How Digital Maturity is Powering Pharma's GMP Evolution

In an exclusive interview with Thiruamuthan, Assistant Editor at India Pharma Outlook, Sandeep Raktate, President - India & Ireland Operations, Amneal Pharmaceuticals, discusses how Indian pharmaceutical companies are adopting digital platforms, IoT, AI, and integrated quality systems to transform day-to-day operations. He also explains that these technologies help prevent compliance lapses and improve operational reliability across plants. Sandeep is an experienced operations executive with over two decades in manufacturing, automation, digitization, and project management, driving operational excellence across global pharmaceutical organizations. 

As India’s pharma sector tightens its compliance framework, how are companies leveraging digital maturity to meet evolving GMP norms and global audit expectations?

Many companies are now using digital platforms to convert regulatory pressure into operational advantage. This means shifting from reactive, paper-based evidence to continuous, auditable digital compliance, and it increasingly includes tools like MEAS or EVMR to enforce step-by-step executions.

A major and important part of this process is the audit trail, such as how we integrate the LIMS and QMS into a single source of data, whether it is a batch record or a quality record, and how we deploy this centrally as a dashboard to ensure role-based access and demonstrate data integrity. Essentially, it is also about contemporary entry and governance during audits.

All of these efforts are driving tighter enforcement to meet the highest standards. It is no longer an option to avoid this approach, so it has become essential. As a leader, I believe we need to fully run through the program to eliminate excessive paper use, establish critical controls on process and quality aspects, and integrate everything together in a way that shows the regulator a single, one-page digital compliance map for inspection.

Also Read: Why Global Pharma Expects CDMOs to Be Ready for Joint Inspections

With data integrity lapses drawing regulatory scrutiny, which digital tools are proving most effective in ensuring traceability and real-time GMP documentation accuracy?

The most effective tools and patterns for ensuring operational and regulatory compliance are as follows. First, MES, the Manufacturing Execution System—also referred to as EBMR or EDPR—plays a critical role by capturing the operator state, time stamps, signatures, and machine data in a single electronic batch record. Second, LIMS is utilized for all quality control analysis, including sample assays, chain of custodial records, and chromatograms.

Third, the QMS system with integrated Kappa and deviation workflow provides essential oversight and process control. Fourth, IoT and SCADA, along with SCADA compliance, are highly important, and maintaining online backups ensures continuous transcription, environmental monitoring, and preservation of other critical records. Next, imageable logging and blockchain-based record groups further enhance traceability and data integrity.

Finally, automated data integrity controls are implemented to maintain compliance at all levels. Collectively, these tools and systems are designed to meet AlcoaPlus expectations and support a robust, digitally governed operational environment.

As hybrid manufacturing models expand across Indian plants, how are digital systems bridging quality control gaps between contract and in-house GMP operations?

The digital systems serve to bridge the hybrid model by creating a common language for data and components. In this context, standardized digital SOPs and EBMR templates enable consistent implementation within the software, while at the same time, robust data management—including cloud and on-premise architecture—ensures proper capture, storage, and handling of information.

Moreover, master data governance and digital recalculations play a critical role, supported by the selection of appropriate partners to maintain effective data oversight. In addition, digital contract and audit portals centralize supplier audits, particularly for vendor management, thereby providing clear visibility into gaps and corrective actions.

As a result, this approach ensures a seamless relationship across operations, quality, and critical data, with all digital batch records captured within a single portal, ultimately enhancing efficiency, traceability, and regulatory compliance.

Given the surge in export-focused production, how are pharma firms applying predictive analytics to prevent deviations and maintain GMP consistency across multi-site facilities?

IoT tools are increasingly important for enabling predictive insights and proactive interventions. To begin with, advanced IoT systems allow monitoring of parameters such as temperature, relative humidity, and particle counts, triggering notifications and escalations to QA while simultaneously recording actions.

This proactive approach is critical to prevent risk-based situations before they occur. Furthermore, anomaly detection on process signatures provides an early warning for critical processes, helping to avoid operational deviations or failures. Equally important, predictive maintenance is essential for critical equipment, as sensors monitor temperature and vibrations, providing indications for maintenance actions, such as bearing replacements, to prevent equipment failure.

Finally, cross-site benchmarking leverages APIs and baseline data to compare performance across different sites or operations, offering a clear understanding of current status and progress relative to established standards. Collectively, these tools enhance operational efficiency, ensure process reliability, and support risk mitigation across the organization.

Also Read: Patient Twinning and Its Impact on Clinical Decision-Making

With MES, LIMS, and IoT integration gaining traction, what barriers continue to limit full digital adoption in GMP-critical environments among mid-tier Indian manufacturers?

Digital solutions offer significant advantages, although certain challenges may arise depending on an organization’s IT, OT, and IoT structure. One key consideration involves legacy equipment and fragmented IT systems, as many plants rely on point solutions that are not fully integrated across the network.

Another significant aspect is skill, talent, and change management; successfully implementing digital transformation requires careful oversight of organizational change, supported by personnel with the right expertise. This includes data scientists, data analysts, and validated CSV professionals to meet regulatory and operational requirements. It is also vital to consider validation and regulatory compliance, particularly with respect to CSV and inspection readiness for digital systems. Attention must also be given to fostering a strong data culture and robust governance, ensuring that information is properly managed, accessible, and actionable.

A further consideration involves connectivity and cybersecurity, where a resilient digital architecture and proactive security measures are essential to mitigate potential risks. Collectively, addressing these factors is critical to maximizing the effectiveness of digital solutions while maintaining compliance, operational integrity, and organizational resilience.

Looking ahead, how will AI-driven quality systems and digital twins redefine GMP benchmarks and reshape regulatory expectations across India’s next-generation pharma facilities?

AI and generative intelligence (GNI) are becoming integral to all industries, including pharmaceuticals. Significant opportunities exist for AI and GNI in pharma; however, the impact depends on how day-to-day operations, business processes, and quality management systems are designed and implemented. This shift enables the transition from retrospective quality assurance to prescriptive quality assurance. AI-enabled quality management systems can analyze batch records and regulatory inspection findings, deriving insights such as root cause analyses and process improvements from internal and external data.

Another critical application involves digital twins, which allow simulation of process changes or control strategies, accelerating inspection readiness and operational optimization. Additionally, there is increasing emphasis on continuous verification, as regulatory expectations evolve rapidly. In this context, process parameters (CPP) and critical quality attributes (CQA) can be managed through AI- and ML-based model governance, aligned with new regulatory artifacts, guidance, and model validation requirements, including data leniency considerations for machine learning.

To support these initiatives, organizations should establish dedicated AI and digital twin governance cells. This approach forms part of overall quality management maturity and continuous improvement. It involves identifying critical data capture points, leveraging IoT platforms, and generating proof-of-concept case studies through systems such as EBMR or LIMS. Governance should encompass enterprise-wide data integrity and AI policies, including CSV and ML validation. Additionally, selecting appropriate partners and use cases is essential to maximize the impact of digital transformation and ensure successful AI adoption in pharmaceutical operations.