How Medical Regulatory and Compliance Space up for disruption with Chat GPT.
Medical regulatory space is quite complex. Building products for clinical, security and data-privacy standards involves enormous effort in compliance.
Let’s go on exploration to see how the space is bound for disruption.
Broad Phases of Compliance, for most standards.
Assessment
Implementation
Certification
Assessment
Medical Product regulation requires knowing what the product should comply to a in a specific country.
Let’s take an example of building blood glucose monitoring device.
Here are the takeaways
Understanding the regulatory policy and classifying the device would have taken an expensive assessment process.
The model is not trained for latest amendments, but the regulation in the space changes at a slow space so should not be a big concern.
The responses need to be expert vetted but provides a very good direction.
Implementation
This is a major area that will see disruption. Here is an interesting experiment that compliancy group ran.
The space currently has several SaaS tools that help manage the entire compliance process. The biggest value add for the tool provides are
Organising the compliance documents. Collecting evidence etc.,
Task Management
The in-accuracy of response stems from non-specific data. It isn’t hard then to imagine a regulatory tool custom trained for a specific regulation to do much better.
With this in place, the primary interface becomes chat for all stakeholders. Chatspot interface is an excellent example for a their Hubspot CRM.
Sitegpt is another excellent example of chatgpt trained on custom website data.
Certification
With more natural language interaction the certification process will also like to happen faster.
There are definitely concerns about
Private data being used to train the models.
Accuracy and traceability of input data.
How do you see the regulatory and compliance landscape changing with adoption of AI and LLMs? Share in the comments.