Commissioning, qualification, and validation (CQV) remain foundational to pharmaceutical manufacturing, ensuring that facilities, equipment, utilities, processes, and computerized systems operate as intended. For decades, paper-based documentation, manual data entry, and fragmented recordkeeping were considered sufficient to demonstrate compliance. That assumption no longer aligns with regulatory expectations.
The life sciences industry is operating in an environment of unprecedented regulatory scrutiny — particularly around data integrity, electronic records, and the validated use of computerized systems. Global regulators increasingly expect manufacturers to demonstrate not only that validation activities were performed, but that records are trustworthy, traceable, and reproducible across the lifecycle. In this context, paper-based CQV is no longer a neutral choice; it introduces avoidable risk.
What was once viewed as a modernization initiative is now treated as a regulatory necessity. A paperless, electronic CQV lifecycle has emerged as the most defensible way to support inspection readiness.
Regulatory guidance has been consistent — and increasingly explicit — about the need for reliable electronic records and validated computerized systems.
FDA 21 CFR Part 11 defines controls required to ensure the authenticity, integrity, and confidentiality of electronic records and signatures. It also clarifies how the agency interprets scope and applies enforcement discretion, while still expecting firms to meet predicate rule requirements and maintain trustworthy records (FDA, 1997).
FDA’s Data Integrity and Compliance with Drug CGMP: Questions and Answers guidance similarly emphasizes that organizations must ensure data are reliable and accurate throughout the lifecycle and implement risk-based controls to prevent and detect data integrity issues (FDA, 2018).
PIC/S data integrity guidance further emphasizes ALCOA+ principles — attributable, legible, contemporaneous, original, accurate, complete, consistent, enduring, and available — highlighting vulnerabilities commonly associated with manual practices (PIC/S Secretariat, 2021). Inspectors continue to cite issues stemming from transcription errors, incomplete records, version confusion, and limited traceability
EU GMP Annex 11 reinforces these expectations by requiring computerized systems used in GxP environments to be validated, fit for purpose, and supported by qualified IT infrastructure (European Commission, 2011).
More recently, EU GMP Annex 22 has extended these expectations to artificial intelligence and machine learning, making it clear that advanced technologies must offer equal or greater assurance of data quality and control when used in GxP environments (European Commission, 2023). Together, these guidances reinforce a clear message: paper-based “patches” are increasingly viewed as high-risk because they impede transparency and complicate investigations.
Modern GMP regulations require a lifecycle and risk-based approach to validation. Frameworks such as GAMP® 5 emphasize maintaining clear linkages among requirements, risk assessments, test scripts, execution evidence, and approvals across the validation lifecycle (ISPE, 2022).
Maintaining these linkages is inherently difficult in paper-based environments, particularly for organizations managing large equipment inventories, global sites, or frequent change cycles. Manual systems fragment traceability and increase the likelihood of incomplete or inconsistent records. Digital CQV environments, by contrast, preserve relationships between validation artifacts throughout the lifecycle, strengthening control and reducing risk.
Inspection trends increasingly demonstrate that regulators expect manufacturers to show process knowledge, state of control, and the ability to detect and address issues proactively. Paper systems obscure real-time insight and slow investigations. Data is siloed, reviews are delayed, and assembling evidence becomes a reactive exercise.
Digital CQV provides centralized access to structured data, standardized workflows, and consistent evidence capture. Dashboards enable real-time visibility into execution status, deviations, and open items. This shift reflects a change in how CQV is expected to support compliance.
Even when paper-based practices technically meet minimum compliance requirements, they often impede the speed and coordination modern CQV demands. Manual workflows introduce delays, increase rework, and make maintaining consistency across sites, systems, and suppliers difficult.
Digital CQV environments centralize information and automate routine tasks, which supports more consistent decision-making. Electronic workflows eliminate delays caused by misplaced documents, missing signatures, or manual collation of evidence. As validation workloads intensify, these efficiencies become essential rather than optional.
Digital validation solutions consolidate protocols, execution data, evidence, and approvals into a centralized repository. This single source of truth reduces versioning issues, eliminates transcription risk, and strengthens reproducibility across validation activities.
In large-scale CQV programs, paper workflows are prone to inconsistency. Digital systems ensure that all stakeholders work from controlled documentation, with updates reflected automatically and changes tracked through secure audit trails.
The quality and compliance benefits of digital CQV extend beyond efficiency. Electronic systems preserve critical metadata, including timestamps, authorship, version history, and audit trails, which makes retrospective QA review more reliable and transparent. By contrast, paper-based evidence often lacks the metadata required to support investigations or defend decisions during inspections.
Table 1 illustrates key differences between paper-based and paperless CQV approaches, highlighting how digital systems improve data integrity, evidence capture, review cycles, traceability, and long-term archival reliability. These are not incremental improvements; they address structural weaknesses in manual practices.
Automation further reduces human error by enforcing required fields, structured data formats, and workflow sequencing. Digital CQV ensures validation activities are carried out consistently across projects and sites, strengthening data quality and reducing rework.
Once a secure, validated digital CQV foundation is established, AI-enabled capabilities provide an additional layer of assurance when implemented with clearly defined intended use, risk-based validation, and appropriate human oversight based on GxP impact. Smart content generation accelerates the creation of protocols, reports, and test scripts using predefined templates and historical data, improving consistency while dramatically reducing preparation time (with outputs reviewed and approved under controlled workflows).
AI-enabled execution tools detect anomalies in real time, flag deviations during test execution, and minimize delays between steps by prompting required actions and routing exceptions for review. Predictive analytics identify emerging issues based on historical patterns, improving audit readiness and reducing downtime.
Importantly, these capabilities must themselves be governed within a validated, risk-based framework. In line with GAMP 5, Annex 11, and Annex 22, AI functions should be treated as GxP-relevant features, with clearly defined intended use, proportionate testing, transparent records (including audit trails where applicable), and qualified personnel retaining final decision-making authority.
Organizations that persist with paper-based CQV — particularly in complex, multisite, or highly automated environments — face increasing regulatory, operational, and quality risks. Manual entries create ambiguity, prolong cycle times, and inflate project costs. Without real-time insight, teams cannot detect issues promptly, increasing the likelihood of deviations and rework.
As regulatory expectations continue to evolve, the limitations of paper-based CQV pose a significant compliance threat.
Moving beyond paper is no longer about efficiency alone. A paperless, risk-based CQV approach is the most defensible way to meet regulators’ expectations while strengthening data integrity across the lifecycle. Digital foundations reduce audit risk, accelerate timelines, and improve the completeness, traceability, and reproducibility of validation evidence.
More importantly, digital CQV provides the transparency and insight required to maintain a continuously validated state. For most organizations, adopting a paperless CQV framework is no longer optional. It is a strategic imperative for organizations seeking to remain inspection-ready and resilient in a rapidly changing regulatory landscape.
Read related content — Industry Insight: The Impact of Artificial Intelligence on CQV
European Commission. (2011). EudraLex Volume 4: EU guidelines for good manufacturing practice for medicinal products for human and veterinary use. Annex 11: Computerised systems. https://health.ec.europa.eu/medicinal-products/eudralex/eudralex-volume-4_en
European Commission. (2023). EudraLex Volume 4: EU guidelines for good manufacturing practice for medicinal products for human and veterinary use. Annex 22: Artificial intelligence. https://health.ec.europa.eu/medicinal-products/eudralex/eudralex-volume-4_en
International Society for Pharmaceutical Engineering. (2022). GAMP® 5: A risk-based approach to compliant GxP computerized systems (2nd ed.). https://ispe.org/publications/guidance-documents/gamp-5-guide-2nd-edition?
PIC/S Secretariat. (2021). Good practices for data management and integrity in regulated GMP/GDP environments (PI 041). https://picscheme.org/en/news/draft-pic-s-good-practices-for-data-management-and-integrity
U.S. Food and Drug Administration. (1997). Electronic records; electronic signatures (21 CFR Part 11). Code of Federal Regulations, Title 21. https://www.ecfr.gov/current/title-21/chapter-I/subchapter-A/part-11?utm_
U.S. Food and Drug Administration. (2018). Data Integrity and Compliance with Drug CGMP: Questions and Answers. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/data-integrity-and-compliance-drug-cgmp-questions-and-answers