Insights for Connected, AI-Actionable Life Sciences
Explore the latest ideas shaping life sciences, with expert perspectives on agentic AI, operating system, architecture, contextualized data, and connected operations.
The AI-Ready Lab: Eliminating App-Hopping in Scientific Workflows
Agentic AI is already cutting app-hopping across HR, IT, and procurement, yet R&D and CMC teams still juggle disconnected LIMS, ELN, and MES systems. In this POV, L7 Founder and CEO Vasu Rangadass, Ph.D., explains how L7|ESP, the agentic operating system for precision science, unifies lab data to make it AI-actionable.
Blog Posts.
The AI-Ready Lab: Eliminating App-Hopping in Scientific Workflows
Agentic AI is already cutting app-hopping across HR, IT, and procurement, yet R&D and CMC teams still juggle disconnected LIMS, ELN, and MES systems. In this POV, L7 Founder and CEO Vasu Rangadass, Ph.D., explains how L7|ESP, the agentic operating system for precision science, unifies lab data to make it AI-actionable.
From Demo to Daily Practice: Four Lessons on Scaling AI in Drug Discovery
Vasu Rangadass, Ph.D., reflects on Christian Diehl's conversation on McKinsey's Eureka! podcast and draws out four lessons for scaling AI in drug discovery: embed AI in daily scientific workflows, move from AI-ready to AI-actionable data, govern agents like associates, and extend lab-in-the-loop into CMC-in-the-Loop. He connects each lesson to L7|ESP®, the agentic operating system for…
Beyond Lab-in-the-Loop: Orchestrating CMC-in-the-Loop
AI is accelerating drug discovery, but CMC has become the constraint that decides how fast candidates reach patients, and it now spans a network of external partners. Vasu Rangadass, CEO of L7 Informatics, explains how CMC-in-the-Loop coordinates that work across internal labs and CDMOs on one governed data model, so process knowledge and quality data…
The Clinical Trial Paradox & The Pragmatic Middle Path: Unifying Biological Boldness with Enterprise IT Risk Management
Vasu Rangadass, President and CEO of L7 Informatics, and Ray Veeraraghavan, VP of Science and AI, examine the clinical trial paradox: pharma takes bold biological risks while IT often defaults to familiar, conventional systems. That divide stalls most life science AI initiatives. Their pragmatic middle path adds orchestration over existing systems instead of replacing them,…
AI Governance Starts Before Agents Can Act
Agentic AI is entering regulated pharma workflows faster than the foundations beneath it can support. Vasu Rangadass, CEO of L7 Informatics, explores why governance depends on context, lineage, and traceability existing before agents act, and how a unified operational foundation turns governance into a natural outcome of execution.
Orchestrating the 98%: The Hidden Architecture of Trustworthy AI
A landmark analysis of a leading AI agent found that only 1.6 percent was the model. The rest was operational infrastructure. Vasu Rangadass explains why, in regulated science, that operational harness is where trust, economics, and durable advantage are built, and why the model was the least of the engineering.
The Agentic Pivot: Why the “Safe Software Choice” Became the Risky One
For two decades, life sciences teams bought point solutions to fix local problems, quietly deepening the fragmentation that now stalls nearly every AI initiative. Vasu Rangadass argues for the agentic pivot: the shift from buying tools to running an operating system for science that takes operations from AI-ready to AI-actionable.
Why Life Sciences Manufacturing AI Keeps Failing at the Finish Line
Between 70% and 90% of AI initiatives in manufacturing never reach production. The reasons are rarely about the AI itself. L7 Informatics' Kevin McMahon identifies the three failure modes consistently killing life sciences manufacturing AI pilots: broken data architecture, missing organizational alignment, and absent change management. Drawing on Gartner's March 2026 MES Market Guide, he…
Agentic AI in Life Sciences: What’s Real, What’s Hype, and What It Actually Takes
Agentic AI is maturing fast, but the honest picture is earlier than most vendors admit. L7 Informatics experts James Ryan, Sean Hinds, and Chris Burke break down what AI agents genuinely do well in pharma and life sciences today, which protocols are worth adopting now, and why your data and workflow substrate matters more than…
Cell Therapy Cannot Scale Without Digital Continuity Across R&D, CMC, and Manufacturing
Cell therapy programs don't fail because of bad science; they fail because context doesn't travel. This article explores how ontologies, KASA-structured process modeling, and a unified execution layer create true digital continuity across R&D, CMC, and manufacturing, turning your CMC backbone into a living, always-available record.
Modernization was the First Chapter, Digital Differentiation is the Next One
Life sciences organizations have invested heavily in digital transformation, but modernization alone does not create a competitive advantage. Vasu Rangadass, Ph.D., President and CEO of L7 Informatics, explains how digital differentiation can only emerge from digital unified platforms that orchestrate scientific workflows, capture context at execution, enable AI inside governed processes, and deliver end-to-end traceability…
From AI-Ready to AI-Actionable: Why Life Sciences Need an Execution Layer
Life sciences organizations have invested in AI-ready data infrastructure. The next step is becoming AI-actionable: enabling AI to participate inside governed workflows across lab and manufacturing. This requires an execution layer that provides shared ontology, manages workflow state, and implements context graphs so recommendations move through compliant paths with traceability.