Rival European Perspectives on the Challenges of Integrating Data into Drug Decision-Making

The European Medicines Agency is going to take a rather bolder approach to the use of data than in Germany, to judge from a couple of major statements just out at the end of January.

EMA has delivered ‘ten recommendations to unlock the potential of big data for public health in the European Union’, a document drafted by the task force on big data that it shares with the complementary Heads of Medicines Agencies. Top of its list is a platform that would access and analyze healthcare data from across the EU, creating a European network of databases that can support regulatory decision-making with robust evidence from healthcare practice.

The view of big data is essentially positive-envisaging datasets captured across multiple settings and devices, including wearable devices, electronic health records, clinical trials or spontaneous adverse reaction reports. “Coupled to rapidly developing technology, big data can complement the evidence from clinical trials and fill knowledge gaps on a medicine, and help to better characterise diseases, treatments and the performance of medicines in individual healthcare systems,” says the EMA task force. It recognizes head-on the obligation on regulators to evolve and change the way they access, manage and analyse data and to keep pace with the rapid advances in science and technology, given the rapidly changing data landscape.

At IQWiG, the German health technology body, there is a similar recognition of the merit of integrating drug data. “Particularly in the case of accelerated drug approvals and drugs for rare diseases (orphan drugs), the evidence available at the time of market access is often insufficient for the early benefit assessment of drugs. Often, the studies are too short or no data on patient-relevant outcomes were collected,” it says.

But the approach outlined is much more cautious. “How must the data be collected and processed so that they can be used” for benefit assessments in Germany, it asks. And it insists, in answer, that “the use of routine practice data for benefit assessments of drugs mandatorily requires a comparison between the new drug and the comparator therapy”-which makes it necessary to conduct comparative studies. The collection and processing of routine practice data from electronic patient records and claims data from health insurance funds, “is currently not possible with regard to benefit assessments of drugs and will not be possible in the near future”, it says, because the data quality in these sources is insufficient and important data are not collected.

Admittedly, the roles of EMA-which evaluates quality, safety and efficacy of medicines-and IQWiG-which assesses benefit-are different, and their needs differ correspondingly. But the contrast is nevertheless striking, even in the tone adopted.

The ever-ebullient Guido Rasi, EMA’s executive director, said of his agency’s recommendations, “I look forward to working with the European Commission and national competent authorities to see how these concrete proposals can be implemented to better harness the potential of big data. This will help to further strengthen the robustness and quality of the evidence upon which we take decisions on medicines”.

But at IQWiG, readiness to shift perspective is less evident: comparative studies with randomization “remain the gold standard”, it concludes.

However, on one point at least, the views of the two bodies coincide: it is important to improve the operation of registries. As IQWiG’s director, Jürgen Windeler, observes, “The conditions for high quality registries could be better. This concerns both funding and the fact that there are different requirements for data protection in different German federal states.” And the EMA recommendations prominently feature the crucial need to have verified quality, content and data security.”