Regulatory issues are not single mistakes but a culmination of tiny, unmonitored errors. Instead of a final compliance check, bake governance into every step of the process to proactively flag issues as they happen, preventing catastrophic failures down the line.
The FDA has adopted AI systems like ELSA and Halo to review submissions. To achieve a successful review, companies must now match the FDA's capabilities by using their own AI tools, assisted by human experts, to prepare documentation, effectively leveling the playing field.
To create a specialized and context-aware AI, treat it like a new employee. Instead of generic training, "onboard" it by connecting it to the company's specific standards, policies, and templates. This makes the AI's output highly relevant to the organization's unique processes.
The primary bottlenecks in getting MedTech products to market are operational, not scientific. Tasks like reviewing regulations and preparing documentation are so mundane and laborious that they lead to human error and a waste of talent. AI is best suited to solve these operational pain points.
In complex fields like regulatory affairs, selling AI as a standalone tool is insufficient, especially for startups. The winning model combines AI with human support. This "AI-assisted services" approach ensures users get expert guidance alongside technological efficiency, enabling scalability and broader adoption.
General-purpose AI like ChatGPT cannot solve complex, domain-specific healthcare problems. The key to success is specialization. Identify a single, high-friction bottleneck that wastes time and money, and focus all AI efforts on becoming the expert solution for that narrow problem.