Abbott and Bio-Rad: How to Build a Trustworthy Foundation for AI in Medtech Regulatory Affairs

Insights from senior leaders at Abbott and Bio-Rad

The rapid evolution of automation in regulatory affairs is redefining how medtech organizations manage global compliance. More medtech regulatory teams are going digital as technology advances. In 2023, only 14% used a digital-first approach; by late 2025 that jumped to 56%. Regulatory leaders recognize that modernizing is urgent; companies that wait may risk falling too far behind to catch up.

To leverage advanced capabilities successfully, organizations must adopt a “dual-mode” strategy—pairing robust enterprise systems of record with downstream AI agents to create a compliant and symbiotic operational model.

Two senior medtech leaders, Brenda Price of Abbott and Elizabeth Platt of Bio-Rad, recently shared their strategic approaches to preparing data, people, and business processes for this new era. This article highlights their insights across three essential pillars.

1. Establish a trustworthy data foundation first

High-value automation requires structured, quality data. Both Price and Platt emphasized that unstructured or siloed data is the primary obstacle to AI success.

“Data cleaning isn’t sexy, but data infrastructure is why AI implementations fail,” says Brenda Price, director of regulatory operations at Abbott. Price notes that managing diverse systems across six different manufacturing sites, many acquired over time, has introduced significant complexity for her team. To prevent “garbage in, garbage out” loops, Abbott focused on standardizing operational data definitions across divisions.

Elizabeth Platt, senior vice president of global quality, regulatory, and clinical affairs at Bio-Rad, shares this same perspective. In preparation for its July 2026 RIM go-live, Bio-Rad spent 2024 consolidating legacy data into a central data lake repository.

“If you build AI on top of data that’s not structured, the foundation’s not good and you won’t get out what you need from it,” Platt says.

By putting in the effort to clean, standardize, and centralize data across enterprise systems, medtech leaders can ensure their operational information is reliable and ready for AI integration.

2. Keep a human in the loop

Operating in a highly regulated life sciences environment means accountability that cannot be outsourced or automated to AI. The industry was reminded of this reality in April 2026, when the FDA issued a landmark warning letter addressing the over-reliance on AI in drug manufacturing. The regulator made it clear: firms cannot abdicate CGMP or regulatory compliance to an autonomous agent.

To avoid similar risk, medtech organizations are developing rigorous governance models that keep a “human in the loop” for all AI-generated outputs.

At Bio-Rad, this governance began with the creation of a specialized focus group named SPARK (Steering Projects with AI Resources and Knowledge). The group pairs regulatory leadership with internal team members who possess advanced expertise in AI.

“Human oversight is more than a slogan; build it directly into your business process,” Platt says. She notes that any business process utilizing AI must include a qualified human reviewer who documents, signs off on, and takes responsibility for the final decision, ensuring a clear audit trail.

Abbott has also established a similar cross-functional governance board that reviews all internal and purchased AI applications to evaluate fit for use, cybersecurity, and data protection.

To build internal competency, Abbott also focuses on elevating employee AI literacy by enlisting AI early adopters to help develop AI solutions for the team’s business use. “Taking those business cases to an internal team, creating the best-in-class prompt you can, and then publishing it to the team gives people a greater sense of safety when using AI,” Price says.

3. Streamline workflows before automating

Before integrating AI, organizations must streamline their underlying workflows. Abbott and Bio-Rad, as well as other industry leaders, are currently targeting several high-value use cases that combine optimized business processes with RIM capabilities.

Global content planning and active dossier: Managing pre- and post-market registrations across more than 170 countries is an incredibly complex matrix. Abbott intends to pilot global content planning to maintain clear visibility into worldwide registration statuses. Price notes that utilizing an AI assistant to match country-specific requirements against submission content helps identify gaps and ensure submission excellence.

Regulatory intelligence: Keeping up with changing regulations globally is traditionally a manual, high-risk process. Bio-Rad identified regulatory intelligence as its top priority to reduce compliance risk. The organization evaluated four different regulatory intelligence systems and is planning to integrate Redica’s offering via an API interface with Veeva RIM, allowing regulatory signals to feed directly into their system of record to support automated impact assessments.

Submission quality and query resolution: Medtech teams are exploring AI capabilities to screen historical submission data, predict health authority questions, and draft high-quality responses based on past, successful interactions.

Steps to take today

The path forward does not require waiting for fully autonomous AI. Regulatory leaders can take practical steps today to prepare their organizations.

Establish cross-functional governance: Form a taskforce that aligns IT, regulatory, and quality leadership to review AI use cases and enforce data protection standards.

Standardize and clean data: Treat data readiness as a continuous priority. Audit current databases, establish clear operational definitions, and leverage centralized data repositories.

Target high-value pilots: Focus initial efforts on defined business needs, such as integrating regulatory intelligence or utilizing global content planning tools, to demonstrate tangible value and build internal trust.

By establishing a connected enterprise platform with human oversight, medtech organizations can successfully navigate the shift to advanced regulatory intelligence and future AI adoption.

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Disclaimer: Views expressed by Drs. Price and Platt in this article are those of the employees only and do not necessarily reflect those of Abbott or Bio-Rad.