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Agentic AI and Data Accessibility: A Strategic Shift for Life Sciences Across the Product Lifecycle
IQVIA Global Market Insights Agent
Kapil Chaddha, Director, New Product Development, IQVIA
Abhishek Jaiswal, Director, Offering Management, IQVIA MIDAS and Agentic AI
Oct 02, 2025

The life science sector is facing an ever-increasingly complex operating environment. Accelerated drug development timelines, diversified treatment modalities, and an array of commercial analytics are converging to create a volatile, interdependent, and data-intensive landscape.

Navigating this environment requires more than siloed analytics or retrospective reporting. It demands integrated, real-time decision-making to keep pace with the business and scientific imperatives of a modern pharmaceutical enterprise. An innovative new solution has emerged in the form of agentic AI capabilities, which represent a structural shift in how data is accessed, interpreted and applied to drive business strategy.

A new era of strategic intelligence with agentic AI

Agentic AI is a new generation of artificial intelligence (AI) which uses advanced reasoning, iterative planning, and performing actions to solve complex, multi-step business problems. Unlike traditional AI systems that focus on narrow prediction tasks or static automation, agentic AI is designed to interact, reason and guide users across a variety of complex business contexts.

Built on top of comprehensive global market data, agentic AI offers an intuitive language interface, enabling users to pose questions as they would to a market expert or consultant. Behind the scenes, it can perform multivariate analyses across structured and unstructured datasets—identifying trends, correlations and recommendations that would otherwise require days of manual analysis and interdepartmental collaboration.

This capability goes well beyond traditional predictive modeling, which often requires statistical expertise, rigid workflows and narrowly defined outputs. By contrast, agentic AI supports contextual decision-making. It understands what a given dataset means in a given strategic or clinical context. Rather than simply producing data reports, it can generate insights that are both tailored and explainable. Agentic AI acts as a reasoning partner across timeframes, geographies, patient populations and product attributes—enabling users to iterate strategic ideas through natural-language interaction and providing nuanced answers to complex questions.

A defining strength of agentic AI is its ability to continuously learn and adapt. As new data becomes available — whether sales trends, promotional feedback, HCP sentiment, or market forecasts — the agent refines its reasoning model in real time. This dynamic learning capability enables forward-looking scenario planning and ensures that insights remain relevant, timely, and aligned with evolving market conditions.

Impact spanning the product lifecycle

Rather than being locked into fixed analytic outputs, organizations now have access to a flexible intelligence agent that evolves alongside their strategic questions throughout the product lifecycle. Agentic AI thereby delivers fast, relevant answers at every stage of product development and commercialization.

    ● In early development, agentic AI can help assess therapeutic landscape dynamics and market potential. By analyzing historical analogues, competitive activity and HCP sentiment data, organizations can confidently shape their pipeline, prioritize assets and understand where unmet need overlaps with commercial opportunity.

    ● During pre-launch, the agent can help bridge scientific potential with commercial readiness. brand and medical teams can evaluate differentiated value propositions, assess market adoption curves and benchmark against expert pharma market forecasts

    ● At launch, agentic AI can track key performance indicators to continuously evaluate patient market share, promotional effectiveness, physician engagement and emerging risks. It can learn from market analogues and link to omnichannel strategy.

    ● Post-launch, the agent can enable lifecycle management and competitive vigilance. It can track erosion patterns after loss of exclusivity and monitor new entrant activity. It can also help guide portfolio expansion by identifying adjacent indications or formulations where clinical and market conditions are favorable. These functions are powered by the integration of real-time datasets and the agents’ ability to continuously refine its analysis with new evidence

The foundation of reliable, cross-functional intelligence

The effectiveness of agentic AI depends on the quality and breadth of the data it draws from. To generate reliable, real-world insights, the underlying datasets must meet rigorous standards of clinical accuracy, regulatory compliance, and relevance to life sciences decision-making. Without this foundation, even the most advanced agent cannot deliver trustworthy or actionable intelligence.

Just as important is how that data is accessed and applied across teams. One of the most transformative impacts of agentic AI is its ability to break down silos and foster true cross-functional collaboration. In traditional models, commercial, medical affairs, and R&D teams often work from separate datasets — leading to inconsistent interpretations, duplicated efforts, and strategic misalignment.

Agentic AI provides a shared intelligence layer through a natural-language interface that adapts to each user’s role and context. Whether shaping clinical strategy, refining a brand plan, or evaluating market access, the agent ensures consistent logic, unified data interpretation, and faster alignment across teams.

Transformational advances through partnership

A strategic collaboration between IQVIA and NVIDIA, announced in early 2025, is poised to help realize the potential of agentic AI in life sciences. This partnership is accelerating the deployment of IQVIA Healthcare-grade AI® — capabilities purpose-built for the complex demands of healthcare analytics. It combines gold-standard commercial, clinical, and regulatory data with IQVIA’s deep expertise in life sciences, advanced analytics, and AI. NVIDIA’s powerful AI infrastructure includes fine-tuned models , inference microservices and optimized blueprints for computational acceleration and reasoning, while also supporting continuous learning and performance improvement through its data flywheel.

Together, these strengths enable robust performance, compliance with healthcare data governance standards, and the delivery of fast, explainable results across global deployments. The collaboration ensures that as datasets expand and user needs diversify, agentic AI will remain a responsive, trusted partner for decision-making at scale to accelerate the delivery of innovative therapies to patients.

Introducing IQVIA Global Market Insights Agent

Agentic AI is engineered to evolve, continuously learning from new data and adapting to the growing complexity of life sciences. It transforms how organizations plan, decide, and execute strategy by enabling a faster, more connected, and more agile operating model. IQVIA is uniquely positioned to support this transformation, with an unmatched portfolio of healthcare data assets, deep domain expertise, and advanced agentic AI infrastructure.

Introducing IQVIA Global Market Insights (GMI) Agent — a new solution that provides a unified, near real-time view of the global market landscape. It leverages agentic AI to synthesize data from IQVIA’s industry-leading syndicated sources, helping life sciences teams answer multi-dimensional questions and solve complex market intelligence challenges. GMI Agent supports smarter decisions from early development through commercialization.

Your Next Step in Market Intelligence Starts Here
Whether you’re just beginning your AI journey or ready to scale enterprise-level intelligence, IQVIA can help guide your next step. Contact us today to discuss how IQVIA can help you leverage agentic AI to empower your teams, unify your data and accelerate smarter, cross-functional decision-making.

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