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ePQR refers to the electronic execution of the Product Quality Review process. Whereas traditional PQR or APQR preparation often relies on manually gathering product-quality, manufacturing, deviation, change, complaint, laboratory, and process data, ePQR obtains and structures this information from digital systems so that it can be analyzed and interpreted more efficiently. Electronic Batch Record (EBR) is one of the key data sources for ePQR.
In pharmaceutical and regulated manufacturing plants, annual product quality assessment is not just about preparing reports. This process shows whether the product is produced under continuous control, whether process performance is stable, and whether quality risks are identified in a timely manner. Centra Electronic Batch Record (EBR) solution supports making the data generated during production more usable and traceable for ePQR assessments.
ePQR, Parameters, and the Basic Logic of the OCR Dataset
What is ePQR?
ePQR is the electronic execution of the Product Quality Review process. This structure gathers product-based quality data, batch records, process parameters, laboratory results, deviations, CAPA records, and changes within a single digital assessment framework. The aim is to analyze product quality periodically in a faster, more accurate, and more evidence-based manner.
Are ePQR and PQR the same thing?
The basic objective is the same: to periodically evaluate product quality. However, ePQR accomplishes this process using digital, traceable, and analyzable data structures, rather than manual data collection and Excel-based reporting.
How is ePQR related to EBR?
EBR collects batch-based data generated during production. ePQR, on the other hand, analyzes this data based on product, period, line, equipment, process step, or quality parameter. In short, EBR is the digital record of a single batch; ePQR is the electronic analysis layer that collectively evaluates the quality performance of multiple batches.
Is ePQR possible without EBR?
Yes, but the process is more manual. Data is collected from paper records, lab reports, and various Excel files. When using EBR, however, the data comes directly from the production source, making ePQR faster and more reliable.
Why are parameter sets important?
In ePQR, not all data points are equally important. Therefore, sets of parameters to be monitored for the product and process must be defined. These sets may include critical process parameters, critical quality characteristics, IPC results, final QC analyses, yield values, deviation numbers, and process trends.
How to select a parameter set?
Parameter selection should be risk-based. Data that directly affect product quality, demonstrate process performance, and are suitable for periodic comparison should be prioritized. For example, in tablet production, data such as weight, hardness, friability, dissolution, assay, and moisture content may be meaningful for ePQR.
What is an OCR dataset?
OCR stands for Optical Character Recognition. An OCR dataset is a data structure created by converting data from paper or scanned documents into digital text. In the context of ePQR, OCR can be used to make critical data from historical paper batch records or PDF reports available for digital analysis.
Why is OCR important for ePQR?
In many businesses, past PQR data is stored in paper files or scanned PDFs. OCR allows this data to be made readable. Thus, past batch records, quality results, and process parameters can be included in digital analysis.
Which data can be digitized with OCR?
With OCR, fields such as batch number, production date, product name, equipment information, process time, temperature, humidity, pressure, weighing quantity, IPC results, QC analysis values, deviation explanations, and approval information can be digitized. However, OCR output always requires human or system verification.
Can OCR data be considered directly reliable?
No. OCR can be prone to errors, especially with handwriting, low-quality scans, complex table structures, or old documents. Therefore, data from OCR should be supported by validation rules, user control, and, if possible, a double-check mechanism.
Frequently Asked Questions about ePQR
How to use CPK and PPK analysis in ePQR?
ePQR can utilize process capability indicators such as Cpk and Ppk when evaluating product and process performance. Cpk indicates how well the process operates relative to specification limits, while Ppk helps assess the actual performance distribution over a longer period. Structured data from EBR enables these calculations to be performed more systematically.
Should CPK be calculated for each parameter?
No. The CPK/PPK calculation should be used only on measurable, sufficient data points and qualitatively meaningful parameters. This analysis may be misleading on non-critical or irregularly collected data.
For which departments does ePQR create value?
ePQR provides value not only to the quality assurance team but also to the production, quality control, validation, regulation, technical operations, and senior management teams. QA monitors product quality trends, production teams see process variability, QC can compare laboratory results periodically, and management monitors quality performance more clearly.
What does ePQR provide for senior management?
For senior management, ePQR provides a clearer overview of the overall product quality status, recurring deviations, process risks, yield losses, and improvement opportunities.
How does ePQR differ from the manual PQR process?
In the manual PQR process, data is collected from various sources, transferred to Excel spreadsheets, and reports are mostly prepared manually. In ePQR, however, data is retrieved from systems, classified by product and period, and graphs and summaries can be automatically generated. This approach reduces report preparation time and increases data consistency.
Will manual PQR disappear completely?
ePQR can significantly reduce the burden of report preparation; however, it does not eliminate quality review. QA and related teams still evaluate data, interpret deviations, and make necessary improvement decisions.
How does ePQR support validation and data integrity?
For ePQR to be reliable, the source, accuracy, timestamp, change history, and approval status of the data used must be traceable. Since EBR systems have electronic signature, audit trail, and authorization structures, the reliability of the data transferred to ePQR can be more strongly defended.
Is OCR data considered within the scope of validation?
Yes. If OCR generates data to be used in GxP decisions, then its accuracy rate, data control mechanism, user approval, and error management should be evaluated in terms of validation.
How does Centra EBR contribute to the ePQR process?
Centra EBR can strengthen the data foundation of the ePQR process by digitally storing production data, process parameters, electronic signatures, deviation records, limit controls, and audit trails. This makes product quality assessments faster, more traceable, and more analyzable.
What should businesses do to start the ePQR process?
Businesses should first analyze which data is used in their current PQR/APQR process, where this data comes from, and which is collected manually. Then, they should plan how to integrate data from EBR, LIMS, QMS, and OCR sources. To digitize the ePQR process and evaluate the appropriate data model, you can contact Centra via their information page.
