Review by Exception: Connecting the Dots for Faster Batch Release

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In batch production, efficient exception management means reducing the time required to identify, review, and resolve process exceptions. Incorporating review by exception functionality within manufacturing execution system (MES) software can streamline biopharmaceutical product release.

Increased competition and complexity, and the mandate to reduce drug costs, are driving the life sciences industry to leaner, more efficient manufacturing operations. This is particularly true for biopharmaceuticals, whose processes are more complex than those for small-molecule therapeutics and which face competition from biosimilars. 

Given current growth rates, the cost of developing a new biopharmaceutical has increased to approximately US$1.1–2.2 billion (EUR 1–2 billion). 

Regulators demand that manufacturers continuously align their operations with regulatory requirements to ensure compliance and product quality.  Achieving this alignment can be challenging, however, in a fast-growing market and a manufacturing  environment marked by increased outsourcing and supply chain complexity, as well as demographic trends.  

As a growing number of experienced professionals retire, there is a greater need for knowledge management and transfer.  At the same time, contract manufacturing organizations (CMOs) are looking for greater flexibility in meeting customer demands and there is a heightened need to coordinate primary API manufacturing and secondary drug product manufacturing operations around the world.

Manufacturing operations objectives

Examining a typical production facility, a pharma operations manager can easily see both the  “actual plant” and the “hidden plant”. The actual plant refers to the transformation of input materials into value-added product. However, the hidden (or “paper”) plant is just as important, and very large because of all the information that must be collected and documented to guarantee product quality and regulatory compliance. Ask any biopharm operations manager, and they’ll probably tell you that maintaining the paper plant takes as much effort as running the actual plant.

Manufacturing leaders are looking to increase right-first-time production, accelerate batch release, enforce regulatory compliance and reduce the cost of manufacturing, and many are implementing digital transformation initiatives to meet these goals. But how can these goals be achieved and digital transformation be effective, while pharmaceutical companies are still running paper-based manufacturing operations?

It is worth reflecting on the limitations of paper-based manufacturing and why this is an issue for lean manufacturing operations. Firstly, in a paper-based environment, it is not possible to enforce work flows or to detect human errors when they happen. As a result, processes slow down and more resources must be used to route paper documents from one location to another. 

In addition, paper-based information can only be viewed by one person at a time and critically, cannot be integrated with other electronic data. As a result, more time and effort are required to analyze data or report information across batches.

Batch release operations

As regulations become more demanding and processes more complex, batch records have become larger and more complex. A batch record can have hundreds of data entries. In a paper-based batch record, incorrect data entry can occur in various areas including manual reporting of process parameters, including missing signatures, incorrect forms being filled out, and the wrong forms sent to the wrong people. Documentation in different storage areas complicates investigation, reporting, and analysis. Consequently, typical paper-based batch release times can take 10–40 days.


Manual data entry errors happen in one out of every 100 entries and a single batch report can contain tens of errors. Right-first-time production can be as low as 47%, with studies indicating the causes for this are 40% equipment-based, 40% operator-based, and 20% caused by other issues. Two out of five wrong-first-time batches therefore are due to operator errors. The average review time for a single batch report is 48 hours and some manufacturers have reported a single full batch report review taking up to 500 hours. An electronic batch record (EBR) system can reduce manual data-entry times by at least 60%.

The journey from paper-based production to a fully electronic manufacturing system must be thoroughly planned, particularly when applied to an existing operating plant. A first incremental step forward from paper-based manufacturing can be the use of `paper-on-glass’ to guide the operators through the process workflow and then to collect data entries on the screen rather than on paper. 

This first step is important for a smooth transition, not to mention the importance of change management. A further step would be implementing the logics related to equipment, material, and skills management to enforce compliance and deliver a comprehensive EBR. 

When batch data are recorded electronically, quality and operations teams can review and approve the manufacturing of a batch based on a full report or, once the EBR system established, by focusing on exceptions with the support of simpler exception reports. 

A final stage of the electronic journey that can substantially reduce batch cycle time is to anticipate exception resolutions as soon as they occur. The real-time review by exception approach is meant to reach the end of the manufacturing process with almost no open exceptions and to allow for a faster release of the end-product. 

Incorporating review by exception in the MES 

To help companies achieve paperless production, automation technology providers have expanded their MES solutions, including features for weighing and dispensing, material management, equipment management, documents management, shift logbooks, EBR management, and quality review management (QRM).  

QRM aims to support the implementation of a real-time review by exception process. The International Society for Pharmaceutical Engineering (ISPE) defines this as “an approach in which manufacturing and quality data are screened to present or report only critical process exceptions as required by approvers for review and disposition of intermediates and products.” In this case, according to ISPE, human review and approval of electronic production records only need occur when a production parameter is out of specification, or features some other discrepancy or critical condition. 

The staff competencies fostered by review by exception methodologies and QRM can be a key workforce skill-builder for manufacturers that are digitizing their manufacturing operations. Digital transformation competencies such as automated workflows improve operational performance by eliminating repetitive tasks and enabling personnel to focus on exceptions and prioritize opportunities that require human intervention. 

Comprehensive QRM should monitor and manage process deviations. This should support a review by exception methodology by providing the ability to capture exceptions from the MES, process control, supervisory control and data acquisition (SCADA) and other systems by monitoring alarms and events. This approach allows the types of exception to be categorized to help organize the review process based on the type of exceptions that occur. 

Resolution stages and workflows optimize the review process, and users can rely on the severity of the exceptions to help focus and prioritize efforts. QRM functionality supports an efficient review-by-exception methodology, allowing quality and manufacturing personnel to collaborate to release batches faster, resulting in a reduction in inventory and in the time required to release product to patients, while continuing to promote quality. 


QRM functionality within life science MES facilitates the collaboration of stakeholders around exceptions. Improving data integrity by capturing the exceptions’ context at the source and maintaining these data in one place, reducing the effort required to managing the data. Processing the review of exceptions as exceptions arise in real-time helps to improve productivity and reduce overall batch review time, enabling manufacturers to release products to the market faster.