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Incorporating real-life clinical data into drug development

When a new medicine reaches the market, it is accompanied by an extensive data package that provides information about the safety and efficacy of the medicine in a clinical trial setting. However, assessing the expected future value of the medicines when used in "real world" clinical practice requires additional information next to traditional (pre-authorisation) clinical trials. Regulatory, HTA agencies and other healthcare decision makers have to make decisions on authorisation and access under conditions of uncertainty. Currently, data packages which aim to minimise uncertainty on safety and efficacy may leave significant uncertainty in assessments of real world effectiveness of new medicines. This results in further research commitments required post-authorisation (PASS, PAES, Reimbursement with Evidence Generation), and wide variability in access to medicines between countries.

The subsequent uncertainty relating to the reimbursement, and thus market implementation of new medication once approved by regulatory authorities, is negatively affecting the value of the drug development pipeline. The costly clinical developments to get to market approval, no longer seem to be a guarantee for market entry. This new risk presents a serious additional hurdle for drug developers that already face pipeline attrition. It also affects the speed and level of patient access, and therefore the extent to which patients and society might benefit from new medicines.

In recent years there has been considerable attention paid to the post-authorisation evaluation of treatments in real world clinical practice: study design and analytical methodology for assessing relative effectiveness; and use of registries and electronic healthcare data. It may be possible to improve the value of information available at initial market authorisation by incorporating these techniques into pre-authorisation drug development. HTA bodies, regulators, will become able to make better-informed decisions, and developers of new medicines will be able to direct development efforts to areas where value is most likely to be delivered to patients and health care systems, improving the efficiency of the whole medicine development chain.

However, the adoption of real world / relative effectiveness objectives in a pre-authorisation development strategy has many operational, methodological, regulatory, and ethical issues and Pharmaceutical R&D organisations need more certainty as to: the impact of development choices on the regulatory review process; the value of different programmes to HTA bodies and other decision makers; the best balance of pre-launch and post-launch effectiveness research and the coordination of various post-authorisation commitments. There is little guidance on how to incorporate alternative study designs into a development programme to optimally meet the needs of all stakeholders over time.

The GetReal consortium aims to improve the efficiency of the medicine development process by better incorporating real-life clinical data into drug development and to enrich decision-making by regulatory authorities and HTA bodies through:

  • Bringing together regulators, HTA bodies, companies, patients and other societal stakeholders
  • Assessing existing processes, methodologies, and key research issues
  • Proposing innovative (and more pragmatic) trial designs and assessing the value of information
  • Proposing and testing innovative analytical and predictive modelling approaches
  • Assessing operational, ethical, regulatory issues and proposing and testing solutions;
  • Creating new decision making frameworks, and building open tools to allow for the evaluation of development programmes and use in the assessment of the value of new medicines;
  • Sharing and discussing deliverables with, among others, Pharmaceutical companies, regulatory authorities, HTA / reimbursement agencies, clinicians and patient organizations;
  • Developing training activities for researchers, decision makers and societal stakeholders in the public and private sector in order to increase knowledge about various aspects of RE.

GetReal is a public-private partnership between key European stakeholders and leading research groups: The GetReal consortium is an interdisciplinary and pan-European consortium that crosses the borders of different disciplines. Participants have been working on real life clinical data and related topics both individually as well as jointly in various settings for several years. The consortium also includes members familiar with the processes and realities of commercial drug development, and the changes to R&D models that are under discussion. Several European organizations who are GetReal participants will ensure complete European coverage and EU-wide dissemination and implementation. These include the EMA, the Dutch reimbursement body CVZ that is a member of the EUnetHTA network in which the various reimbursement bodies throughout Europe are bundling their expertise on Health Technology Assessment, and the International Alliance of Patients' Organizations (IAPO) that covers patient organizations all over the world GetReal creates impact by developing a set of tools, decision frameworks, methods and insights to include real clinical data in drug development: GetReal will deliver within the timeframe of three years an important set of tools, decision frameworks, methods and insights that are of immediate use to public and private stakeholders and which can be applied in decision making and strategy development.The key deliverables include:

  • Analyses of key issues in scientific papers, reports and workshops. Taking into consideration inputs from regulators, HTA bodies, patients and health care professionals;
  • A decision-making framework for Pharma R&D for the design of development strategies that include pragmatic trials and observational studies to provide information about real world effectiveness of medicines, including RE;
  • Open tools allowing different stakeholders to use mathematical models to inform drug development, market authorization and reimbursement decisions, including the use of different comparators and assessing their impact; Impact of the deliverables is ensured as GetReal brings together the key pan-European organizations in a results-oriented dialogue, thus creating a strong platform for discussions and dissemination of results.


Makady A, Stegenga H, Ciaglia A, Debray TPA, Lees M, Happich M, Ryll B, Abrams K, Thwaites R, Jonsson P, Goettsch W on behalf of GetReal Work Packages 1 & 4. Practical Implications of Using Real-World Evidence in Comparative Effectiveness Research: Learnings from IMI-GetReal. Journal of Comparative Effectiveness Research 2017.0:.

Efthimiou O, Mavridis D, Debray TP, Samara M, Belger M, Siontis GC, Leucht S, Salanti G, on behalf of GetReal Work Package 4. Combining randomized and non-randomized evidence in network meta-analysis. Stat Med 2017.36:1210-1226.

Panayidou K, Gsteiger S, Egger M, Kilcher G, Carreras M, Efthimiou O, Debray TP, Trelle S, Hummel N, on behalf of the GetReal methods review group. GetReal in mathematical modelling: a review of studies predicting drug effectiveness in the real world. Res Synth Methods 2016.7:264-77.

Debray TP, Schuit E, Efthimiou O, Reitsma JB, Ioannidis JP, Salanti G, Moons KG, on behalf of GetReal Workpackage 4. An overview of methods for network meta-analysis using individual participant data: when do benefits arise?. Stat Methods Med Res 2016.0:.

Efthimiou O, Debray TP, van Valkenhoef G, Trelle S, Panayidou K, Moons KG, Reitsma JB, Shang A, Salanti G, on behalf of the GetReal methods review group. GetReal in network meta-analysis: a review of the methodology. Res Synth Methods 2016.7:236-63.

Debray TP, Moons KG, van Valkenhoef G, Efthimiou O, Hummel N, Groenwold RH, Reitsma JB, on behalf of the GetReal methods review group. Get real in individual participant data (IPD) meta-analysis: a review of the methodology. Res Synth Methods 2015.6:293-309.

Hummel N, Debray TPA, Didden E-M, Efthimiou O, Egger M, Fletcher C, Moons KG, Reitsma JB, Ruffieux Y, Salanti G, van Valkenhoef G, on behalf of WP4. Methodological guidance, recommendations and illustrative case studies for (network) meta-analysis and modelling to predict real-world effectiveness using individual participant and/or aggregate data. 2017.0:.

Project Details

FunderInnovative Medicines Initiative
Project Reference115546
Funded PeriodOct 2013 - Dec 2016
Funded ValueEUR 16,952,280
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