Welcome to the 8th edition of Mareana Deep Dive. This edition includes our updates from April and May 2026.

[Whitepaper] A Quality Leader’s Guide to Review by Exception

Pharmaceutical manufacturers are increasingly burdened by a parallel infrastructure of manual documentation and review that consumes as much labor as the physical production of medicine. Relying on paper-based records or unstructured PDFs forces Quality teams to spend up to 70% of their bandwidth on mechanical proofreading rather than high-value process improvement. To remain competitive and compliant with evolving global mandates, organizations must transition to data-driven Review by Exception (RbE) models that replace manual verification with algorithmic oversight.

You can access the whitepaper here: A Quality Leader’s Guide to Review by Exception

Review by Exception Guide

[Blog] How Virtual Sponsors Are Solving the CDMO Batch Record Problem from Their Side

Virtual pharma sponsors face increasing compliance pressure and fragmented CDMO data that traditional solutions cannot effectively address. A sponsor-side Manufacturing Intelligence Platform (MIP) uses AI to convert unstructured manufacturing records into structured, actionable insights, enabling real-time visibility, automated compliance, and audit-ready data without requiring changes to CDMO operations.

Read How Virtual Sponsors Are Solving the CDMO Batch Record Problem from Their Side.

[Blog] AI In Pharma Manufacturing: A Deep Dive

AI is transforming pharmaceutical manufacturing by improving efficiency, quality, and compliance across key operations. Strong data foundations, system integration, and risk-based validation are essential to make AI effective in regulated environments. High-value applications include batch digitization, predictive maintenance, supply chain forecasting, review by exception, and process monitoring. Overall, AI is emerging as a strategic enabler for pharma companies that want to modernize manufacturing while staying audit-ready and compliant.

Read our blog AI In Pharma Manufacturing: A Deep Dive to dig deeper.

[Blog] Manual Batch Record Review: Hidden Costs and Compliance Risk

Manual batch record review is becoming a major bottleneck in pharmaceutical manufacturing, especially where teams still rely on paper records or static PDFs. Much of QA’s time is spent on repetitive verification of signatures, dates, calculations, and documentation instead of activities that directly improve quality. The blog frames this as the “Hidden Plant,” where administrative review work adds cost, delays batch release, and increases compliance risk. It also introduces Review by Exception as a smarter approach, where software handles routine compliant checks and only escalates unusual events to QA.

Read Manual Batch Record Review: Hidden Costs and Compliance Risk and prepare yourself for the changing landscape of pharma compliance.

[Blog] Three Paths to Faster Batch Review: Beyond the Enterprise MES Assumption 

Review by Exception (RbE) is becoming essential for pharmaceutical manufacturers looking to reduce manual batch review and accelerate batch release. Vishal explores three practical paths to implementation: Document Review Automation (DRA), Composable MES, and Enterprise EBR/MES, while explaining how manufacturers can choose the approach that best aligns with their operational maturity, business model, and digital transformation goals. The piece also highlights the key capabilities organizations should evaluate when modernizing batch review, reinforcing that successful transformation depends on selecting the right architecture for their unique operational reality.

Learn the Three Paths to Faster Batch Review: Beyond the Enterprise MES Assumption.

[Video] AI v/s OCR – Digitization of Paper Batch Records

See How AI Transforms Paper Batch Records into Trusted Manufacturing Intelligence

[Inside Mareana] Events and Celebrations

At Mareana, we invest in people to better serve our customers.

Mareana’s Vishal Prasad Featured in Innovations in Pharmaceutical Technology

Rewards and Recognition

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