AI in MLR is one of the most talked about terms in pharma right now. We see it in conference programmes and hear about it in speaker decks, but what does it actually mean?
Well, for us at Aithena, AI MLR is the same medical, legal, and regulatory review that pharma has been doing for decades. The difference now is that there are AI technologies that can help with repetitive, technical parts of the process. That's the parts that are slow, painful and if we're honest, are error-prone.
With the AI MLR software, human reviewers can focus on the part that humans do best: applying their judgement. AI MLR doesn't replace the process. It changes the shape of the review.
Anyone who has worked as a reviewer or signatory knows the traditional MLR review process has a hidden problem: inconsistency. Different reviewers interpret the ABPI Code differently. Different companies apply different internal standards. A junior reviewer might miss what a senior signatory would catch. An experienced reviewer coming from one company might apply standards their new colleagues don't recognise.
Of course, none of this is a criticism of reviewers. It's a description of what happens when compliance judgement is spread across a network of people, each with their own history and interpretation of the same rules. AI MLR closes that gap. When the same underlying set of compliance frameworks and code checklists is applied to every piece of content, in the same way, every time, variability drops.
AI MLR shifts what the reviewer's job focus is. In the current way of doing things, a lot of a reviewer's time is spent hunting for details. Whether that's cross-referencing claims against the SmPC, checking dosing information against the latest label or verifying that every promotional statement is substantiated by an approved reference.
In an AI MLR workflow, AI does that hunting. It surfaces the details, the references, the potential inconsistencies. The reviewer applies nuanced and situational judgment and make decisions. So where does this leave the current and next generation of reviewers?
For us at Aithena, the trajectory is upwards and exciting. The MLR review process as we know it, will compress over time. Faster reviews and more consistency across the industry.
What won't change is the need for final human sign-off. Any serious AI MLR platform is built with the human in the loop in mind. And not just because regulators require it, but because compliance judgement is what people are good at, and AI is not (and isn't meant to be).
Aithena's AI MLR platform MLRcle helps life science and pharma teams compress MLR review cycles from weeks to days, without compromising on quality. It handles the technical checks (as well as multiple other checks) so reviewers can focus on the judgement work.
That should be the real promise of AI MLR: not less compliance but better compliance. Not less reviewers but more reviewers doing better work.
