Advancing RWE together with academia

Pharma can realise the potential of RWE faster by collaborating more effectively with academia but first it must build trust

The promise of real-world Evidence (RWE) to offer a cost-effective way to help drive transformations in healthcare and drug development is dependent on significant improvements being made in the way real-world data (RWD) is collected and developed into robust evidence.
Challenges include limited access to databases, incomplete data and problems dealing with the enormous volume of data generated on a daily basis. Much time is spent on acquisition, cleansing, integration, standardisation and encryption, as well as analysis and extraction of insights.
This is where closer collaboration between pharma and academia can help. The two can do a lot more to foster stronger ties and more fruitful cross-sector collaborations, says Thomas D’Hooghe VP and head of global medical affairs fertility at Merck KGaA. 
With 20 years of medical scientific experience in academia, he has worked on projects ranging from from pre-clinical research in animal models, to diagnostics and real-world data to health economics and patient-centricity projects. 
Differing incentives
Pharma needs deep therapeutic area expertise from people who have both a clinical and a medical scientific background, says D’Hooghe. But the differing drivers that exist between academia and industry are a problem, he says. 
“In academia the incentive is really to have new developments, to focus on innovation and to have a paper with a high hit-back factor which creates new grants, new insights and so forth,” he explains. “From a pharmaceutical perspective, however, the idea is to develop a product that can be brought to patients. 
“The big divide is the discrepancy between innovation and validation. Usually and unfortunately academia stops at the level of innovation and does not go sufficiently into validation because first the mindset may not always be there and second the funding may not be there.”
This gap between academics, who want to see their innovations become effective tools in future drug developments, and industry, which is looking to adopt new technologies and bolster shrinking pipelines, must be bridged, says D’Hooghe.
He believes collaboration early on with the right academic partners is crucial for defining a study question, the right population, methodology and so on. “This is a huge opportunity for pharma to partner with academia early on to develop an innovative idea through to validation into a product,” he says. 
Success will depend on developing complementary competences between industry and academia. “It’s always better to work with academia because they know from a practical and scientific point of view what is important and what is less important.”
And he says early engagement will ensure sufficient funding for the important projects.
Mind the data gaps
But problems with accessing data and gaps in the data itself will still need to be resolved before the impact of RWE can be fully realised. “Generally speaking,” he says, “I think it’s true to say that most of the nationally available databases are not really of the quality needed to answer some of these questions.
“Many are not reliable, the quality control is lacking and the relevant data are not always present. So, pharma must look to academic centres that have high-volume, high-quality clinical care and high quality of data collection.”
The growing use of Electronic Health Records (EHRs) makes more standardisation of EHRs a pressing priority for all, adds D’Hooghe. “Pharma needs to work with academia to develop standardised data collection methods, raise quality standards and build confidence in RWE,” he says.
As well as partnerships between academia and industry, regulators and clinicians should also be involved in developing data standards. There has been much discussion around a three-way academia-industry-government partnership, known as the Triple Helix Model, which is seen by many as the latest evolution of strategic alliances to bridge the translational gap, provide incentives and directly fund projects.
Finally, pharma must also work to foster greater trust. Without it the quality of academic partnerships companies are able to forge will suffer. “There is a traditional suspicion from academia about pharma’s motives,” says D’Hooghe. “Some academicians might be reluctant to put their name alongside a publication which has been co-written by pharma. 
“In the past they have had experiences where industry was manipulating data, not telling the full truth. Certainly, in the 80s and 90s it was quite clear that academicians were finding themselves being highly influenced by industry.  It’s a mindset that needs to disappear and industry, which needs to work with academia for credibility purposes, must work on that.”
In his own field of fertility, D’Hooghe says a typical area where the chasm between academia and industry is clearly evident is in the treatment of endometriosis.
“We don’t yet have a biomarker available that can identify endometriosis in women who have a normal ultrasound,” he says. “One of the reasons for this is there are a massive amount of papers describing innovation but hardly any translation of these innovations into validations. 
“More structured and prioritised partnerships between academia and industry early on in development leading to co-development could be a solution to this.”
Given the potential of RWE, collaboration with academia to identify research opportunities, standardise data collection methods and build trust are essential to bridge the gap between clinical research and clinical practice and lay the foundations for future breakthroughs. 

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