As shared in Part 2 of this blog series, real-time, simplified regulatory decision making will be enhanced by Regulatory analytics, informatics and robotic automation, whereas natural language processing (NLP), machine learning and data mining will drive much-needed improvements in data quality and improvements in data integrity between documents and databases.
That, in turn, means more time can be freed up for important activities such as finding innovative ways to get treatments faster to patients and ensuring no harm is done to patients with faster implementation of required changes to labels.
The Starting Conditions Are in Place to Drive Success
One of the barriers to adopting the new technologies has been the ‘speed of change’ of existing technologies (e.g., eCTD) and lack of global standardization (e.g., IDMP – SPOR). Generally speaking, the regulatory industry likes the idea of new technologies but remains sceptical that technologies can be easily implemented in the complex global regulatory environment.
The regulatory landscape is slowly but surely evolving with increasing telematics demands driven in Europe by initiatives like the Common European Submission Platform (CESP), the clinical trial portal, and SPOR, and in the US with the FDA’s next five-year plan, post PDUFA V. More countries are taking on electronic submissions (eCTD,) impacting all regulatory functions. eCTD 4 is on the horizon, requiring more change. With increasing focus being placed on data exchange (EVMPD, SPOR and SPL post-PDUFA V), driven by standardization, there is a clear move away from a traditional document focus to data management. With pharma companies seeking productivity gains within this expanding and changing regulatory environment it is time to embrace a different paradigm.
The reality is automation has come a very long way and is well entrenched in our lives in ways we may not realize. These systems are being used in facial recognition in mobile phones, in chatbots for customer service, for estimation of real estate prices, and for providing movie recommendations on Netflix. In medicine, they are being used in cancer diagnosis and treatment, and have been proven to be better than experts alone in identifying malignancies from medical scans.
The starting conditions for Regulatory Analytics & Informatics and automation to successfully transform Regulatory work are in place:
- The ‘new’ technologies are here; automation is coming
- A global standardization project is in place with IDMP (SPOR)
- Simplification and standardization is happening across the regulatory domain
- Collaboration is in place with all stakeholders to realize benefits for all
- New capabilities are emerging / will be required to drive value
The life-sciences industry realizes the massive potential of the new technologies and embracing these in regulatory, within end-to-end management of day-to-day activities, will begin to differentiate the early adopters.
We hope you found this regulatory blog series enlightening. We encourage you to listen to the full webcast broadcast for more comparisons and insights to how automation is coming to life in Regulatory today. Click here to view the on-demand webcast.