How agentic AI is revolutionizing life sciences

Traditional AI systems create models designed to analyze data sets – from a large number of databases across a digital network – to generate predictions for human operatives to consider and act upon. Recent evolution in AI technology has resulted in the creation of AI agents, able not only to generate recommendations but to act on them autonomously, without human intervention. Agentic AI possesses multiple agents but harnesses them in a unique way that allows them to perform even more complex analytical tasks. Where multi-agent AI models use an array of agents to generate predictions, agentic AI employs agents to act autonomously.

“Endowed with greater context understanding than the alternative, agentic AI can analyze complex situations, weigh potential outcomes, and make autonomous decisions or recommendations based on their programmed objectives and learned knowledge,” says Jelle Klapwijk, Senior Client Partner, Life Sciences and Medtech at Cognizant.

Life science applications of agentic AI

Agentic AI has the potential to integrate digital systems across all departments functioning at every stage of the product life cycle. This means that each discrete business function can share knowledge and learn from each other to enhance efficiency across the entire lifespan of the product.

Key examples of how agentic AI can be harnessed across the product lifecycle are:

1. Redefining R&D: Within drug discovery, in transferring projects into clinical manufacturing, for right-first-time regulatory submissions, and for regulatory change impact assessments.
2. Delivering efficiencies across manufacturing and laboratory operations: To accelerate new product introduction, in quality control, and in supply chain optimization.
3. Accelerating commercialization timelines: In augmenting customer relationship management with personalization, in sales and marketing orchestration, and in market access and pricing.

Only scratching the surface

Capable of independent action and complex problem-solving, agentic AI is already revolutionizing a range of aspects of the life sciences ecosystem. While current applications demonstrate significant promise, the industry is only scratching the surface of agentic AI’s potential. As agentic AI evolves, the life sciences space can anticipate a shift toward more proactive and predictive capabilities. This personalized approach, powered by agentic AI, could usher in an era of truly precision medicine, where treatments are optimized for maximum effectiveness and minimal side effects.

“In life sciences in particular, the evolution and refinement of industrial AI agents will be key to reconciling increasingly stringent regulatory requirements impacting the drug manufacturing process with cost- and resource-efficiency demands,” says Jelle Klapwijk.

Nordic contact

Jelle Klapwijk, Senior Client Partner, Life Sciences and Medtech, Cognizant jelle.klapwijk@cognizant.com