Implementing artificial intelligence (AI) and machine learning technologies to process big data sets has led to faster analysis of clinical trial data, identification of RWE gaps and the agile generation of evidence to meet HTA and other stakeholder requirements. So, under the cloud of COVID-19 and the growing demands of multiple stakeholders for evidence of utility and value, what’s next for advanced AI analytics and big data and what are the key trends market access planners should be following?
To examine this critical area of pharma’s business, we interviewed pharma and market access experts. In this detailed first-hand report they reveal the applications and strategies that are delivering clinical, operational and commercial wins across the market access spectrum. Learn from what they said in Big Data and AI in Market Access.
Experts explore key questions
- In what areas are pharma innovatively utilizing big data and AI to influence their clinical and commercial market access strategies?
- To what degree has AI impacted comparative effectiveness/RWE data analytics in respect to pricing and reimbursement decision making?
- How are pharma using multimedia big data to profile, target and engage with KOLs/Rx influencers, pharmacies and payers?
- In what ways is AI being applied by payers for assessing the potential cost effectiveness of a drug and to determine its long-term budget impact?
- What are the key AI and big data lessons pharma need to learn to effectively build, communicate and deliver value to key market access influencers and decision makers?