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Establishing the Comparative effectiveness and Safety of New Treatments Using Real World Data

It is important to compare competing interventions to determine value of medicines, both from clinical and societal perspectives. In the market, regardless the clinical condition under evaluation, usually many interventions are available and few of them have been studied in head-to-head studies.[1] HTA agencies generally rely on techniques such as, network meta-analysis (NMA) to derive the necessary estimates and incorporate them into cost-effectiveness models. The use of real world data (RWD) for head-to-head comparison purposes was often challenged due to data limitations and difficulty to draw causal conclusions.

However, the increasing availability of regulatory-grade RWD is challenging this status quo. The biases that used to plague the use of observational data can now be avoided. Specifically, we can eliminate immortal time bias which occurs when during the period of observation, there is some interval during which the outcome event cannot occur. [2] 

Decision makers have to decide between the available treatments irrespective of the quality of the available evidence. A sound use of real world data allows us to provide information (even if it is tentative) that can support and improve the quality of their decision making. This is especially true for decisions involving head-to-head comparisons for which no randomized trial is available.

Although, other challenges of working with RWD (e.g., confounding) continue, the approach of emulating target trials makes causal inference and head-to-head comparative effectiveness using RWD a reality.

The Target Trial Emulation approach is a new approach which leverages the design of a clinical trial and through appropriate data source selection and the use of advanced epidemiological and statistical methods allows to provide a comparison of how the drug perform in the actual clinical practice.

There are many benefits of using this approach. Target trial emulation can be used to generate efficacy or safety evidence for conditional regulatory approval or post-market assessment. It provides a comparison when NMA is not possible, for example, if we have disconnected networks. Target trial emulation also helps in expanding the scope of a randomized trial, refining aspects of an existing treatment protocol, and enabling a comparison to identify optimal treatment regimen.

Several life sciences companies have started to support their regulatory submissions with findings from RWD studies. Click the button to learn how Cytel can help you position your therapy for success.

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[1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5386629/

[2] https://jamanetwork.com/journals/jama/article-abstract/2776315



About the Author of Blog:

Mansha Sachdev specializes in content creation and knowledge management. She holds an MBA degree and has 11 years of experience in handling various facets of marketing, across industries. At Cytel, Mansha is a Content Marketing Manager and is responsible for producing informative content that is related to the pharmaceutical and medical devices industries.


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