pharma

𝗙𝗮𝘀𝘁 𝟱: From Health AI to #Ozempic in kiosks, Amazon is bookending the healthcare journey. Link to the full brief at Beghou.com is in the comments, but here are the highlights... 𝟭. 𝗪𝗵𝗮𝘁’𝘀 𝗵𝗮𝗽𝗽𝗲𝗻𝗶𝗻𝗴: Amazon is expanding its Health AI agent and access to #GLP1 treatments, embedding both within its broader, app-based healthcare experience.  • In March, Amazon expanded its Health AI agent beyond the One Medical app, embedding it directly into Amazon.com and its mobile app, marking the first time the tool has been available at scale to general consumers.   • Amazon Pharmacy said last Thursday that it will dispense the Ozempic pill for type 2 diabetes at its One Medical kiosks, which Amazon Pharmacy launched at select One Medical locations in December, and enable same-day delivery for $149 monthly, eliminating a separate pharmacy trip.   • Amazon also launched a One Medical GLP-1 management program offering oral GLP-1s for weight-loss, like Eli Lilly and Company’s #Foundayo and Novo Nordisk’s #Wegovy.  𝟮. 𝗪𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 𝗯𝗶𝗴 𝗱𝗲𝗮𝗹: Amazon is positioning itself as both the front door and fulfillment engine for healthcare.   • Health AI — now sitting inside the world’s largest online marketplace — beckons patients to start their health journeys in the same place they shop.   • With roughly 180 million Prime members in the U.S., Amazon already has a built-in audience at massive scale.   • Primary care (One Medical), pharmacy, retail distribution, and home delivery complete the consumer experience.  𝟯. 𝗪𝗵𝗮𝘁’𝘀 𝗮𝘁 𝘀𝘁𝗮𝗸𝗲: An entirely different healthcare experience.   • Amazon is introducing a consumer-centric alternative: on-demand, digitally coordinated, and integrated end to end.  𝟰. 𝗪𝗵𝗮𝘁’𝘀 𝗶𝘁 𝗺𝗲𝗮𝗻 𝗳𝗼𝗿 𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗶𝗮𝗹 𝗲𝘅𝗲𝗰𝘀: If patients increasingly engage with healthcare through platforms like Amazon, commercialization strategies may need to move upstream in the patient journey, observes Rishi Raj Manchanda, associate partner at Beghou.   • “Patients may form awareness, questions, and provider preferences inside platforms like Amazon before they ever speak with an HCP,” Manchanda explains.   • In turn, patient identification and targeting may shift away from geography and HCP affiliation, as digital platforms decouple care from local provider networks.  𝟱. 𝗪𝗵𝗮𝘁’𝘀 𝗻𝗲𝘅𝘁: Overall, this suggests the need to shift from influencing decisions at the point of care to engaging patients earlier, in the platforms where journeys begin.   • Manchanda counsels brands to optimize content for AI-driven search (i.e., through generative engine optimization, or GEO) and platform discovery: “Brand education needs to be compliant, clear, and findable in AI/search-led healthcare experiences, not just on brand websites or traditional media,” he stresses.

I was at #PMSA2026 with the Beghou team. This year opened with a question that framed the entire conversation: why do so many organizations that have invested in AI still find themselves stuck, cycling through pilots, unable to close the gap between what the technology can do and what the business needs? The pattern in the answer was organizational factors, and it surfaced across keynotes, breakouts, and the conversations in between. Here are my takeaways: 1. AI is fundamentally an operating model problem, not an IT implementation one. Enterprises that treat AI as a technology deployment tend to fail to scale. The ones that win excel at redesigning talent, processes, and decision-making culture alongside the technology, turning isolated pilots into repeatable, production-grade capabilities. 2. The deeper unlock is cultural. Real progress requires an enterprise-wide embrace of continuous change, where every function has internalized that the way work gets done is being permanently restructured. 3. Data foundations are as strategic as the model themselves. Semantic layers, knowledge graphs, and governed data platforms are what separate organizations that can scale from those stuck in perpetual pilots. Even the best models take organizations nowhere when run on fragmented, ungoverned data. 4. Agentic AI is the new center of gravity. The real breakthrough is collaborative agents: a targeting agent feeding an omnichannel orchestration agent, which informs a field coaching agent, all aligned to a shared commercial objective. A fundamentally different paradigm than a chatbot. 5. The language has shifted from "pilots" to "scale." The question is no longer whether to adopt, it's how fast and how broadly. I look at scale as a stress test that exposes governance gaps, data fragmentation, and change management deficits. 6. The "hallucination problem" has matured into a "governance problem." The field has moved toward actively managing uncertainty through confidence scoring, validation, compliance guardrails, and human-in-the-loop design. In pharma, this is what makes AI commercially deployable. 7. The destination is always-on, autonomous intelligence. The north star is proactive, governed systems that surface the right insight to the right person at the right moment, without being asked. The organizations that will define commercial pharma over the next five years could be the ones that ask the right questions about what AI requires from an enterprise. That means governed data that AI can reason over with confidence, talent repositioned to work alongside intelligent systems, and processes designed for autonomy. #AI #Pharma #CommercialExcellence #AIStrategy

In our survey of biopharma marketers, an overwhelming majority said they define omnichannel success by engagement and behavior as opposed to outcomes. In this series of videos – part of our “Commercialization that Works” series of research activities and content – Beghou Associate Partner Rishi Raj Manchanda shares some of the building blocks behind impactful omnichannel, like knowing who your customer is and where they are in their journey. Get your copy of the Commercialization That Works report here: https://hubs.ly/Q04gtcZT0 #OmnichannelStrategy #LifeSciences #Biopharma #GoToMarket

Beghou’s CTO, Dan Cardinal was recently featured on the Modern CTO podcast with Joel Beasley. The conversation explored how Dan is thinking about AI inside Beghou’s engineering organization and how those lessons inform the way Beghou delivers value to clients faster. Dan and Joel Beasley | Modern CTO talked about:   • How to prioritize the right kinds of work for AI to support   • Why a framework migration made sense as an early test case with Blitzy   • What it looks like for AI to move a project most of the way forward, and which decisions still need to stay with the engineering team   • How AI is shaping Dan’s thinking around engineering capacity, team focus, and the pace of product development   • The leadership advice that has stayed with him - you are in the seat for a reason, so make the decision and lead Check out the full conversation here: https://hubs.ly/Q04gh4dz0 #AIAdoption #CTOInsights #TechLeadership #ModernCTO

Looking forward to the Veeva Commercial Summit! Reach out if you will be there.