The use of Real World Data (RWD) has been identified as one of the key pilots where the practical applications of cross-border health data exchange should be tested for research and public health purposes (EC COM(2018) 233 final). RWD may be related with health-related data not collected within the context of a typical clinical research setting, such as randomised controlled trials. Over the last years, the use of RWD for health purposes has been increasing rapidly. Such a use could complement traditional health care data sources to provide broader insights into in a real-world setting. A wider use of RWD is supported by the digitalisation of health records, efforts to link different health data resources and cross-border exchange. The use of wearable devices is an example of a source of RWD which can support drug development and personalised medicine through advanced analytics.
RWD has the potential to be used as a source of Real World Evidence (RWE) which can support and/or complement data collected from traditional clinical research. For regulatory purposes, RWE can be a useful source of information, such as to better understand disease epidemiology or the life cycle of a medicine. In the marketing authorisation phase, RWE can be supportive to the evaluation and decision on the benefit/risk balance and for extrapolation to special populations. In the post-marketing phase, RWD could provide evidence on real-world effectiveness and safety thus refining the benefit-risk. The COVID-19 pandemic has further highlighted the value of RWD for decision-making and regulatory purposes. The field or rare diseases is of particular interest as the scarcity of individuals living with a particular condition as well as the heterogeneity of the disease are just some of the challenges making the traditional clinical research difficult and lengthy. The rich but diverse health care landscape of different countries, the increasing importance to establish data platforms as a reliable source of information and the several projects that have been initiated in this respect make it crucial to provide an up-to-date overview of the progress that is being made.
This Research Topic is dedicated to RWD generated for regulatory purposes in the rare diseases setting. We invite experts, i.e. scientists, economists and experts in social sciences to propose their original research articles, reviews and meta-analyses describing the use of RWD in the orphan medicines R&D and picture the possible economic, social and political impact. Key themes within this Research Topic:
• Facilitation by national authorities of RWD use
• Use of RWE by Health Technology Assessment bodies and payers to support decisions on cost-effectiveness
• Research activities specifically aimed to implement RWD in the orphan medicines R&D for regulatory purposes, e.g. o Data collected within academic trials or Patients-initiated data collection/sharing
• Impact of off-label prescription data for regulatory purposes e.g. for repurposing
• Economic, political and social implications of the collection and use of RWD
• Use of analytic tools and methodologies, such as Artificial Intelligence
• Post-marketing data collection based on RWD.
The use of Real World Data (RWD) has been identified as one of the key pilots where the practical applications of cross-border health data exchange should be tested for research and public health purposes (EC COM(2018) 233 final). RWD may be related with health-related data not collected within the context of a typical clinical research setting, such as randomised controlled trials. Over the last years, the use of RWD for health purposes has been increasing rapidly. Such a use could complement traditional health care data sources to provide broader insights into in a real-world setting. A wider use of RWD is supported by the digitalisation of health records, efforts to link different health data resources and cross-border exchange. The use of wearable devices is an example of a source of RWD which can support drug development and personalised medicine through advanced analytics.
RWD has the potential to be used as a source of Real World Evidence (RWE) which can support and/or complement data collected from traditional clinical research. For regulatory purposes, RWE can be a useful source of information, such as to better understand disease epidemiology or the life cycle of a medicine. In the marketing authorisation phase, RWE can be supportive to the evaluation and decision on the benefit/risk balance and for extrapolation to special populations. In the post-marketing phase, RWD could provide evidence on real-world effectiveness and safety thus refining the benefit-risk. The COVID-19 pandemic has further highlighted the value of RWD for decision-making and regulatory purposes. The field or rare diseases is of particular interest as the scarcity of individuals living with a particular condition as well as the heterogeneity of the disease are just some of the challenges making the traditional clinical research difficult and lengthy. The rich but diverse health care landscape of different countries, the increasing importance to establish data platforms as a reliable source of information and the several projects that have been initiated in this respect make it crucial to provide an up-to-date overview of the progress that is being made.
This Research Topic is dedicated to RWD generated for regulatory purposes in the rare diseases setting. We invite experts, i.e. scientists, economists and experts in social sciences to propose their original research articles, reviews and meta-analyses describing the use of RWD in the orphan medicines R&D and picture the possible economic, social and political impact. Key themes within this Research Topic:
• Facilitation by national authorities of RWD use
• Use of RWE by Health Technology Assessment bodies and payers to support decisions on cost-effectiveness
• Research activities specifically aimed to implement RWD in the orphan medicines R&D for regulatory purposes, e.g. o Data collected within academic trials or Patients-initiated data collection/sharing
• Impact of off-label prescription data for regulatory purposes e.g. for repurposing
• Economic, political and social implications of the collection and use of RWD
• Use of analytic tools and methodologies, such as Artificial Intelligence
• Post-marketing data collection based on RWD.
