Much of pharma’s big data activity to date has focused on R&D. Yet big data can also unlock the potential of existing medicines. By analysing data about their existing treatments, pharmacautical companies have a real opportunity to prevent health problems that may be associated with the drugs and to improve the overall quality of care.
Using big data to identify which patients may be at risk, pharmaceutical companies can drive early prevention and mitigation measures. These may involve patient education or alternative treatment options. Pharma companies could also become part of a ‘patient service workflow’, joining forces with other organisations to address the whole care scene, of which drugs are just a part. US drugstore chain Walgreens is an example of how this can work in practice. The company has developed apps and tools to help people manage their health and is working with organisations such as the Centers for Disease Control and Prevention (CDC) to improve access to healthcare services.
If pharmaceutical companies follow this route, healthcare payers will come to view them as partners that help reduce cost and hospitalisation, while patients will associate them with wellness rather than illness. Collectively, this will enable pharma to become part of a trusted ecosystem of care, safeguarding future revenue streams.
In our view – based on our experience of working with a range of global pharma clients – there are three steps that pharmaceutical companies should follow to use big data more effectively.
In order to be part of this type of ecosystem, pharmacautical companies need to focus on predicting which patients will experience which issues in the future. This means asking questions like:
What characteristics make a patient most and least likely to suffer from a particular condition?
What characteristics are associated with a particular adverse event?
Which patients are most likely to relapse?
How well is the patient population as a whole responding to a drug treatment?
The right big data techniques can answer all of these questions at an extremely detailed level and can allow treatment protocols to be implemented such that patients take their treatments, alter treatments and so on.
To get the right answers, pharmaceutical companies need to make sure they have the right data and should aim to become part of a data ecosystem. They can achieve this by collaborating with partners who host online patient networks and working with academia to help them build up a complete picture of the patient.
In addition, monitoring tools – which enable patients to track their own vital signs – are also fast becoming a prolific source of useful data, and some pharmaceutical companies are already starting to provide these tools to patients. Sanofi Diabetes, for example, is due to launch blood glucose meters that will empower patients to monitor and manage their diabetes in a proactive way1.
The use of big data with traditional technologies has significant time constraints and also requires upfront investment. However, the combination of big data and new cloud technologies breaks down these barriers, allowing pharma companies to gain insights faster and reducing upfront cost.
To realise the opportunities in big data, pharmaceutical companies must develop a well-defined big data strategy. An innovative approach to data may well be the key to competitive advantage in an increasingly patient-centric and wellness-driven world.
PA Consulting Group has been supporting its pharma clients in unlocking the potential of big data. Our work includes designing big data strategy, providing expertise in data analysis, and developing and implementing tools for processing big data.
To discuss successful commercial strategies for big data in pharma, please contact us now.