Why imaging is at the epicenter of precision medicine
Estimated reading time: 4-6 minutes
While the term “precision medicine” – medical diagnosis and treatment based on the individual characteristics of a person – is relatively new, as a concept it has been a goal of healthcare systems for some time. Today, for example, cystic fibrosis patients with certain gene mutations can take advantage of specifically tailored medications to help improve lung function, enabling them to live well for longer. Or, a woman with breast cancer can receive targeted therapies proven to be much more effective based on her genetic makeup.
Precision medicine is, at its core, the recognition that each of us is unique, and our healthcare treatment or therapy should be unique as well. Few would argue that it doesn’t represent the future of healthcare. Everyone wants personalized care. Now, in an era of unprecedented data resources and analytics capabilities, precision medicine seems tantalizingly in reach; however, achieving it will require unprecedented levels of coordination and focus.
As a company deeply rooted in diagnostic imaging, Philips is keenly interested in the first part of the precision medicine challenge – precision diagnosis. Indeed, we believe that the accurate diagnosis of the underlying condition via all available data – genetic, pathological, historical, and demographic – is the crux of precision medicine. The more accurate and specific we can be on the diagnosis, including identifying those who may be at higher risk of certain conditions from the outset, the more effectively and cost-efficiently we can treat the condition or disease.
Imaging is, of course, the ubiquitous workhorse technology that helps doctors and radiologists make a confident determination of a patient’s underlying condition. At Philips, we are actively taking steps to combine the power of diagnostic imaging with the capabilities of genomics, informatics, data analytics and artificial intelligence to enable precision diagnosis. By connecting data and technology in this way, we believe imaging is the critical enabler of precision medicine’s greater promise – precise therapies with predictable outcomes.
Let’s apply this vision to the field of oncology. In large measure, cancer still eludes the promise of precision medicine. While some forms of cancer (prostate cancer for example) can exist for years in a non-threatening state and are best not treated at all, other forms progress rapidly and require prompt, sometimes drastic treatment to avoid fatal outcomes. The problem is: we still haven’t got the right diagnostic tools and care pathways to accommodate that difference. We are still relatively inefficient in how we combine lab and imaging results with genetic and population data to determine what course of treatment will be the most effective and least disruptive to a patient based on personal characteristics. The impact of these “imprecise” and inefficient diagnostic pathways can be dramatic and life-altering for patients – not to mention costly for health systems.
Solutions that generate and combine clinical data to provide a single patient view to perform first-time-right diagnosis, ultimately lead to more personalized treatment. With precision diagnosis, we can also extrapolate data in a way that can be applied more systematically to populations of people with specific diseases, as my colleagues Rob Cascella and Dr. Chip Truwit explain in “Precision Imaging: A key Component of Precision Healthcare.” Using a combination of artificial intelligence and data informatics with imaging technology, we can aggregate data from multiple sources to accelerate image processing and accuracy, make diagnoses with minimal interventions, or guide therapy. Radiation therapy is an example of precision medicine – highly individualized – as my colleague, Homer Pien explains in more detail here.
When you add the idea of a “digital twin” into the mix, as my colleagues Henk van Houten and Jeroen Tas have talked about in past posts on the “Digital Patient” and “Digital Hospitals” respectively, the possibilities of precision diagnosis really begin to take shape. Essentially, the digital twin is a lifelong, integrated, personalized model of a patient that becomes progressively “smarter” with the addition of each lab result, exam, image, or other patient data. How empowering would it be to have at your fingertips not just a record or monitoring of important health information from a wearable device, but a dynamic “digital twin” that enables you to intelligently use and integrate information to proactively manage your health and better inform your medical decisions for the future?
Of course, we’re not there yet, but it’s already possible to envision the transformative effect it will have, most notably for diseases like cancer and chronic conditions such as diabetes. With so much potential, it’s no surprise that the precision medicine market is predicted to be worth over USD 96 billion by 2024 . In the meantime, it’s exciting to see the advances we are making in imaging innovation at Philips today with precision diagnosis to help enable precision medicine in the future.
Kees Wesdorp joined Philips in 2017 to lead Philips’ largest business group, Diagnostic Imaging (DI). DI includes Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Advanced Molecular Imaging (AMI) and Diagnostic X-Ray (DXR).