Including real-world data from expanded access programs into regulatory approval decisions and health-economic analyses: benefits and challenges
Patients suffering from seriously debilitating or life-threatening conditions who are not eligible for further treatments or any clinical trials, may resort to ‘expanded access’ (EA): pre-approval access to investigational treatments. EA is an option for a select group ofdrugs that passed Phase-I/II, but have not yet obtained full regulatory approval. The growing number of requests for EA and recent movements, such as Right-to-Try in the US, stress the interest of patients and physicians in EA.
Historically, EA programs were not considered for research. Nowadays, these programs often incorporate basic effectiveness and safety data collection. Such data – collected outside of conventional clinical trials – is called ‘real-world data’. Although the interest in RWD has risen over the last years, little is known about how, why and whether real-world data (RWD) and expanded access (EA) can be combined.
To answer the above, we first aim to investigate how RWD from EA programs has been used in the past by regulators (e.g. Lutathera, developed at Erasmus MC). Secondly, we will investigate statistical techniques to appropriately combine RWD (‘big data’) and RCTs. Thirdly, we will assess whether RWD from EA can play a role in cost-effectiveness analyses. Lastly, we aim to quantify the value of RWD from EA in terms of value of information analyses.
Our research will help clarify the usability of these data. Awareness of the potential value of RWD from EA should facilitate that these data are incorporated in decision making whenever this is feasible and appropriate, and this should impact on traditional clinical development. For patients, this better use of available data can result in speedier access to more diverse treatments
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