Blog
How Emerging AI Capabilities are Reshaping Life Sciences
Raja Shankar, Managing Principal and Head of AI and Technology Consulting, IQVIA
Oct 23, 2025

“Everything we do today as a pharma company or as a service provider to a pharma company, we can do better with AI across the lifecycle.”

The life sciences industry has entered a new era, where artificial intelligence has moved from the margins to the mainstream and expanded from traditional machine learning to autonomous AI agents. These technologies are reshaping the entire lifecycle of life sciences and healthcare, from redefining research and development to streamlining clinical trial design and reshaping commercialization strategies.


The growing impact of AI in life sciences and healthcare

A recent cross-industry survey conducted by IDC, which includes life sciences organizations, provides insight into the impact of AI adoption. In the report, 73% of industry participants surveyed reported “spectacular” or “significant” improvements in core operational processes from using vendor applications embedded with AI.1

In the same survey, respondents across industries noted the top three most important business benefits from AI: faster innovation, increased operational efficiency, and increased profits. These results signal a fundamental shift in how life sciences companies bring therapies to market. In automating routine processes and streamlining workflows, AI also drives faster time to market, fosters higher success rates, and allows for a heightened focus on higher-value strategic work.

By bringing AI into research, development and commercialization workflows, organizations can accelerate the pace and stay competitive. Perspectives are able to shift to be less reactive and more proactive. Using advanced models, organizations are better equipped to anticipate needs, surface deeper insights faster, and integrate intelligence directly into workflows. As technology continues to evolve, we can expect even broader and deeper impacts.


How AI is reshaping processes from clinical to commercial

AI adoption drives measurable improvements at every stage across the asset lifecycle, acting as both a research partner and an operational companion. AI delivers value in four key ways: It increases the likelihood of success, accelerates speed to market, improves quality, and enhances stakeholder experiences.

  • In clinical development, AI increases the likelihood of success by helping drug developers choose the right indications, trial designs, and trial strategies for each asset. This can derisk R&D investment decisions by enabling life science companies to develop the right asset for the right indications in the right order for the right patients.
  • In trial execution, AI compresses timelines and processes, improving the experience of investigators, sites and patients while strengthening overall trial quality.
  • In real-world evidence generation, AI quickly analyzes data from sources like electronic health records and scientific literature. This helps stakeholders understand how treatments work in everyday settings, supports faster regulatory submissions, and improves post-market monitoring.
  • In commercialization, AI is transforming engagement strategies. AI can predict market shifts, identify where patients and providers are in their journeys, and enable organizations to deliver the right message to the right stakeholder at the right time. This moves organizations toward proactive, precision-driven engagement that ultimately strengthens business outcomes.
The real value of AI comes when you connect intelligence across silos — clinical, regulatory and commercial — so insights flow seamlessly.
Raja Shankar, Vice President, Machine Learning, IQVIA
Impact on patients

AI is helping to improve the experience for patients at every stage of their journey. It can quickly match individuals to clinical trials that fit their needs, making it easier to find appropriate opportunities. With automated systems guiding patients through the consent process, enrollment becomes simpler and easier. Patients are no longer faced with long and complex forms. By making these documents easier to understand and providing interactive support, AI improves clarity and engagement, reduces patient confusion, and eliminates administrative delays.

Once patients are enrolled, AI enables better trial designs that select the right patients, ensuring the optimal benefit-risk balance. Early protocol assessments driven by AI can minimize patient burden (i.e., eliminating unnecessary site visits or biopsies). During clinical trials, AI-driven digital tools provide timely information, reminders and support, helping inform and retain patients. These improvements reduce administrative burdens, speed up access to new therapies, and ultimately create a smoother, more supportive experience for both patients and their caregivers.

Following successful trials, AI shortens the path to market for effective therapies. Commercialization in life sciences is all about timing, creation and impact. Current AI capabilities make the final data analysis, reporting and submission process easier, more efficient, and higher quality. Al supports launching a drug at the right time, creating positive patient impacts and bringing precision to brand messaging. These factors help transform go-to-market strategies. AI ensures that every launch, every campaign, and every engagement across life sciences stakeholders are timely and impactful.


Successful AI: The power of connected, high-quality inputs

Strategic initiatives, such as our work with NVIDIA, benefit our customers by bringing advanced infrastructure and additional technical expertise to IQVIA’s agentic AI solutions.

At IQVIA, we deliver this level of connectivity through our proprietary data assets, advanced technologies, and deep domain expertise. IQVIA Connected Intelligence brings together information from multiple sources, empowering our AI to generate informed, actionable insights and accelerate the journey from molecule to market. This foundation supports our Healthcare-grade AI®, which is designed to be transparent, explainable and governed by rigorous standards, ensuring trust and reliability for our clients.

Strategic partnerships, such as our collaboration with NVIDIA, benefit our customers by bringing advanced infrastructure and additional technical expertise to IQVIA’s agentic AI solutions. For organizations, this means expedited processes, improved quality, and faster access to powerful, scalable AI tools that are continually refined to meet evolving industry needs. By leveraging these partnerships, our customers can accelerate innovation, improve decision-making and achieve better outcomes for patients and stakeholders.


AI’s end-to-end impact

By improving success rates, reducing timelines, enhancing quality, and delivering better stakeholder experiences, AI is transforming how therapies are developed and delivered from start to finish. At IQVIA, we are working at the cutting edge of these advanced technologies. Together with our clients, we are fundamentally reimagining paths to innovation, ensuring treatments reach the right patients faster, with greater confidence and lasting impact.

To explore how AI solutions can benefit your organization, visit iqvia.com/AI.


References:

IDC, Worldwide GenAI Industry Use Case Early Adoption Trends, 2025: Life Sciences, doc # US53317424, April 2025

Meet the expert

Raja Shankar

VP, Machine Learning, Research and Development Solutions, IQVIA
Raja is focused on transforming life sciences with Applied AI. As the VP for Machine Learning, Raja is determined to change healthcare with the power of AI. He believes that imagination is the biggest barrier and motivates his team to create new narratives that fully leverage AI's potential to reshape the industry from R&D through to commercialization. Raja brings together a diverse set of technical and strategic capabilities, including Machine Learning, Deep Learning, Generative AI, Product Development, Life Sciences Expertise and Business Consulting Skills. His team combines data science, engineering, domain expertise and consulting skills to drive impactful change by applying AI to life sciences and healthcare decisions. Currently, his focus is on leveraging data and AI to help transform clinical development. Raja is a trusted advisor to global life sciences companies, public sector clients and international organizations.

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