It may seem hard to believe but for every person who benefits from taking one of the top 10 selling medical drugs in the US, far more people - between one in four and one in 25, depending on the drug - see no benefit whatsoever.
This means there is tremendous waste and cost associated with giving the wrong treatments to the wrong people, with obvious implications for public healthcare systems that are often over- stretched, and for private systems trying to be as efficient as they can be.
Fortunately, there is a revolutionary solution at hand: precision medicine.
Put simply, precision medicine uses data and processes like genome sequencing to predict more accurately what treatments – particularly ones that can be preventative – are most likely to be effective for a particular disease and a particular patient.
By studying huge datasets on the medical histories, DNA and lifestyles of millions of people it is possible to identify the causes of cancer and heart disease, weeding out failing treatments and matching patients with the best drugs.
Pathogen genomics, for example, decodes the DNA of malignant bacteria so that doctors can attack microbial resistance to treatments. Then there is “CAR T-Cell” therapy, which uses the body’s immune system to attack cancer cells.
“Precision medicine has the potential to transform the entire healthcare ecosystem,” says Jo Pisani, partner at Strategy&. “By providing cost-effective therapies that actually work, it can reduce healthcare budgets and, importantly for patients, we get disease-modifying therapies that can cure or prevent disease.”
In the UK, digital medicine is centre stage for the National Health Service (NHS), which is set to make extensive use of preventive medicine as part of a new, long term plan focused on prevention, with the backing of an extra £20bn funding for the system over the next five years.
Precision medicine also promises to open up significant opportunities for growth and cost reduction by pharmaceutical companies.
Yet there are significant challenges associated with this. One is the use of data and the analytics used to produce recommendations for patients. Another is how to align budget cycles in a way that allows the sort of long-term planning needed.
Given that big data is so critical to precision medicine, how should that data be used, bearing in mind privacy concerns? By and large, the public supports research into precision medicine but is understandably nervous about the way data may be commercially exploited.
These concerns were brought into sharp focus in 2017, when the UK privacy watchdog found that an NHS trust broke data protection laws when it gave Google’s artificial intelligence arm, DeepMind, access to the personal medical records of 1.6m British patients.
Trust and security loom large here. That’s particularly true when it comes to genomics data given that there have been controversial breakthroughs in genome sequencing. “The critical challenge will be: who owns that data?” says Genya Dana, Head of Precision Medicine at the World Economic Forum’s Centre for the Fourth Industrial Revolution. “How does it get integrated into your medical record? And then, how does that translate into actual healthcare practice?”
