Narrativa

💡 Which AI ecosystem is best for pharma? That might be the wrong question. Claude, Gemini and GPT are all making their way into pharma, with different partnerships, use cases and reported results. But there’s no clear single winner. For life sciences companies, the bigger questions are: Does it work with our documents? Can we switch models without rebuilding our workflows? And where do validation and expert review fit? Swipe through for a look at how the three ecosystems are being used across pharma. 👇 And don't forget to follow us for more insights on AI adoption, innovation and the future of Life Sciences.

❓ Should AI make this decision? MIT suggests asking two questions first: 1️⃣ How ambiguous is it? 2️⃣ How risky is it if AI gets it wrong? Low risk + low ambiguity → strong candidate for automation. High risk + high ambiguity → humans should lead. A simple framework for a question that’s becoming increasingly important as AI agents take on more responsibility. https://lnkd.in/ezxBK6P9

🩸 Real experiences. Real-world AI. Ashley Yocum from Blood Cancer United opens our AI at Work series, sharing her experience working with Narrativa and how AI is supporting their work. Hear it directly from Ashley. 👇 #AIatWork #AgenticAI #LifeSciences #ClinicalResearch

📝 Medical writers rank #1 among the roles sponsors and CROs expect AI to significantly reshape over the next 1–2 years. We’re already seeing how agentic AI can change the way clinical and regulatory teams work, not by simply automating individual tasks, but by rethinking entire workflows. The shift is already underway. 👇 https://lnkd.in/esuCXZQv

🧬 Patient data doesn’t become regulatory-ready on its own. Behind every clinical dataset are multiple steps involving data processing, standardization, statistical programming, anonymization and validation. Agentic AI can help connect these activities into controlled workflows, while maintaining the traceability and human oversight required in regulated environments. In our latest article, we explore how agentic AI can support the journey from patient data to regulatory-ready outputs. 👉 Read the full article: https://lnkd.in/ewrugaRY #AgenticAI #ClinicalTrials #ClinicalData #LifeSciences #Pharma

❌ More than 80% of employees involved in AI innovation eventually disengaged in one of the organizations studied by the Massachusetts Institute of Technology. The problem wasn’t access to AI. It was the lack of ongoing support for the people testing, refining and turning experiments into real solutions. A good reminder: scaling AI is as much an organizational challenge as a technology one. https://lnkd.in/ew7xiRGT

📊 Clinical data and biostatistics are leading AI adoption. But are the results keeping up? 57% of life sciences organizations already use AI capabilities in data science and biostatistics, making it the most AI-active of nine functions surveyed. The use cases are expanding, from coding assistants to data quality checks and clinical trial optimization. But there’s still a gap between adoption and robust evidence of impact. So what should teams be looking at before scaling AI across clinical data workflows? Swipe through for the data, the use cases, and the questions that matter. 👇

👀 Another look at life as an intern at Narrativa! This time, Lillian Novotny takes us behind the scenes of her internship, sharing some of the projects she worked on and the lessons she picked up along the way. Having interns on the team also means new ideas, different perspectives and plenty of opportunities to learn from each other. Thanks for being part of Narrativa, Lillian! 💙 #Internship #TeamNarrativa #AI

🔍 Clinical trials don’t only lose time between milestones. They also lose it between teams. Biostatistics, data management, medical writing, clinical operations and regulatory affairs all contribute to the same trial. But information still moves between them through different systems, document handoffs, clarifications and repeated review cycles. That creates internal white space: the time and effort lost between teams before information can actually move forward. Agentic AI can help close those gaps by connecting data, documentation and workflows, reducing repetitive work and making collaboration more efficient. In this article, we explore where this white space comes from and how clinical teams can reduce it. 👇 Take a look at the full article below.

➡️ AI could add between 0.2 and 1.3 percentage points to annual labour productivity growth across G7 economies over the next decade. But unlocking that potential isn’t just about faster innovation. Trust, reliability and security matter too. Innovation and trust shouldn’t be competing priorities. AI needs both. https://lnkd.in/gjD5WSTf