White Paper: AI-Powered Real-World Evidence Generation

By Philipp Cimiano

Improving Pharma’s Ability to Focus on the Needs of Key Stakeholders

Executive Summary

Success in the pharmaceutical industry is about effectively demonstrating value. Product approval is necessary, but not sufficient. A new drug must provide compelling evidence of added benefit over what is already available.

Value demonstration happens formally in the context of health technology assessment and negotiations with payers. As budgets are squeezed, payers are becoming more rigorous, pushing hard to ensure they gain maximum added benefit from new products, at the lowest cost. Market access is now commonly referred to as the “fourth hurdle,” after discovery, development, and approval challenges have been overcome.

Yet this demonstration of value must continue well beyond health technology assessment (HTA) and initial pricing discussions, as a new product is positioned among prescribers, payers, and patients in a real-world clinical setting. Even a product that makes it onto the list of reimbursed therapies needs to actually be prescribed and used in order to achieve commercial success. Understanding the drivers of prescription and of product usage is therefore critical to overcoming what might be considered this “fifth hurdle.”

Pharmaceutical firms need to know how a drug is perceived by those who prescribe it, take it, and pay for it. They require timely insights into how a drug is impacting everyday lives in real-world setting, so that they can help ensure that treatment is appropriately used and delivers maximum benefit, and is optimally positioned relative to competitors. Such “real-world evidence” (RWE) can also help ensure future products are improved in ways that are the most helpful to patients. Indeed, RWE considered more broadly is among the most important forces shaping the future of the pharmaceutical industry.

Semalytix’s data analytics platform provides that real-world evidence. It enables pharmaceutical firms to access the most pertinent and up-to-date information about how their products are viewed and used by patients and practitioners. The platform applies cutting-edge machine reading, natural language processing, and machine learning technology to read through millions of unstructured documents.

This generates action-ready insights about patients’ experiences and outcomes, and about healthcare providers’ treatment considerations around specific conditions. The insights come with humanlevel accuracy, but at machine speed and scale, supporting teams across business development, market research, insights and analytics, health economics and outcomes research (HEOR), and market access and medical affairs.

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Tags: Paper, Semalytix, AI