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Covid-19 has changed the drug development landscape: the time for real-world data is here – experts

by Natalie Morrison
LONDON, 17 July (APM) - Covid-19 has changed the drug development landscape with drug developers, regulatory and health technology assessment (HTA) bodies all now relying more heavily on real-world data for urgent answers, according to Aetion chief executive Carolyn Magill.
She and Cegedim Health Data's global head, Gilles Paubert, spoke to APM in an emailed interview on Thursday after announcing a new partnership between the two health technology data management and analysis companies to power real-world evidence research in Europe.
The collaboration comes as the drug development landscape is rapidly modifying processes to allow data collected in a real-world setting to be used for evidence generation, whereas traditionally the focus has been randomised clinical trials.
"Real-world data is critical at a time like this because it can be available quickly — within a few days of the point of care, as an example — and provides a robust view of treatment pathways and outcomes across patient populations," Magill said.
"Importantly, these data reflect disparities based on race, geography and co-morbidities in time for something to be done to expand access to quality care and improve outcomes."
But it seems use of these data will not just be for the pandemic - it is here to stay. Many experts and drug developers - recently including Novartis (APMHE 67879) - agree that pharma's "digital moment" has finally arrived and that real-world evidence generation will be applied to wider drug development.
"It's time is absolutely here," said Paubert, adding that, since the crisis, many organisations have made changes in order to use real-world data more. "I think it's time to take action and move beyond statements about the value of this data. Clearly, the role of this data is key for clinical trials, with a potential impact on cost reduction and speed of results."
The U.S. Food and Drug Administration (FDA) has already repeatedly aired expectations that learnings derived from Covid-19 research will be central in the ongoing shift towards continuous evidence generation at scale, Magill said.
"Lessons abound from our new world order of navigating clinical research during this global pandemic," she added.
"Increasing pressures on the time and cost of getting medications to market necessitate that these lessons — of how and when to turn to data to accelerate drug testing and development — extend to other indications."

Real-world data uses

The data sets can be used for many purposes, including in regulatory assessment to better understand safety and efficacy of treatments, as well as for health assessment bodies to better understand value.
However, Magill argued that its biggest utility will be in supplementing clinical trials to represent populations and settings traditional studies cannot.
"We also expect real-world data to play a role in secondary indications and safety studies where appropriate endpoints are captured systematically in readily accessible data," she said.
Applying real-world research methods to vaccines means it is now possible to efficiently study safety in large populations over time, Magill added, with analyses updated on a monthly basis, rather than a "static moment-in-time approach".
For diseases, it can help better understand pathology and its evolution, helping to identify treatments and sub-groups of patients who could benefit. "Above all" it should help health authorities to "better manage diseases", said Paubert.
He argued that its biggest possible utility is for tracking and monitoring real-time population health, enabling health authorities globally to develop an early warning indication for any change in symptoms or spikes in illness which could indicate another potential pandemic.
He added: "This data goes beyond patient biometrics and diagnoses to include treatments, clinical outcomes and medical history when possible. Longitudinally, it also supports retrospective insights into pathways and patient journeys, both of which can lead to the identification of novel patterns which can then be further interrogated through research."
In any case, the medicines industry is becoming "smarter" about how it identifies fit-for-purpose data, Magill continued. "We understand more about the scientific rigor required to control for confounding variables as we generate evidence. These advancements empower real world data to play an increasingly critical role in the months and years to come."

Clinical consultations a key source

There is a wealth of information available, with healthcare systems capturing huge amounts of data across "millions of touchpoints", Paubert said.
But he noted that the "most prolific" is clinical consultations.
"Information captured at this crucial intersection between patient and doctor has huge value when it is coded, structured, anonymised and ready for advanced analytics or artificial intelligence (AI)," he said.
He went on to emphasize the need for data to be accessible and ready to use quickly, "because if you have to wait three to six months to analyse data, you'll be too late".
The Cegedim-Aetion partnership was formed to this end, he said, with the aim of integrating Cegedim's THIN European real-world data into Aetion's evidence platform, which analyses real-world data to produce real-world evidence rapidly for biopharma, regulatory and other healthcare body uses. "Our partnership with Aetion illustrates how analytic platforms can improve the time to produce results and secure a decision."
"EHR data can support faster selection of appropriate sites for clinical trials to be conducted, and the evidence we derive from these data inform selection criteria for patients to participate in studies," Magill said.
"This new collaboration will enable Aetion's clients to easily access Cegedim's leading edge clinical data, which includes millions of patient records in Europe. By analysing the THIN database on our platform, biopharma will be able to unlock essential treatment insights to inform clinical development planning, prepare regulatory and HTA submissions, and to meet post-marketing safety requirements."

Data privacy

Paubert conceded, however, that there remain concerns in general about the protection of personal data.
"But while it's important for everyone to understand that the protection of personal data is crucial, we're in the early adoption stages. The sharing of anonymous health data must continue to be seen as ethical and of great value to people."
Had better adoption of real-world data already been in place before the Covid-19 pandemic, "it's likely to have had a different impact on the transmission of the virus and containment measures, particularly with the introduction of alert and monitoring indicators," Paubert said.
Still, "it is very difficult to predict exactly how differently the pandemic situation would have played out had better adoption of real-world data had already been in place more widely," he said.
"We have not yet measured all the collateral impacts on chronic pathologies, but the implementation of monitoring solutions based on real-world data is essential. Beyond the optimisation of clinical trials, real-world data, in this case, gives us a unique ability to anticipate and manage pathologies.
"Global collaboration is without any doubt going to be essential in managing the response to any future pandemic and real-world data will be key to surfacing key learnings."
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