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INTERNATIONAL JOURNAL OF DATA SCIENCE AND MACHINE LEARNING (ISSN: 2692-5141)
Volume 05, Issue 01, 2025, pages 170-181
Published Date: - 15-05-2025
Doi: -
https://doi.org/10.55640/ijdsml-05-01-17
GMP Compliance and MES: Strategies for Automated
Compliance Assurance
Shriprakashan. L. Parapalli
Emerson Automation Solutions, Durham, NC- USA
BioPhorum, The Gridiron Building, 1 Pancras Square, London, NIC 4AG UK
International Society for Pharmaceutical Engineering (ISPE), 6110 Executive Blvd, North Bethesda, MD 20852, USA
MESA International, 1800E.Ray Road, STE A106, Chandler, AZ 85225 USA
ABSTRACT
Current Good Manufacturing Practice (cGMP) regulations emphasize stringent control over production processes,
personnel, equipment, and documentation in pharmaceutical manufacturing. Meeting cGMP requirements
involves meticulous recordkeeping, comprehensive quality control, and robust oversight
—
processes that are
prone to human error when relying on traditional, paper-based approaches. Against this backdrop, Manufacturing
Execution Systems (MES) offer a powerful solution for managing production workflows and ensuring regulatory
adherence. This paper explores the integration of MES in a cGMP environment to automate compliance assurance
and details key strategies including automated validation, data integrity assurance, QMS integration, regulatory
reporting, training and competency tracking, risk-based automation, and AI-driven continuous improvement.
Through literature reviews and case study analyses, we identify critical process elements where MES adds the
most value, such as reducing human error, streamlining documentation, and facilitating digital audit trails. The
findings suggest that adopting MES not only enhances operational efficiency but also enables a proactive approach
to regulatory compliance, positioning organizations to adapt quickly to evolving industry standards.
KEYWORDS
cGMP, GMP Compliance, Manufacturing Execution System, Quality Control, Pharmaceutical Manufacturing,
Automated Compliance, Regulatory Adherence, Electronic Recordkeeping, Process Control, Data Integrity
INTRODUCTION
Pharmaceutical manufacturing operates under stringent regulatory frameworks to ensure product quality, efficacy,
and patient safety. In the United States, the Food and Drug Administration (FDA) enforces these standards through
current Good Manufacturing Practice (cGMP) regulations, codified in 21 CFR Part 211 [5] These regulations outline
comprehensive requirements for personnel qualifications, documentation protocols, process controls, equipment
maintenance, and quality assurance, all designed to minimize errors and ensure batch-to-batch consistency [8,13].
Globally, analogous standards, such as the European Union’s GMP guidelines [2] reinforce these principles,
emphasizing traceability and accountability across the production lifecycle [2]. Despite these rigorous mandates,
many pharmaceutical facilities continue to rely on traditional paper-based systems for documentation and
compliance management. As production lines grow increasingly complex
—
driven by technological advancements,
global supply chains, and the rise of personalized medicine
—
manual record-keeping introduces significant risks,
including transcription errors, oversight gaps, and inefficiencies that can lead to non-
compliance [10,16]. The FDA’s
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2018 guidance on data integrity highlights these concerns, stressing the need for robust systems to ensure accurate,
attributable, and secure data [3]. Paper-based processes are increasingly inadequate for meeting these
expectations, particularly in high-throughput environments where human error can compromise compliance [1].
Manufacturing Execution Systems (MES) have emerged as a transformative solution to address these challenges.
MES platforms digitize workflows, enable real-time data capture, and integrate seamlessly with enterprise resource
planning (ERP) systems, providing enhanced visibility and control over manufacturing processes [15,7]. By
automating critical functions
—
such as electronic batch records (eBR), process monitoring, and audit trails
—
MES
reduces compliance risks associated with manual errors and improves responsiveness to production anomalies
[6,11] Moreover, MES aligns with the FDA’s data integrity expectations by ensuring secure user access cont
rols,
reliable data backups, and comprehensive audit trails [3].To illustrate this alignment, (
Fig.1
) presents a conceptual
diagram mapping key MES functionality to cGMP requirements. The diagram categorizes cGMP mandates (e.g.,
documentation under 21 CFR
211.186, process controls under 21 CFR 211.110, and data integrity per FDA’s 2018
guidance) along one axis, with corresponding MES features (e.g., eBR, real-time monitoring, and audit trails) along
the other. Arrows indicate how specific MES capabilities address regulatory obligations, such as eBR ensuring
complete batch records or real-time monitoring facilitating in-process controls. This visual framework underscores
the potential of MES to bridge gaps in traditional systems, offering a structured approach to compliance assurance
[7].
However, MES adoption in the pharmaceutical industry remains uneven. High initial investment costs perceived
regulatory uncertainties surrounding electronic records (21 CFR Part 11), and resistance to transitioning from
established paper-based processes pose significant barriers [9,12,14]. These challenges highlight the need for a
clearer understanding of how MES functionalities align with cGMP requirements and support compliance in
practice, as depicted in (
Fig.1
), which serves as a foundation for the analysis in this paper.
Research Gap and Objectives
Research Gap
: Existing cGMP processes in many pharmaceutical facilities rely heavily on manual checks and paper-
based documentation, rendering compliance labor-intensive, error-prone, and increasingly inadequate for modern
manufacturing complexities [10,1]. While MES solutions promise to streamline compliance through automation,
there is a lack of comprehensive studies that systematically correlate MES features
—
such as those illustrated in
(
Fig.1
)
—
with specific cGMP requirements (21 CFR Part 211 and global standards). This gap leaves manufacturers
uncertain about the regulatory benefits, implementation challenges, and practical outcomes of MES adoption [12].
Objectives
: This paper aims to bridge this gap by analyzing how MES functionalities align with and support the
stringent requirements of cGMP regulations in pharmaceutical manufacturing. Specifically, it seeks to:
1.
Identify key cGMP requirements under 21 CFR Part 211, supplemented by global standards such as EU GMP
Annex 11 and ICH guidelines.
2.
Map MES features
—
including real-time data capture, electronic batch records, process monitoring, and
audit trails
—
to these regulatory requirements, building on the framework presented in (
Fig 1
).
3.
Evaluate the impact of MES adoption on compliance assurance, operational efficiency, and risk mitigation,
using metrics such as error rates, batch release times, and audit outcomes.
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4.
Propose best practices for implementing MES in a cGMP-compliant manner, addressing barriers such as
cost, system validation, and organizational change management.
The subsequent sections outline a methodology for correlating cGMP regulations with MES capabilities, present
findings from this analysis, and discuss strategies for effective MES implementation. By providing a structured
framework, informed by the visual mapping in (
Fig.1)
, this study aims to demonstrate how MES-driven automation
enhances regulatory compliance, reduces operational inefficiencies, and mitigates the risk of costly regulatory
citations, offering actionable insights for pharmaceutical manufacturers seeking to modernize their operations.
MES Core System
Equipment Management
Cleaning and Maintenance Log
(21 CFR 211.182)
Process Control
SOP Enforcement
(21 CFR 211.100)
Personnel Qualification
Training Verification
(21 CFR 211.25)
Component Charge
Material Accuracy
(21 CFR 211.101)
Record Keeping
Electronic Batch Records
(21 CFR 211.188)
Figure 1
: MES Integration with cGMP Requirements
–
A block diagram illustrating how MES functionalities map to
specific 21 CFR Part 211 subparts for comprehensive compliance.
2.
Methodology
2.1 Materials
To address the challenges in pharmaceutical manufacturing and ensure compliance with regulatory standards, a
comprehensive approach involving regulatory documentation, advanced Manufacturing Execution Systems (MES),
and computational tools is essential. Regulatory documentation forms the foundation for compliance, with
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resources such as the
GMP Compliance and MES.docx
providing a compiled overview of cGMP highlights and
requirements, detailing critical aspects like personnel qualifications, documentation protocols, and process controls
[8]. Complementing this, the FDA’s 21 CFR Part 211 guidelines on pharmaceutical manufacturing outline
the legal
framework for ensuring product quality, safety, and efficacy through stringent requirements for equipment
maintenance, batch record management, and quality assurance [5]. These documents collectively serve as a
benchmark for manufacturers to align their operations with regulatory expectations [13]. MES platforms play a
pivotal role in operationalizing these regulatory requirements by digitizing and automating manufacturing
processes. Proprietary MES systems, such as Emerson’s Syncade, Siemens Opcenter, Rockwell Automation’s
PharmaSuite, and SAP MES, offer robust features tailored to pharmaceutical needs, including real-time process
monitoring, electronic batch records (eBR), and audit trails, which enhance traceability and compliance with cGMP
mandates [7]. For manufacturers seeking flexibility, open-source or modular MES solutions provide viable
alternatives, focusing on key functionalities like traceability, process control, and batch record management,
enabling scalability while maintaining regulatory adherence [12]. These systems integrate with enterprise resource
planning (ERP) platforms, ensuring seamless data flow and operational visibility across the production lifecycle [15].
Supporting these MES platforms, computational tools are critical for data analysis and secure recordkeeping.
Statistical software such as Minitab and R enables manufacturers to analyze quantitative data on compliance
deviations, identifying trends and process variability to ensure adherence to cGMP requirements for process
validation [10]. Additionally, document management systems and e-signature solutions bolster data integrity by
providing secure recordkeeping mechanisms, aligning with 21 CFR Part 11 requirements for electronic records and
signatures through features like access controls, audit trails, and encryption [3,17]. Together, these tools and
systems provide a comprehensive framework for pharmaceutical manufacturers to achieve regulatory compliance,
improve operational efficiency, and mitigate risks associated with manual processes [9].
2.2 Methods and Procedures
The methodology for this study began with a targeted literature review of cGMP requirements, focusing on key
areas prone to compliance issues, including Quality Control Unit responsibilities, equipment cleaning and
maintenance, personnel qualifications, production and process controls, and recordkeeping and reports, as outlined
in the FDA’s 21 CFR Part 211 guidelines, to establish a baseline understanding of regulatory expectations [5,8]. Next,
the study mapped cGMP requirements to MES functionalities, examining how MES supports compliance through
data capture and traceability by automating data entry, reducing manual transcription errors, and maintaining
unique identifiers like batch and lot numbers for raw materials and finished products, a capability highlighted in
studies on digital manufacturing solutions [7]. It also analyzed workflow enforcement, assessing how MES ensures
sequential steps in Master Production Records are followed with timely in-process checks, aligning with cGMP
requirements for production controls [13], and studied audit trails, noting how MES automatically logs user
interactions, parameter changes, and procedure deviations to provide an electronic trail for audits, supporting data
integrity as per FDA guidance [3]. To contextualize these findings, a case study analysis was conducted, investigating
pharmaceutical firms that transitioned from paper-based systems to MES-driven operations, evaluating
improvements in compliance metrics such as the number of deviations, corrective actions, and audit observations,
drawing on documented transitions in the literature [16]. Finally, data analysis was performed, qualitatively
identifying patterns in how MES addresses or falls short of cGMP mandates based on the literature and case studies
[1], and quantitatively reviewing documented evidence where available, such as faster batch release times, fewer
documentation errors, and improved data integrity following MES implementation, as reported in industry analyses
[18].
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3.
RESULTS AND DISCUSSION
3.1
Integration of MES with GMP Requirements
3.1.1
Equipment Cleaning and Maintenance
Under cGMP requirements for equipment cleaning and maintenance, as stipulated in 21 CFR Part 211, records
must be maintained for maintenance, cleaning, sanitizing, and inspection activities; however, traditional
paper-based logs often suffer from incompleteness or inconsistency [5]. MES platforms address this
challenge through built-in asset management modules that automate the scheduling and recordkeeping of
all cleaning and maintenance procedures. The study’s findings indicate that these automated maintenance
logs significantly reduce data entry errors and ensure that equipment is not used beyond its recommended
service interval, thereby mitigating risks of cross-contamination [7].
3.1.2
Personnel Qualifications
Under cGMP requirements, as outlined in 21 CFR Part 211, all personnel must possess the necessary education,
training, and experience for their assigned duties [5]. MES systems support this mandate by integrating with
Human Resource (HR) databases to verify operator competencies in real time, restricting access to specific
processes to only those who are qualified. The study’s findings show that this mechanism enhances both
compliance and quality by preventing unauthorized or untrained personnel from handling critical operations,
thereby reducing the risk of errors [13].
3.1.3
Production and Process Controls
Production and process controls, a core component of cGMP as per 21 CFR Part 211, mandate strict adherence
to procedures to ensure consistent product quality [5]. MES supports this by digitally enforcing procedures
through presenting Standard Operating Procedures (SOPs) during production steps, prompting operators to
record critical process parameters in real time, and issuing alerts for deviations with instant notifications sent
to the quality control unit (
Fig.2
). The study’s findings indicate that these real
-time alerts and digital
instructions significantly reduce the risk of oversight, ensuring consistent production quality across batches
[7].
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Production Start
MES Display SOPs
( e.g. Mixing Step)
Operator Enters Parameters
(e.g., Temp:25°C)
Parameters Within Specs?
(20-30 °C)
Next Step Initiated
Alert Sent to QC
Batch Completed
Deviation Logged
(21 CFR 211.100)
Yes
No
Audit Trail Entry
Figure 2
: MES Workflow for Production Control
–
A flowchart showing MES’s enforcement of SOPs,
parameter validation, and deviation handling in real-time.
3.1.4
Automated Charge-In of Components
Under cGMP requirements outlined in 21 CFR Part 211, each component added to a batch must be accurately
weighed or measured, with specific labeling and verification to ensure precision [5]. MES facilitates this by
integrating with automated dispensers and barcoding systems, ensuring that each component is precisely
measured while automatically capturing all relevant data, such as date, time, and operator ID. The study’s
findings reveal that this automation significantly reduces mix-ups or mislabeling, and the traditional second
operator verification step can be replaced with electronic checks, thereby increasing operational efficiency
[7].
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3.1.5
Recordkeeping and Reports
cGMP, as specified in 21 CFR Part 211, mandates meticulous recordkeeping, encompassing batch production
records, distribution records, complaint files, and more, to ensure traceability and accountability [5]. MES
addresses this by consolidating all documentation into a secure electronic repository, maintaining real-time
data and e-
signatures to confirm actions. The study’s findings demonstrate that digital recordkeeping
accelerates batch release by making all production data immediately accessible for review and approval,
thereby minimizing the need for manual reconciliation and enhancing efficiency [18].
3.2
Automated Validation and Verification
Validation and verification are critical under cGMP to ensure that both the manufacturing process and associated
systems like MES function as intended, a process traditionally reliant on extensive paper documentation and manual
cross-checking [5]. MES enhances this through automated protocol execution, guiding operators step-by-step
through validation protocols while capturing data in real time, and enabling electronic approvals with e-signatures
and automatic date/time stamps to confirm each step, thus facilitating swift audits. Additionally, MES supports
continuous monitoring post-validation by tracking production parameters and triggering alerts if they deviate from
validated ranges. The benefit of this automation is a significant reduction in human error, an accelerated
qualification cycle, and a clear electronic trail of approvals and test results, improving overall compliance and
efficiency [7].
3.3
Data Integrity Assurance
Data integrity is a cornerstone of cGMP regulations as per 21 CFR Part 211, and in an MES environment, every user
action
—
such as data entry, parameter adjustments, or material additions
—
is recorded and time-stamped to ensure
traceability [5]. MES enhances this through access controls, implementing role-based permissions to ensure only
authorized personnel can edit or approve records, and version control, which maintains histories of manufacturing
instructions to prevent the accidental or unauthorized use of outdated procedures. Additionally, comprehensive
audit trails log all system interactions, enabling quick detection of anomalies or deviations (
Fig.3
). The benefit of
these features is that real-time data validation and secure, tamper-evident audit trails align with cGMP
requirements for accuracy, consistency, and completeness, significantly strengthening compliance [3].
Secure Output
Examples: EBR Signed, Blockchain Hash Generated
Access Control
Role-Based Login (e.g., Operator vs QA)
Version Control
SOP v2.1 Locked, v2.0 Archived
Audit Trail
Log: User Jsheth changed temp at 09:15.
Raw Data Inputs
Examples:
Operator Entry:
Sensor Data: Pressure 1.2 bar
Batch ID 1234
ALCOA+ Compliance
Figure 3
: Data Integrity in MES
–
A layered diagram depicting how MES ensures ALCOA+ compliance through
secure data handling and logging.
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3.4
Quality Management System (QMS) Integration
A holistic approach to pharmaceutical manufacturing often incorporates a separate Quality Management System
(QMS) to manage deviations, corrective and preventive actions (CAPA), complaints, and change control, ensuring
compliance with cGMP standards [5]. Integrating MES with QMS provides significant advantages, including a single
source of truth where production data from MES automatically populates QMS records for deviations or CAPA
investigations, streamlined deviation management by allowing deviation reports triggered in MES to flow directly
into QMS workflows for faster resolution, and harmonized change control, where approved changes in QMS
automatically update relevant MES procedures to align with current SOPs (
Fig.4
). The benefit of this seamless MES-
QMS integration is accelerated root-cause analysis, ensuring that production and quality teams operate with
unified, up-to-date information, thereby enhancing overall compliance and efficiency [1].
MES
QMS
Production data Captured
(e.g., Temp Deviation 32 °C)
Deviation Flagged
CAPA Initiated
(ID: CAPA-001)
Root Cause Analyzed
(e.g., Heater Malfunction)
Change Approved
(e.g., New SOP v3.0)
Data Transfer
(e.g., Deviation
Details)
Updated Procedure
(e.g., SOP v3.0
deployed)
Unified Database
Figure 4
: MES-QMS Integration
–
A process flow showing bidirectional data exchange for deviation management
and procedural updates
3.5
Regulatory Reporting and Documentation
Regulatory bodies, as noted in FDA guidance, increasingly accept or prefer electronic documentation for
inspections, provided the systems meet data integrity requirements outlined in 21 CFR Part 11 [3]. MES facilitates
this shift by enabling the automated generation of compliance reports, such as batch records, cleaning logs, and
deviation summaries, in standardized formats, and supporting digital submission through secure electronic files
that can be sent directly to regulators, saving time and resources. Additionally, MES provides instant traceability,
allowing investigators to trace each batch’s history from material receipt to finished product within a centralized
interface. The benefit of this streamlined regulatory reporting is a reduced administrative burden, enhanced
transparency, and shortened audit times, improving overall compliance efficiency [7].
3.6
Training and Competency Tracking
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MES can enhance personnel training by incorporating training modules or linking to a Learning Management System
(LMS) to monitor training and certification, ensuring compliance with cGMP requirements for qualified staff as per
21 CFR Part 211 [5]. This includes role-based training, where operators access only modules relevant to their roles
for focused learning, competency validation, where MES ensures users pass necessary training exams or
certifications before granting system privileges, and automated reminders and requalification, notifying staff when
retraining or requalification is due to prevent lapses in compliance. The benefit of this system-enforced training is
that it ensures only competent, up-to-
date personnel participate in production, directly aligning with cGMP’s
requirement for properly qualified staff, thereby enhancing compliance and operational quality [13].
3.7
Risk-Based Automation
A risk-based approach in pharmaceutical manufacturing, as encouraged by ICH Q9 guidelines, tailors automation to
maximize impact on compliance and product quality, recognizing that not all processes require the same level of
automation [2]. This involves critical process identification, where high-risk steps like component weighing or sterile
transfers benefit most from automation and real-time monitoring, scalable implementation, allowing lower-risk
areas to use partial automation or remain manual if justified by a robust risk assessment, and dynamic risk profiles,
where MES uses real-time data to update risk levels and adjust control strategies as needed (
Fig.5
). The benefit of
this approach is optimal resource allocation, enabling manufacturers to maintain compliance by prioritizing high-
risk processes without overcomplicating less critical areas, thus enhancing efficiency and effectiveness [1].
Figure 5
: Risk-Based Automation in MES
–
A bar chart showing automation prioritization based on ICH Q9 risk
scores for key processes.
3.8
Continuous Improvement and AI Enhancement
The concept of continuous improvement (CI), a key principle in quality manufacturing as per ICH Q10 guidelines, is
enhanced by MES through the accumulation of data, which enables advanced analytics and AI to uncover process
inefficiencies and quality trends [2]. This includes predictive maintenance, where AI-driven insights on equipment
performance trigger preventive maintenance to reduce downtime and quality deviations, process optimization,
where machine learning algorithms analyze historical batch data to refine process parameters for improved yield
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and consistency, and real-time decision support, where AI-powered MES dashboards provide operators with
suggestions or alerts to minimize deviations (
Fig.6
). The benefit of leveraging AI within MES is the fostering of a
culture of ongoing improvement, extending beyond basic compliance to enhance overall operational excellence in
pharmaceutical manufacturing [1].
MES AI System
Data Collection
Batch Data (e.g., Yield
98%), Equipment Logs
AI Analysis
ML Model (e.g.,
Predict Failure at 500
hrs)
Predictive Insights
Alert: Maintenance
Due in 24 hrs.
Process Adjustment
Update: Increase Temp
to 26 °C .
Feedback Loop
Feedback Loop
Feedback Loop
Feedback Loop
Figure 6
: AI-Driven Continuous Improvement in MES
–
A circular flowchart illustrating how AI processes MES data
for predictive and adaptive enhancements.
4
Limitations and Challenges
Despite the clear benefits of MES in enhancing GMP compliance, several limitations and challenges must be
acknowledged. The transition from paper-based systems to MES-driven operations requires significant initial
investments in software, hardware, and infrastructure upgrades, which can be a financial burden, particularly for
small to medium-sized enterprises [9]. Additionally, comprehensive staff training is essential to ensure users are
proficient in the new system, adding to the overall cost and time required for implementation [12]. System
validation, as per GAMP 5 guidelines, is another critical challenge, as it demands rigorous testing and
documentation to ensure MES meets regulatory standards, further increasing complexity and resource demands
[6]. Cultural resistance to change poses a significant hurdle, as employees accustomed to manual processes may be
hesitant to adopt digital workflows, necessitating structured change management strategies, including stakeholder
engagement, phased rollouts, and ongoing support to facilitate a smooth transition [9]. Moreover, ensuring
uninterrupted compliance during the implementation phase is challenging, as any disruptions or errors during the
rollout could lead to regulatory non-conformance, potentially attracting scrutiny from bodies like the FDA [16].
Finally, while MES offers robust data integrity features, the integration of emerging technologies like IIoT and cloud-
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based platforms introduces new risks, such as cybersecurity threats and data privacy concerns, which must be
carefully managed to maintain compliance with global regulations [12]. Addressing these challenges requires
careful planning, adequate resource allocation, and a proactive approach to risk management to fully realize the
benefits of MES in pharmaceutical manufacturing.
5
CONCLUSION
This paper emphasizes the transformative role of Manufacturing Execution Systems (MES) in modernizing and
reinforcing Good Manufacturing Practice (GMP) compliance within the pharmaceutical industry, addressing the
inherent limitations of manual documentation systems. MES achieves this by enabling real-time data capture for
accurate production activity recording, enforcing workflow integrity to ensure adherence to standardized
procedures, and providing robust audit trails that create a tamper-evident record of all user actions, aligning with
stringent regulatory expectations such as those in 21 CFR Part 211 [5,7]. The comprehensive framework introduced
in this study integrates advanced strategies to enhance compliance and operational efficiency. This includes
automated validation to streamline qualification processes, data integrity safeguards like role-based access controls
to meet FDA guidance [3], and seamless QMS integration for unified deviation and CAPA management [1].
Additionally, the framework incorporates streamlined regulatory reporting, training and competency tracking, risk-
based automation, and AI-enhanced continuous improvement to optimize processes and reduce deviations [13,2].
Future research could explore the potential of AI-driven analytics, Industrial Internet of Things (IIoT) integrations,
cloud-based platforms, and blockchain technology to further enhance MES capabilities, particularly in improving
data integrity and scalability [12,18]. By adopting these strategies, pharmaceutical companies can significantly
improve product quality, regulatory readiness, and operational efficiency, ensuring public health safety and
competitiveness in a highly regulated market, where compliance failures can lead to costly penalties, recalls, or
reputational damage [16]. The shift to digital systems also aligns with Industry 4.0 trends, enabling data-driven
decision-making and fostering continuous improvement for long-term sustainability in pharmaceutical
manufacturing [1].
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