The precision medicine boom is giving oncologists and cancer patients access to vast amounts of critical information that can be leveraged to develop a comprehensive profile of a patient’s disease and inform the best course of treatment.
The challenge: making sense of the data.
There are more than 20,000 genes in the human genome, after all. And each patient has unique variations and genetic predispositions, meaning that two people with the same cancer could have vastly different needs.
A new tool is helping the Miami Cancer Institute bring clarity to this complex process. Earlier this year, the South Florida cancer center began using IntelliSpace Precision Medicine Genomics, a system that pairs next-generation DNA sequencing with deep learning algorithms.
The clinic uses mountains of precise data about genetic mutations, drugs that might target them and enrollment criteria for relevant clinical trials to craft a personalized plan of attack.
Developed by Philips and aided by third-party scientists, the collaborative tool accomplishes something far beyond the capacity of most cancer centers, says Jeff Boyd, the Miami institute’s director of translational research and genomic medicine.
“The ability to interpret terabytes of binary data from a patient’s tumor and turn it into an oncologist-friendly molecular pathology report takes some very robust technology infrastructure with a lot of people and computers,” Boyd says. “This technology can be leveraged to do truly extraordinary things.”
How Precision Medicine Uses Cancer Patient Data
To get started, the Miami team obtains a tumor biopsy and conducts the DNA sequencing in its genomics laboratory.
Data from the sample — which covers hundreds of genes and variant types associated with common solid tumors and allows multiple biomarkers to be evaluated — is fed into a patient’s electronic medical record. That record is then transmitted via Philips’ cloud-based, HealthSuite digital platform to N-of-One, a third-party molecular decision-support company.
Experts there, Boyd says, “perform bioinformatics analysis that would be uninterpretable to an oncologist.” The company “cleans up the data and provides a very nice-looking, user-friendly report” that is sent electronically to the Miami Cancer Institute. The process takes about 10 days from start to finish.
The Philips platform offers privacy features (patients’ personal information is obscured) and controls that follow best practices and comply with relevant regulations, such as HIPAA. It also incorporates backup, recovery and encryption controls, as well as secure authentication and authorization mechanisms.
Cloud Platform Connects Cancer Data
Each patient ultimately receives a report based on the data analysis. Fields identify critical genes and mutations, any FDA-approved drugs that target those specific tumors and mutations, drugs that match a mutation but for another tumor type (what is known as “off-label use”), and relevant clinical trials searchable by a patient’s location.
Using the Philips technology, “we can identify ZIP codes that are looking at a specific gene mutation with specific drugs coming out of the pipeline and being used in a clinical trial setting at one institution or another,” Boyd says.
The ultimate goal? To save time and money, and to deduce the best-aligned medical treatments that target a particular tumor — strategic execution that Boyd describes as like a “key in a lock or hand in a glove.”
Still, the approach isn’t suitable for every case. Doctors recommend using the IntelliSpace technology based on a patient’s cancer type and the viability of existing options, Boyd says, noting that tougher-to-treat variations such as lung and pancreatic cancer are prime candidates.