In the loop

Modular agents are reshaping life sciences workflows while keeping humans updated

In life sciences, speed and transparency are crucial. Agentic AI, composed of autonomous, task specific agents, is accelerating drug discovery, trial design and regulatory readiness, while keeping humans firmly in the loop.

Unlike conventional automation, agentic AI comprises modular agents that autonomously analyse, decide and act across complex workflows.

They surface subtle patterns in chemical, biological and real-world data; simulate trial scenarios dynamically; and flag safety signals early, without losing explainability or control.

In highly regulated settings, decision traceability and auditability are non-negotiable. Agentic AI architectures are explicitly designed to document the ‘how’ and ‘why’, supporting compliance and human validation at every step.

Yet data noise and bias can derail even the most advanced systems. Without strong governance, corrupted data can lead to skewed predictions or biologically implausible outputs.

That’s why enterprise AI platforms, like those developed at SAS, integrate large language models, enterprise tools, memory features and other capabilities alongside explainable decision engines, version control and guard rails that support agentic workflows with verifiable precision.

Real-world momentum backs this up. Today, about 80% of pharmaceutical and life sciences professionals use AI in drug discovery workflows and AI is projected to deliver $350bn+ in annual value by 2025.

According to a survey reported by Axios: ‘53% of life sciences firms that have adopted AI have formal policies, and 51% conduct regular audits.’ But fewer than half have combined these elements into a fully mature governance framework.

Agentic AI is already proving its value across the drug development spectrum. In early research, agents can traverse massive biochemical and genomic data sets, surfacing novel molecules and biomarkers that might never be spotted through manual analysis.

In clinical development, they integrate real-world evidence to design smarter, more adaptive trials, optimising patient stratification, predicting safety and efficacy outcomes and helping regulators review models with confidence.

The benefits extend to rare disease research too, where limited patient data has long hindered progress.

Synthetic or agent-augmented inputs can bridge those gaps, making trials viable that would otherwise falter on statistical power.

And beyond the science itself, AI agents are quietly orchestrating the operational side of development, streamlining regulatory documentation and even commercial planning, shrinking timelines from months to weeks while keeping every step traceable and auditable.

Agentic AI is not about replacing human expertise, but rather augmenting it. Organisations calibrate agent autonomy based on task criticality and risk. Manual override remains standard.

This hybrid mindset builds user confidence, especially with early wins like automating manual compliance reporting or protocol version control, so that scientists see tangible benefits quickly.

It’s critical that governance is layered from day one with built-in transparency, risk mitigation and auditability aligned with regulatory standards. A patient-first mentality ensures all recommendations support ethical, safe outcomes.

Adoption hurdles remain. In one recent survey: ‘51% of life science professionals cited resistance to change as a top barrier to agentic AI innovation.’ That’s why successful deployment means pairing technology with behavioural change and aligning workflows around new forms of human-AI collaboration.

Agentic AI, guided by rigorous governance and decision frameworks, won’t just accelerate drug development, it has the potential to redefine it.

As the industry moves from experimentation to enterprise integration, advanced platforms, including those developed by SAS, are enabling life sciences organisations to turn ideas into impact faster, smarter and with greater transparency than ever before.

Jonathan Riches is Head of Life Sciences, Europe at SAS