Access to real-world clinical data provides pharmaceutical companies with the opportunity to understand how their drugs actually work in patients, helping new drugs get through regulatory approval faster and, in turn, reducing costs and providing better products for patients.
There has long been talk about the potential of translational medicine to transform the way drugs are discovered and how patients are treated, but now we are now seeing that talk become a reality. Interestingly, rather than advances in sciences or technical process being at the heart of this change, it has been the use of informatics and the application of eHealth to the field that is making the most difference - and through this is helping the pharmaceutical sector overcome the difficulties it faces in developing new drugs in an economically viable way.
PA Consulting Group and 4D Biomedical’s recent annual translational medicine foresighting event highlighted how many of these developments are now working in practice across the UK. The contributors showed that the challenges of securing access to clinical data; developing the tools to understand that data; and of creating business models that derive value from translational medicine are being overcome. A particularly important driver of progress is the way that Government, academics and industry are coming together to make these developments a reality all through the use of an Open Data approach.
One example of this approach is the UK Government’s commitment to make all patient data available for approved research. This is being taken forward through the Clinical Practice Research Datalink (CPRD) which is providing researchers with access to 52 million medical records. Difficulties relating to consent have now been resolved with an opt out clause. As a result the CPRD is now offering the biomedical sector the opportunity to access real-world health data and unlock real value from that information.
For pharmaceutical companies, this offers the opportunity to make major advances in their understanding of how drugs work in real-world patient populations. It will also provide more information about side effects and about disease progression. All this will help new drugs get through regulatory approval faster and that will, in turn, reduce costs as well as provide better products for patients.
Another important development lies in the way technology is being used to enable the combination of data from multiple sources. This is particularly useful given the disparate nature of structures in the NHS and in academic research, where historic difficulties in sharing information across different parts of the discovery pathway, such as between basic research, clinical translation, primary and secondary care.
For example, IDBS, a data management company, is working with a number of academic organisations, including King’s College London, to integrate data from a number of different hospitals with data from research. This is then helping clinicians make better decisions about diagnosis and treatment decisions. Paul Denny Gouldson VP of Translational Medicine at IDBS summed up the position:“We need to get new treatments from research into the clinic much faster and also requirements from clinic back into research much faster, but as researchers we don’t trust data unless we have the context to interpret and analyse it ourselves. That means you need as much good quality data as possible.” These informatics developments are the key to enhancing the availability of that data.
Another way in which data is being made more widely available can be seen in the North West ehealth (NWeHealth) initiative. NWeHealth is aggregating and anonymising data from particular populations which can then be used to better develop health provider services and enable biomedical research. It currently provides access to 400,000 patient records and by next year this should have risen to two and a half million. What is critical is the way this system is able to interrogate multiple data sources so that if one group is looking at social modelling and another patient behaviour, the data analysis should be able to identify automatically related findings from both groups. The data can also be used to identify patients for clinical trials in a way that is faster and cheaper than traditional approaches, and so reduce a key cost of drug development.
Much of this work is being enabled by the development of large scale data processing by the emergence of relatively low cost cloud computing platforms. PA has used a cloud system to analyse year on year A&E admissions to a hospital in 20 seconds, when previously it would take weeks or even months to extract this information. It is this ability to analyse large scale population data quickly that is changing the way in which we treat patients and deliver care.
It is now clear that this data has real commercial value both to existing pharmaceutical companies and to the new entrants to the sector. But in order to secure this value, companies will need to develop new business models. Those models will need to reflect the contribution of each of the data providers and ensure that the inputs are appropriately reflected in any commercial arrangements. This is particularly relevant in the growing field of stratified medicine as more therapies are linked to a diagnostic product and gene analysis test. This means pharmaceutical companies will need to work more closely with device companies and use clinical data to identify which particular patient cohorts will benefit from a particular drug.
This will draw on work such as the four year collaboration between Arizona State University and Pfizer, which aims to identify protein and biomarkers which will predict cardio-vascular disease and assess new treatments for type 2 diabetes. This kind of approach underlines that, instead of information coming exclusively from clinical trials, there is now the possibility of identifying the patient cohort from data held by academic or healthcare providers. However, for this to happen traditional licensing and royalty arrangements will need to be reviewed and we also require a willingness to think about new ways of funding research.
All this means that the pharmaceutical industry will need to be more agile in the way it accesses data and funds its provision. This will be especially important if funding moves to outcomes based pricing where quality information about patient outcomes will be critical. So, all those involved will have to undertake careful work to ensure that all contributors’ input is valued in a way that incentivises data sharing.
It is clear that if pharmaceutical companies are to benefit from this work, and so meet the challenges the industry is facing, it will need to work in a different way. It will need to harness the power of large data sets by finding ways to analyse them and then using that analysis to understand disease progression better and the impact of treatment in particular groups of patients. Interpretation of data is likely to become more complex as more sources of data are combined and it will be vital to use the technology and growing expertise, both in the sector and outside, to maximise the benefits and understanding from that data.
The companies that embrace this approach and are more innovative in their drug discovery processes will reduce time and costs and make the development of new drugs more sustainable. The technology is now out there that can make a difference, and it is working in practice.
While there is much more to be done, especially in developing business models that will deliver commercial value from this work, the opportunities are there. The UK is perhaps uniquely placed to stimulate that work because it is giving researchers access to such a wide range of data from early discovery through to the details of how patients respond to treatment.
It is clear that we are on the brink of a huge change in the way we carry out drug discovery and the industry needs to seize the opportunities both to secure a sustainable future and to deliver real improvements in treatment.
Dr Hakim Yadi is a life sciences and healthcare expert at PA Consulting Group.
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