Case Study: AstraZeneca — Transforming Oncology Benefit-Risk Analysis

Company

AstraZeneca (Top 10 Global Pharmaceutical)

Therapeutic Area

Oncology — NSCLC & Urothelial Carcinoma

Products

Tagrisso (osimertinib) & Imfinzi (durvalumab)

Development Stage

Post-Marketing Lifecycle Management

ArcaScience Modules Used

Data Intelligence, Decision Intelligence, Automated Outputs

Timeline

12-week implementation

The Challenge

Managing Complex Multi-Product Safety Portfolios

AstraZeneca's oncology franchise faced challenges with managing comprehensive benefit-risk analysis across Tagrisso and Imfinzi. Manual PSUR preparation took 14+ weeks per product. Cross-product signal analysis was siloed. Regulatory timelines were increasingly compressed with EMA's revised PSUR submission requirements. The team needed to manage safety data across 47 ongoing clinical trials and post-marketing surveillance for both products.

The Solution

ArcaScience Platform Deployment

ArcaScience deployed its full platform to unify safety data management and BRA workflows across AstraZeneca's oncology portfolio, enabling cross-product signal detection and automated PSUR generation.

Implementation Process

Weeks 1-3

Data Integration

Connected to AstraZeneca's Argus safety database. Ingested clinical trial data from 47 studies. Established unified signal detection framework across both products.

Weeks 4-6

Signal Detection & Analysis

AI-powered cross-product analysis identified shared immune-related safety patterns. Comparative analysis with class-level competitor data. Automated MedDRA coding validation.

Weeks 7-9

BRA Framework Build

MCDA models for both products with shared criteria. Quantitative benefit-risk scoring with stakeholder-derived weights. Monte Carlo simulations for uncertainty characterization.

Weeks 10-12

PSUR Automation & Delivery

Automated PSUR generation for both products. Interactive regulatory presentation materials. Training for AstraZeneca's PV team on platform usage.

Results

68%

Reduction in BRA
cycle time

Safety signal detection
improvement

40%

Cost savings vs.
manual process

Quantitative Outcomes

Metric	Before ArcaScience	After ArcaScience
PSUR preparation time	14 weeks per product	4.5 weeks per product
Cross-product signal detection	Manual quarterly review	Continuous AI monitoring
PSURs completed Year 1	4 (2 per product)	12 (6 per product)
FTE effort per PSUR	8 FTEs	3 FTEs
New signals identified	2 per year	7 per year (3x improvement)
Annual PV cost savings	Baseline	$2.4M annually

"ArcaScience has fundamentally changed how we approach benefit-risk analysis for our oncology portfolio. The ability to detect signals across products and automate our PSUR workflows has given us both speed and scientific rigor we didn't think were achievable."

— VP, Global Patient Safety, AstraZeneca

"The cross-product signal detection identified an immune-mediated pneumonitis pattern across Tagrisso and Imfinzi that would have taken us months to characterize manually. That kind of insight protects patients and strengthens our regulatory position."

— Head of Oncology Pharmacovigilance, AstraZeneca

Key Takeaways

Cross-product BRA frameworks enable detection of safety patterns that single-product analysis misses.
Automated PSUR generation dramatically reduces cycle times while improving consistency and completeness.
Continuous AI-powered signal detection outperforms periodic manual reviews by identifying signals earlier and with greater sensitivity.
Unified PV platforms reduce FTE burden, allowing safety scientists to focus on signal evaluation rather than data compilation.
The 40% cost savings represents significant ROI and enables reinvestment in enhanced pharmacovigilance activities.

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AstraZeneca: Transforming Oncology Benefit-Risk Analysis