All Whitepapers
Seizing the Customer Experience Opportunity in Life Sciences
March 14th 2022To get a better understanding of how technology can power superior customer experiences, Salesforce commissioned research to explore what being customer-centric means for life sciences organizations and technology’s role in building stronger connections among people, data, and processes that ultimately lead to better health outcomes.
Smarter Signal Management: AI, big data, and predictive analytics
February 15th 2022What if you could predict potential safety issues before clinical development begins? Innovative new signal detection and management approaches have been developed to help clinical trial sponsors, manufacturers, and CROs combat safety-related challenges and provide insight to be used to predict potential safety issues even before clinical development begins. Applying those learnings to their choice of initial research candidates can ultimately mean safer medicines for patients.
The Next Domino: Automation, AI, and touchless safety case processing
February 15th 2022With the increasing volumes of adverse event reports and stagnant budgets, the time is now for a revolutionary change in drug and device safety case management. A robust management process is necessary for identifying and evaluating adverse events (AE) and reporting them properly to regulators.
Using ML, AI and RWD to Infer HCP Specialties
October 2nd 2021Pharmaceutical sales operations teams often rely on outdated or inaccurate data when prioritizing HCP targets, limiting promotional effectiveness. By applying artificial intelligence and machine learning to real world data, pharmaceutical companies can more effectively target physicians hiding in plain sight and PCPs behaving like specialists.
Shortening the Rare Disease Diagnostic Odyssey
October 2nd 2021Specialty and rare diseases have undefined patient populations with patients who are undiagnosed or misdiagnosed, healthcare providers who are unaware of disease states and their manifestations, as well as diagnostic and treatment journeys that are not well-understood. By applying artificial intelligence and machine learning to real world data, pharmaceutical companies can improve outcomes at scale.
