Intelligent Automation-Led Transformation of Clinical Data Management: A New Solution for a Smarter Biopharma Industry

Biopharma companies find themselves at an interesting crossroads today. Disruptions in the biopharma industry have significantly changed the focus from drugs to the patient. Thanks to the transformation, the new normal expects the value to move away from the historical volumes-based approach to outcomes-based pricing, personalized medicine and therefore, smaller groups, which means elaborate research and better product launches in future. The way forward is to define the patient engagement and focus on the patient experience. This outcome can be achieved only by adopting various digital technologies across automation, artificial intelligence (AI), advanced analytics and beyond. Over the last couple of years, biopharma has seen a sharp increase in the adoption of intelligent automation to gain competitive advantage in the marketplace. Since Clinical Data Management is a data-intensive process, usage of Clinical Business Intelligence tools such as clinical data warehouse can play a critical role in the disease management programs. Clinical Business Intelligence tools will play a critical role in the Intelligent Automation of Clinical Data Automation.This paper delves into the practical automation opportunities in the R&D area specific to Clinical Data Management (CDM) through a value-complexity matrix to arrive at a business case for Intelligent Automation. Given the immense opportunity in this space, the paper is also a “call for action” for active collaboration among key stakeholders working on different aspects of Intelligent Automation, including Business Process Management (BPM), Machine Learning (ML), Conversational Agents, Advanced Process Integration (API), and of course the Robotic Process Automation (RPA). Also, some important areas like Clinical Business Intelligent and extended usage of Semantic Modeling and Knowledge Graph have been identified as the relevant topics for future work.The COVID 19 pandemic has put the need for rapid science and drug development at the core. As multiple biopharma companies either together or individually race to get both a drug and vaccine to the market, the pressure to get the clinical process right and deliver at speed has never been higher.