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Cognizant Blog

In the first blog of our Agentic AI series, we explored how Agentic AI can help overcome the persistent barriers slowing pharmaceutical R&D, from siloed data to regulatory complexity. 

However, R&D is not the only part of the product lifecycle experiencing data challenges hindering project success. Drug developers face further complexity throughout manufacturing and laboratory operations, including manual workflows that drain productivity and capacity constraints. To meet rising demand, life sciences companies need smarter, faster solutions. 

In the second blog of our Agentic AI series, we explore how Agentic AI is helping to unlock the next level of efficiency in manufacturing and laboratory operations through autonomous, intelligent action.

The operational bottleneck

As new therapies enter the pipeline, pharmaceutical manufacturers face growing pressure to increase output. The rapid rise in demand for these therapies is outpacing traditional capacity expansion, intensifying the need for more agile and efficient production methods [1]. 

However, manufacturers are finding it increasingly difficult to meet these demands due to persistent, systemic challenges, including:

  • Increased manufacturing complexity 
    Pharma companies face growing pressure to launch therapies faster while managing the demands of complex products like personalized medicines, which require specialized processes and equipment.

  • Manual lab workflows 
    Heavy reliance on manual lab tasks, including data entry and routine testing, slows workflows, limits output and increases the risk of inconsistency.

  • Fragile global supply chains 
    Global supply chains remain vulnerable to disruption, with material shortages and delays threatening production timelines and patient access.

  • Regulatory complexity 
    Expanding into multiple markets means navigating differing requirements mandated by various regulatory bodies, complicating manufacturing and delaying approvals.

These pressures aren’t just operational hurdles throughout manufacturing. The inefficiencies, delays and capacity constraints caused by these issues can have real consequences for patients waiting on life-changing treatments. 

From bottlenecks to breakthroughs with Agentic AI

To meet patient needs with greater speed, precision and resilience, life sciences organizations must transform their manufacturing and laboratory operations to overcome the issues stemming from traditional workflows and siloed systems. By adopting intelligent, autonomous technologies like Agentic AI, life science organizations can transform their operations from the ground up, helping to ensure that vital medicines reach the people who need them, when they need them most.

Empowering digital agents to act autonomously in real time, Agentic AI can deliver various benefits across manufacturing and laboratory operations:

  • Accelerating new product introduction (NPI)

Bringing new therapies into a good manufacturing practice (GMP) production setting is often time-consuming and complex. Agentic AI streamlines this by autonomously configuring shopfloor systems, moving from manual coordination to checklist-driven setup and eventually, one-click deployment. This agility significantly reduces time to production, helping therapies reach patients faster.

  • Enhancing throughput and capacity

As demand intensifies, Agentic AI delivers role-specific insights that help operators, supervisors and plant managers make faster, better-informed decisions in drug manufacturing. Agentic AI can provide a real-time view of performance, enabling tighter process control, reduced variation and improved resource utilization.

  • Proactive predictive maintenance

Unexpected equipment failures can derail production. Agentic AI analyzes historical and real-time sensor data to forecast maintenance needs with precision. By identifying issues before they become problems, teams can schedule interventions proactively, reducing downtime, extending equipment life and avoiding costly delays.

  • Laboratory automation and orchestration

Labs remain a critical bottleneck in the manufacturing chain. Agentic AI can orchestrate high-throughput lab workflows, allocate tasks to instruments efficiently and monitor equipment health in real time. This minimizes human intervention and improves turnaround times while supporting seamless integration with downstream manufacturing.

  • Smarter quality control

Ensuring consistent product quality is non-negotiable for therapeutics. Agentic AI enhances quality control by detecting micro-deviations across data streams, such as temperature, pressure and visual anomalies, that may go unnoticed by human inspectors. Feeding these insights into process analytical technology (PAT) systems tightens control and reduces batch failures and waste.

  • Resilient supply chain optimization

Agentic AI brings end-to-end visibility to supply chains, enabling agents to monitor production, inventory and logistics in real time. When risks like shipment delays or inventory gaps arise, agents can autonomously reroute deliveries, adjust schedules and order supplies to keep operations on track.

Building a smarter, faster future for pharma operations

By enabling autonomous agents to analyze data, make decisions and take action in real time, Agentic AI delivers meaningful efficiency gains across pharmaceutical manufacturing and lab operations. Just as importantly, it frees up expert teams to focus on innovation and continuous improvement, helping more patients receive the treatments they need, faster.

In our next blog, we’ll explore how Agentic AI supports the final phase of the pharmaceutical lifecycle: commercialization. We’ll examine how it enhances regulatory submissions, market access strategies, and sales and marketing performance to maximize product success post-launch.

Want to take a closer look at what’s possible with Agentic AI?

Download the full eBook to explore real-world applications and learn how your organization can get started and how Cognizant and Microsoft can help: https://www.cognizant.com/emea/en/cmp/agentic-ai-in-life-sciences.

 

References:

[1] BioPlan Associates, Inc. (2023, April). Twentieth annual report and survey of biopharmaceutical manufacturing capacity and production: A study of biotherapeutic developers and contract manufacturing organizations. https://bioplanassociates.com/wp-content/uploads/2023/06/BioPlan-Annual-Report-TOC-06052023.pdf




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