Connecting Patients to Therapies and Devices Faster with AI
Read the Harvard Business Review Analytic Services report
Implementing AI in Commercial Life Sciences
We have sponsored this report to examine how life sciences organizations can develop trusted AI strategies to reimagine their operations while promoting patient-centricity and connectivity across R&D and healthcare. Through interviews with analysts, academics, and other healthcare experts, this paper outlines the challenges and opportunities that healthcare companies face moving into this next era of healthcare AI. Alongside this research, the insights offered in this paper can help life sciences organizations build an AI strategy that establishes a well-governed data ecosystem that provides a contextualized foundation to drive lasting impact to customer experiences and costs through intelligence and automation.
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AI & Global Labeling: How Next-Gen Tools Are Streamlining Structured Component Authoring Effectively and Compliantly
Outside of the physical drug product itself, global labeling plays the most fundamental role in helping pharmaceutical companies deliver safe and effective therapies to the population. But the process behind global labeling—the authoring, editing, collaborating, translating, and publishing of drug labels—is both incredibly complex and time-consuming. This guide explores how AI-powered tools are helping teams simplify and accelerate their in-house authoring workflows, without sacrificing compliance. It also explains how, by using such tools, companies can transform not just the way they work but also the entire “last mile” of the drug development lifecycle.
AI & Global Labeling: How Next-Gen Tools Are Streamlining Structured Component Authoring Effectively and Compliantly
Outside of the physical drug product itself, global labeling plays the most fundamental role in helping pharmaceutical companies deliver safe and effective therapies to the population. But the process behind global labeling—the authoring, editing, collaborating, translating, and publishing of drug labels—is both incredibly complex and time-consuming. This guide explores how AI-powered tools are helping teams simplify and accelerate their in-house authoring workflows, without sacrificing compliance. It also explains how, by using such tools, companies can transform not just the way they work but also the entire “last mile” of the drug development lifecycle.
