Real-world evidence: Why pharma firms are investing

You probably know someone who has trouble controlling their cholesterol levels. Many patients have successfully used statins; however, some patients experience adverse events while taking these medicines and need to try new or different approach to lowering their cholesterol.

These patients and their health care providers need to understand:

  • What is the safest and most effective statin?
  • Is there any evidence to suggest one statin might be more effective for a particular individual than the competitors?
  • What is the most cost effective approach to lowering cholesterol within goal?
  • Which treatment will cause the fewest side effects?

Why all the interest in real-world evidence?

The data needed to answer these questions and derive critical insights exists across the health care and life science industries, but the sheer size and complexity of the data can seem daunting. Real-world evidence provides significant insight into how a drug or drug class performs or is used in real-world medical settings.

The ability to quickly transform real-world data sources such as claims data or electronic medical records (EMR) into evidence can improve health outcomes for patients by helping pharmaceutical firms be more efficient in drug development and smarter in commercialization.

These insights can help biopharmaceutical companies develop better therapies more quickly, provide verifiable evidence for payers and differentiate their brand in the health care market. That provides a lot of value both to the industry and the patients who ultimately experience better health outcomes.

While accessing, exploring and analyzing vast amounts of data sounds complex, the timely generation of real-world evidence is becoming easier thanks to advances in data management and analytics.

Real-world evidence can be less daunting than it seems

Many organizations tend to assume that data presents a major challenge, especially assembling and preparing a variety of data sources for analysis. Certainly, analytic data preparation this is not simple, but these organizations may be underestimating the capability of modern data management tools.

Health care data is often fragmented, but management of structured data has improved. In addition, Hadoop and the related technologies of big data enable large and disparate data sets (structured and unstructured) to come together for analysis.  In addition, Hadoop and the related technologies of big data enable large and disparate data sets (structured and unstructured) to come together for analysis.


Real World Evidence: 10 Benefits for Providers, Payers and Pharma (click each slide to open)

  • Determine outcomes based on much larger data samples
  • Link data across disparate sources
  • Satisfy payer demands for cost-effective medicines
  • Reduce costs and improve the efficiency of clinical trials
  • Prevent false starts and accelerate time to market
  • Respond faster to adverse developments
  • Increase personalization of drug therapy and treatment
  • Unearth new indications for existing treatments
  • Identify new markets and underserved patient populations
  • Win payer acceptance for expensive new treatments

More rapid time to insight is crucial

The analyses of drug and device performance in actual medical practice can be complex and time-consuming. The analysis may involve iterative cycles of sorting through the needed data sources, programming specific analyses, then changing focus or asking new questions – and the cycle continues.

Advances in technology are bringing stakeholders together to explore all the data and examine different hypotheses in real time. With faster time to insight, it may be possible to rule out lines of inquiry that would have taken months of effort, or perhaps discover more productive new items for further investigation. Today’s technology can be used to shorten cycle times and do in a few hours what used to take weeks. That’s a pretty exciting innovation in the creation of real-world evidence.

Why invest? Better health outcomes and greater business impact

The principal goal in life sciences is to improve patient outcomes and bring better drugs and devices to market faster. Along with market access and commercialization strategies, these activities have the biggest effect on the bottom line. Investments in the right data, analytics, and technologies enable companies to accelerate the bench-to-bedside process and improve the commercialization of new therapies.

This is good news for patients who struggle to meet their cholesterol lowering goal with current treatments. Advances in data management and analytics technology can speed the delivery of information and insight and the enable a broader range of people to work more directly than ever with the data, analytics and evidence. Hopefully, the evidence will help to discover new medical breakthroughs to benefit these patients.


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