Clinical Trials, Reimagined: Decision Intelligence in Action

In clinical trials, every shipment of investigational medicine plays a critical role in maintaining treatment schedules and ensuring study integrity. But as trials grow more global and complex, supply chains must contend with unpredictable demand, evolving protocols, siloed systems, and high manual workload. The result is often a scramble to identify issues, coordinate teams, and avoid costly disruptions that could compromise patient care and regulatory compliance.

To meet these growing demands, life sciences organizations are turning to decision intelligence. By embedding real-time, context-aware intelligence into clinical logistics, decision intelligence enables teams to move from reactive triage to proactive orchestration. It helps detect risk earlier, recommend smarter interventions, and reduce unnecessary effort — all while learning from each decision to continuously improve performance. The result is a more resilient, responsive clinical supply chain that can keep pace with the demands of modern research.

Why Traditional Approaches Fall Short

Coordinating investigational medicines and supplies across global trials is an inherently complex task. Traditional methods rely heavily on spreadsheets, email threads, and siloed systems, leaving teams to manually track shipments, verify site readiness, and respond to issues as they arise.

The result is often missed opportunities to act, reactive interventions, and high levels of cognitive load for clinical supply professionals. Key challenges include:

• Multi-geography operations: Shipments span regions with different customs, logistics networks, and compliance rules, each introducing friction and variability.
• Dynamic study protocols: Changes to eligibility criteria, study design, or site activation can quickly shift demand patterns, making static plans obsolete.
• Unpredictable demand: Patient enrollment rates, treatment arms, and retention vary by site, often in ways that are hard to forecast and even harder to manage.

These factors introduce uncertainty at every turn. And in a setting where timely delivery is mission-critical, the margin for error is thin.

The Case for Decision Intelligence

A smarter, more proactive approach is needed — which is where decision intelligence comes in. By combining real-time data, AI-driven insights, and automation, decision intelligence helps clinical supply teams shift from reactive triage to forward-looking orchestration, spotting issues sooner, understanding their impact, and guiding the right response.

Aera, the decision intelligence agent, brings this approach to life. It acts as an always-on, context-aware layer that continuously monitors supply flows, flags emerging risks, and recommends the next best action, tailored to the situation, the user, and the clinical context. Unlike traditional tools that simply alert users to problems, Aera interprets delays in light of protocol needs, patient risk, and downstream impact. It then simulates options, recommends a path forward, and learns from every decision made — growing more accurate and effective over time, all while keeping human decision-makers in control.

A Closed-Loop System for Smarter Inventory Management

Most clinical supply chains are saturated with data — from Interactive Response Technology (IRT) systems, shipment trackers, and ERP feeds — but lack a mechanism to act on it cohesively. Aera changes that. It brings together clinical, operational, and external intelligence into a closed-loop, learning system comprised of six steps:

1. Unified data foundation: Aera ingests information from IRT, ERP, logistics feeds, and risk indicators to create a single view of demand, supply, and shipment status.
2. Trigger detection: Intelligent thresholds and milestone tracking detect early signs of delay, flagging potential issues based on expected timelines, shipment states, and clinical priority.
3. Context-aware simulation: The agent assesses root causes, forecasts impact to sites and patients, and proposes mitigation options like rerouting or site-to-site reallocation.
4. Next-best-action recommendations: Based on risk, feasibility, and user role, the agent suggests high-confidence steps, from automated emails to escalations or delivery confirmation.
5. Integrated execution: Smart emails, reminders, and status checks are embedded directly in workflows, so recommended actions turn into verified outcomes.
6. Continuous learning: Each decision and result is captured to improve future recommendations, refine thresholds, and adapt to shifting study needs.

With this structure in place, teams gain not just visibility, but also the ability to act with precision and speed.

Real-World Results at Scale

One global biopharmaceutical leader faced a familiar challenge: growing trial complexity, rising headcount, and still nearly 60% of packed product ending up as waste. Manual processes and fragmented data made it hard to scale or manage risk effectively.

To address this, the company partnered with Aera Technology and ZS, a global life sciences consultancy. After launching a data excellence initiative, the first Aera Skill went live in just three months, freeing analysts from manual data wrangling and surfacing risks in real time. In one early success, Aera flagged a stalled cancer trial shipment over the weekend, enabling proactive intervention before a stock-out occurred.

As additional skills were deployed, more improved outcomes followed:

• Reduced product waste: Better data integrity and smarter, context-aware decision-making helped cut down excess and prevent avoidable loss.
• Faster deployment cycles: New capabilities launched quickly to support continuity and reduce supply disruptions.
• Scalable, self-healing network: A foundation was established for intelligent orchestration across clinical and commercial operations.

By uniting domain expertise with decision intelligence, the organization is building a faster, more resilient clinical supply chain.

Empowering the People Behind the Decisions

Decision intelligence doesn’t just streamline operations; it transforms how clinical supply professionals work. By embedding intelligence directly into their workflows, Aera reduces manual effort, clarifies priorities, and enables faster, more confident decisions.

Here’s how it transforms work for each of these roles:

• For logistics specialists, the agent filters out noise and highlights only the most urgent issues, often with ready-to-send emails and clear next steps. With 75–90% less effort per alert, they can focus on high-impact coordination instead of chasing status updates.
• For clinical supply study leads (CSSLs), Aera improves visibility, auto-verifies deliveries, and triggers smart escalations when protocol-sensitive shipments are at risk. With prioritized tasks and patient-aware alerts, CSSLs can manage study continuity proactively, not reactively.

By taking on the heavy lifting, the agent frees teams to apply their expertise where it matters most, protecting patients, trials, and timelines.

Human + AI: Smarter Decisions, Together

The power of decision intelligence lies in the collaboration between people and technology. Aera doesn’t replace clinical supply professionals — it amplifies their expertise. By handling data-heavy tasks like risk detection, root cause analysis, and mitigation modeling, the agent clears the way for humans to focus on judgment, coordination, and strategic oversight.

Users remain in control at every step. Recommendations are transparent, explainable, and tailored to role and context, whether that’s a logistics specialist managing vendor follow-ups or a CSSL overseeing protocol-critical milestones. Users can adapt, accept, or override suggestions as needed.

And because the system learns from every interaction — every confirmation, escalation, or adjustment — it continuously improves. Over time, this feedback loop builds a smarter, more aligned decision system that evolves with the needs of the organization. With Aera, clinical supply decisions become more consistent, coordinated, and confident — not because humans are removed from the loop, but because they're empowered within it.

A Blueprint for the Future of Clinical Supply Chains

As clinical trials evolve — with more sites, more data, and higher expectations — success will depend on the ability to manage complexity with speed and precision. Aera provides the infrastructure to do just that.

By transforming fragmented systems into a unified, self-learning network, decision intelligence empowers clinical supply chains to become proactive, adaptive, and resilient. They sense risk early, recommend action intelligently, and execute reliably, ensuring every patient receives what they need, when they need it.