Agentic AI Use Cases – Life Sciences 2025

The life sciences sector is witnessing rapid evolution in the adoption of Agentic AI, with use cases offering critical insights into the industry’s maturity, demand, and strategic direction. Applications of Agentic AI vary widely across the value chain, from drug discovery and clinical trials to regulatory affairs. The report highlights the factors behind prioritizing use cases such as clinical trials and drug discovery, owing to its impact on reducing R&D timelines, optimizing trial design, and enhancing predictive accuracy.

Emerging use cases such are gaining momentum, highlighting the industry’s growing focus on precision medicine and personalized therapies. While these areas are still at a developing stage, high-priority applications including clinical trials and drug discovery are leading to faster adoption owing to their significant impact on scalability, efficiency, and compliance.

Adoption patterns are strongly influenced by integration capabilities and regulatory readiness. Organizations with established digital infrastructures and collaborations with technology providers are scaling Agentic AI across R&D and clinical functions. However, others face barriers such as siloed data, high integration costs, and stringent compliance requirements. Case studies highlight how early adopters are moving beyond pilot projects to enterprise-level deployments, demonstrating the transformative potential of Agentic AI in accelerating drug discovery, optimizing clinical trials, and strengthening regulatory workflows.

Key Highlights

• Maturity of Agentic AI in the Life Sciences Sector – Analysis of leading pharmaceutical companies and service providers shows that Agentic AI adoption in the life sciences sector is still in its early stages. While initial implementations demonstrate potential in drug discovery, clinical trials, and regulatory compliance, widespread deployment is limited. Organizations are gradually exploring scalable and autonomous AI solutions to improve efficiency, decision-making, and operational agility.

• Transforming Life Sciences Workflows through Agentic AI – Agentic AI is transforming life sciences by accelerating drug discovery, clinical trials, and regulatory workflows. It designs and simulates molecules, predicts drug-target interactions, and mines data for novel targets, while optimizing trial protocols, speeding patient recruitment, and enabling real-time monitoring. Multi-agent systems further automate reporting, ensure data integrity, and streamline compliance documentation.

• The Future of Agentic AI in Transforming Life Sciences – Agentic AI is anticipated to drive hyper-personalized drug development, integrate genomics for precision medicine, and enable real-time optimization of drug discovery and clinical trials. By complementing researchers, it has the potential to enhance trial design, patient selection, and operational efficiency, while extending its impact across manufacturing, supply chains, regulatory compliance, and post-market surveillance.

• Challenges of Implementing Agentic AI in Life Sciences – Life science companies face challenges in adopting Agentic AI, including data privacy and security concerns, integrating heterogeneous datasets, ensuring regulatory compliance, maintaining transparency in AI-driven decisions, and balancing human oversight with automation. Additionally, high computational costs, model interpretability, and workflow disruption can slow adoption across drug discovery, clinical trials, and regulatory processes.

Table of Contents

1. Key Highlights

2. Introduction

3. Agentic AI Use Cases Across Life Science Value Chain

4. Framework for Evaluating Agentic AI Use Cases in Life Sciences

5. Case Studies – Deep Dive into Agentic AI Use Cases

6. Supply Side Perspective: Agentic AI Solution Providers in Life Sciences

7. Future Trends and Use of Agentic AI in Life Sciences Industry

8. Recommendations for Tech Buyers and Vendors

A Complimentary 45-Minute Strategic Session on Agentic AI for Life Sciences Leaders

AIM Research’s Research Analyst will deliver a complimentary 45-minute session focused the report on –  Agentic AI use cases in the life sciences sector. The briefing provides strategic insights tailored to tech buyers and vendors, including C-suite executives, product development teams, and business leaders. The content can also be customized based on organizational needs or executive roles.

Tech Vendors Perspective

Product and Development Executives: Gain insights into high-value use cases such as clinical trials optimization, drug discovery, pharmacovigilance, and personalized medicine, including technical considerations, scalability, and integration strategies.

Sales and Marketing Teams: Gain actionable insights to inform data-driven marketing strategies and optimize client engagement.

Strategic Roadmaps: Learn emerging trends, adoption challenges, and competitive positioning to guide product development and go-to-market strategies.

Tech Buyers Perspective

C-Suite Executives: Evaluate the strategic potential of Agentic AI for accelerating R&D, improving efficiency, and ensuring regulatory compliance, with insights on ROI and risk management.

IT and Digital Transformation Leaders: Gain a comprehensive view of Agentic AI applications across the life sciences sector, with specific insights into its use in clinical trials and other key life sciences processes. Understand approaches for vendor evaluation for Agentic AI Platforms in Life Sciences.