5 Ways Technology Is Changing Personalized Medicine

October 18, 2013

By Thomas Heydler 
October 18, 2013 | In today’s doctor’s office, when a physician diagnoses a patient, a number of tests are consulted and the best possible course of treatment is prescribed. Unfortunately there is often limited data that allows the doctor to tailor and customize treatment specifically to a patient's biology and lifestyle. But there are five ways technology will change that over the next decade, bringing personalized medicine to fruition.
1) Correlations and Data Science. As consumers we first realized the power of correlation with e-commerce. Amazon's "people like you also bought" feature introduced algorithms to look at our online buying profile and match us to others so we could easily find new products we might enjoy. These commerce algorithms are in fact the foundational technology for creating medical algorithms to segment populations for clinical trials. Ultimately, physicians will use biomarkers and genetics to correlate a patient to a population "like him" and thus match him to the most efficacious treatment. At the current moment, a handful of diseases with simple and direct markers have been found, but the power of correlation will truly come to fruition in approaches like those used by researchers Nigam Shaw and Russ Altman, who have been able to use data mining to identify potential rare side effects and segment the population into those at risk of experiencing those side effects. By understanding a person’s biology and how he will react to a particular therapy, researchers will be able to develop more targeted and effective treatment options and physicians will more accurately prescribe those treatments. 
2) Advancing Clinical Utility of Genomics. Obtaining sequencing data has gotten faster and less expensive, but bottlenecks exist not just in regulatory process but also in correlating DNA sequence with clinical outcomes. Great examples of sequences with clinical utility exist, such as BRCA1, BRCA2 in breast cancer or the CFTR gene for cystic fibrosis. A key driver for the future is advancement of clinical utility for other genes with advances in the bioinformatics pipelines and data management. Major players in sequencing technologies are already offering data analysis and data storage cloud services in addition to just the instrumentation. New technologies that break the bottleneck in analysis and drive clinical utility of additional genes will be crucial to advancing the translation of sequencing to the clinic.
3) "Datafication" of Tissue. To date, much of the buzz in personalized medicine has been focused on the increasing possibility to easily extract data from DNA. The reality is that diagnoses today and in the future will be made of multiple types of diagnostic data. It will be essential for scientists and clinicians to be able to mine not just DNA, but also extract quantifiable data from images. At Definiens, we've termed the datafication of tissue images and its correlation with clinical outcomes “phenomics”. Although genomic data can give clues to the ideal therapy, tissue images typically are more highly correlated to stage and presentation of disease, making the correlation of both types of data essential to the future of personalized medicine. 
4) Telemedicine and Biosensors. At September's TedMed, Eric Topol dazzled audiences by using a cell phone to remotely monitor vital signs. While the term personalized medicine originally applied to tailored therapies, many like Topol believe that personalized medicine will also entail the use of devices and sensors for physicians to continuously monitor their patients remotely and tailor treatments on the go. Today's sensors are as small as a dime, but advances in nanotechnology could shrink sensors to allow for implantation in the body. With this miniaturization, you can imagine a day in which not only could glucose levels be monitored effortlessly in diabetics, but biomarkers of response to prescribed treatments could be continuously monitored via small sensors to alert physicians if threshold levels were reached.
5) Engineering Cells and Printing Organs. Within the next few decades, 3D printing will come to medicine. With over ninety thousand Americans awaiting organs, nothing will become more personal than the ability to "print" an organ from your own cells. Regenerative medicine pioneer Tony Atala has already printed the first 3-D kidneys and San Diego-based start-up Organovo is working on the 3-D printing of a liver. Initially 3-D tissue prints will be used as models for drug action and safety, but many believe that in 10-15 years 3D printing will enable tissue and organ construction from cells harvested from the patient, providing the ability to produce custom and personalized organs on demand.
While some of these technologies like DNA sequencing and tissue datafication exist today, others such as 3-D printing of organs are still in proof of priniciple phases. Nonetheless, as we look to the future of personalized healthcare, technology is poised to be a major driver in how we get there.
Thomas Heydler is CEO of Definiens, the leading provider of image analysis and data mining solutions for quantitative digital pathology in the life sciences, diagnostic biomarkers and healthcare industries. Heydler has more than 20 years of entrepreneurial expertise and in-depth knowledge of global software and IT, having served in prior executive roles at Barcelona Design, InterPro Business Solutions, Documentum, Cadence Design Systems and Siemens AG. He can be reached at theydler@definiens.com.