This founder built a simulation platform for FDA submissions

^{A week in AI is like a year in other industries. I hope these issues become your weekly source of AI information, inspiration, and ideas. If we haven’t met before, I’m Amanda Smith. I write about AI and the fascinating folks who are building in this brave new world.}

Good morning. I’m always blown away by the range of AI innovation. While the landscape is becoming oversaturated, there are still pockets of opportunity. This week’s founder story is one such example. 

Let’s jump in.

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Srividya Narayanan is a dentist-turned regulatory affairs specialist, who moonlighted as an AI builder while working for a medical device company. Having come into the regulatory space as a clinician, she was well aware of the leap required to speak in regulatory language – and wanted to help ease that journey for others. 

Narayanan’s idea was to build an AI simulation regulatory platform she describes as “the GitHub of Regulatory Affairs.” Having just finished her Master of Science at Northeastern University, Narayanan noticed a need to add a practical experience to the theoretical concepts – whether for students or early-stage professionals. 

Narayanan’s platform, ReguTron, allows users to build regulatory submissions across medical devices, drugs and biologics, through hands-on workflows, realistic case scenarios, and FDA feedback. Users can experiment with a hypothetical company and talk to the chatbot as a regulatory affairs specialist planning to complete a submission for FDA approval on that particular device. 

The model is trained on guidance documents from various government agencies, so it’s able to provide FDA feedback on mock submissions. “It’ll tell you how to respond to any deficiencies, so that you can practice within the platform. At the end, users get a certification of completion of that particular case scenario, which can be added to a resume or LinkedIn,” Narayanan said. 

Given Narayanan’s connections at Northwestern, she leaned on the student population to help build and test ReguTron. The first testing cohort went for three months from January to March 2026, which served as the “to-do list” for cohort two – a small group of 15 regulatory professionals cherrypicked from 200 applications to stress-test the product. 

Their primary target customer is the university. They’ve done demos or are in conversation with Northeastern at the Boston campus, Northeastern Toronto, Long Island University, and Washington University. “Professors are intrigued and say they see the value of adding it within their curriculum,” she said. 

ReguTron operates as a subscription model, with three tiers ranging from $19 – $79 per month. 

Narayanan said engaging the student population is their main marketing approach right now. This includes the university club events, as well as connecting with the faculty in regulatory or experimental learning. 

Beyond students, other target user groups include professionals, job seekers, startups and SMEs. The co-founders use LinkedIn for marketing and lead generation. Future plans include investing in SEO, but she admits “AI simulation regulatory platform” might be hard to rank for as it’s quite novel. 

Going direct is their plan for now, especially with the growth of AI-enabled medical devices she expects to see in coming years. 

“Startup founders who are building these medical devices don’t necessarily have the budget to hire a consultant to do the regulatory work. This allows founders to figure it out on their own, at least in the initial stage of their regulatory submissions to the FDA,” Narayanan concluded. 

If one of these stories stuck with you, I’d love to hear which one.

Speak soon,
Amanda

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