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By Mark Lee, Global Head for Personalized Healthcare, Genentech
& Ron Park, Global Head of Personalized Healthcare, Global Product Strategy

The technologies we use on a daily basis — from search engines to streaming music services — recognize patterns in our behaviors and use vast amounts of data from millions of other individuals to make predictions of what each of us may want in the future. In so doing, the power of data at scale has transformed almost every industry, personalizing experiences in many aspects of our lives. Yet, in healthcare, we’ve only scratched the surface.

The dream of bringing about this transformation has been around for several years, but the digitization of healthcare has never been at the requisite level — until recently. The future of personalized healthcare will be about meaningful data at scale: utilizing technology to acquire a greater breadth, depth, and quality of data than ever before, and then combining data in a manner that enables us to understand what makes each individual unique.

Data can come from many sources. Real-world evidence — data acquired in everyday clinical practice — can provide valuable insights related to individuals’ disease biology and treatment outcomes. Such information not only helps us understand existing medicines, but can also be taken from the bedside back to the research bench to inform the development of future treatments. Real-world data also have the potential to replace the control arm in clinical trials, making evaluation of medicines more efficient.

Comprehensive diagnostics are another key source of data. Current companion diagnostic tests based on single biomarkers are only the beginning. Next-generation sequencing can map out an individual’s full genetic makeup, tumor mutations, and other defining molecular features to find the most appropriate treatment. Liquid biopsies may allow us to non-invasively track how a cancer evolves over time and adjust treatment accordingly.

Digital health platforms like wearables and apps can gather more data and capture a critical perspective: the patient voice. People can report detailed information about their symptoms, treatment burden, and quality of life, documenting their health in real-time detail, in a way that goes beyond the standard tests performed episodically at their doctor’s office.

Artificial intelligence (AI), such as machine learning, can help us analyze these vast amounts of healthcare data to derive insights we previously could not have realized. AI can potentially enable more consistent interpretation of images, resulting in better-informed treatment decisions.

Patient data across all of these dimensions have enduring value when aggregated and accumulated to ever-increasing scale. But it’s not as simple as just collecting a large volume of data. We need smarter ways of analyzing it, and the whole healthcare system — from the way we develop therapies to the way care is delivered to patients — has to evolve to accommodate new kinds of data and the means to act on the insights that will follow. We also have to make sure these aggregated data are appropriately de-identified or anonymized to protect patient privacy. This is the path to finally capturing a complete picture of an individual’s medical profile and defining truly optimal care for each person — what personalized medicine is all about.

Learn more about our vision for the future of healthcare.