Adopting an AI-driven approach for mid-size pharma to meet regulatory expectations and scale with confidence

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Michelle Gyzen, Senior Director of Strategic Regulatory Solutions, IQVIA, explores how mid-size pharma can meet European regulatory expectations without rebuilding infrastructure.

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Across Europe, mid-sized pharmaceutical companies face the same regulatory expectations and development timelines as their larger incumbents, yet leaner teams and fragmented systems can make execution difficult. These imbalances slow submissions, stretch internal resources and increase operational risk, particularly around clinical, regulatory and operational functions that lack consistent alignment. Outside of these challenges, disparate data and manual workflows can add layers of stress. This forces teams to spend valuable time reconciling information instead of advancing development.

At the same time, regulators continue to raise expectations surrounding data integrity, documentation quality and inspection readiness, all while organisations face growing volumes of content and a need to coordinate information across multiple countries. In 2025, the European Commission issued draft updates to the EU Good Manufacturing Practices Chapter 4,¹ which oversees documentation, and Annex 11,² which governs the use of computerised systems in pharmaceutical manufacturing and regulatory operations.

For mid-sized pharmaceutical teams working across disconnected tools, each new programme adds complexity and increases the likelihood of rework. These pressures force companies to rethink how they approach regulatory operations, moving away from reactive approaches towards models that support consistency and scalability.

Moving beyond point solutions towards integrated execution

One approach to overcoming regulatory burdens is to hire additional staff or introduce new tools to address immediate gaps; however, this method rarely leads to lasting improvements. Point solutions often create new silos, increase handoffs between teams and restrict visibility throughout the development lifecycle, ultimately undermining efficiency.

The future of mid-size pharma depends on its ability to balance agility with operational discipline as pipelines expand and regulatory expectations evolve”

For example, lifecycle management activities such as labelling updates, tracking system maintenance and license renewals are frequently distributed among multiple authorities, platforms and functions. Teams are then forced to reconcile documentation, submissions and interactions spread out over disparate systems. A more effective strategy focuses on connecting and streamlining data, workflows and decision-making within a unified model that encompasses all operational functions.

With better alignment in these processes, mid-sized pharmaceutical companies can mitigate points of friction and improve execution of valuable tasks through coordinated action. By streamlining and connecting data sources, the foundation for regulatory operations and pipeline growth becomes scalable.

Embedding AI into regulatory workflows

One of the most powerful tools that mid-sized pharmaceutical organisations can now leverage is AI. According to McKinsey,³ 75 to 85 percent of workflows contain tasks that could be enhanced or automated by agentic AI, freeing up to 40 percent of an organisation’s capacity. From a regulatory operation perspective, AI is bridging data to platforms that support authoring, regulatory intelligence and submission planning. This bridge between data and action enables teams to identify potential issues before they have a chance to halt development. AI-empowered teams can ultimately make more informed decisions throughout the submission process.

An AI-embedded approach evolves how regulatory teams operate daily. Repetitive, time-consuming tasks can be automated while intelligent systems identify obscure insights, giving professionals the ability to focus on strategy and risk assessment. AI is a powerful tool that unlocks the ability for firms to gain speed without sacrificing quality or oversight. Other areas where mid-size companies typically see impact are:

Regulatory submissions: AI assistants can automate regulatory and clinical content. This co-authoring capability helps teams develop smarter submission strategies that shorten document development cycles while keeping professionals integrated into review and validation processes.
Data integration and transparency: by eliminating silos, clinical, regulatory and operational teams gain greater visibility into various pools of data.
Compliance without breaking the budget: mid-sized pharmaceutical companies that utilise intelligent workflows can meet evolving European and global expectations without building large internal teams.

Strengthening data integration while maintaining inspection readiness

By breaking down silos of information into one integrated environment, mid-sized pharmaceutical teams gain visibility of operational metrics without the constant requirement to reconcile multiple sources or track versions manually. It supports faster decision making and stronger cross-functional alignment. This hub of information and automated traceability further simplifies inspection preparation by maintaining clear and consistent records across regions.

As a result, teams are not reacting with haste to the threat of an audit, because readiness is included in operations. During inspections or scientific advice interactions with the European Medicines Agency or other regulatory bodies, teams can efficiently provide controlled documentation and trace lifecycle changes, such as labelling updates or CMC variations. This allows mid-sized pharmaceutical teams to demonstrate end-to-end data integrity without manually consulting multiple sources of truth. This approach reduces disruption during inspections and builds confidence with regulators by demonstrating consistent governance and transparency across development activities.

Preserving human oversight while embracing automation

Advanced technologies like AI do not deliver regulatory success. The keys to success are still found in the hands of experienced professionals who provide judgment, oversight and contextual understanding that automation cannot replace. These professionals are essential for tasks like validating output or aligning with regional standards.

Companies that synchronise intelligent automation with strong regulatory leadership create a balance between efficiency and accountability”

Collaboration between experienced professionals and technology establishes trust and confidence with regulators by demonstrating responsible and transparent use of advanced capabilities. It ensures regulatory decisions remain grounded in expert interpretation, even as automation accelerates execution.

Building a foundation for long-term growth

The future of mid-size pharma depends on its ability to balance agility with operational discipline as pipelines expand and regulatory expectations evolve. Manual processes that rely on outdated, fragmented systems cannot support scalable development. Conversely, integrated platforms and AI-enabled workflows establish a foundation for consistent execution and growth across programmes and geographies. The ability to compete against larger organisations no longer requires extensive infrastructure investment, but rather coordinated teams empowered by connected data and intelligent automation.

By implementing a modernised, AI-driven approach, mid-sized companies can accelerate their submissions, enabling them to embrace compliance and scale with confidence, all while preserving the flexibility that defines them.

Meet the author

Michelle-Gyzen

Michelle Gyzen

Michelle Gyzen is Senior Director of Strategic Regulatory Solutions, IQVIA, where she designs strategic solutions for regulatory compliance, with a focus on operational efficiency, scalability and technology. Michelle has more than 20 years of experience in the pharmaceutical, biotech and medical device industries. She is a senior director with expertise in designing large-scale regulatory outsourcing programmes, offshore resource modelling and regulatory tech integration and automation.