IBM Watson Health is collaborating with more than a dozen leading cancer institutes to accelerate the ability of clinicians to identify and personalise treatment options for their patients.
The institutes will apply Watson’s advanced cognitive capabilities to reduce from weeks to minutes the ability to translate DNA insights, understand a person’s genetic profile and gather relevant information from medical literature to personalise treatment options. The project is part of IBM’s broader Watson Health initiative to advance patient-centred care and improve health.
The collaborations will enable clinicians to use Watson with a much broader set of patients by the end of 2015, and will accelerate the promise of personalised medicine for cancer patients everywhere.
Ann & Robert H Lurie Children’s Hospital of Chicago, BC Cancer Agency, City of Hope, Cleveland Clinic, Duke Cancer Institute, Fred & Pamela Buffett Cancer Center in Omaha, Nebraska, McDonnell Genome Institute at Washington University in St. Louis, New York Genome Center, Sanford Health, University of Kansas Cancer Center, University of North Carolina Lineberger Cancer Center, University of Southern California Center for Applied Molecular Medicine, University of Washington Medical Center, and Yale Cancer Center are among the first to participate in the project.
As participating institutions use Watson to assist clinicians in identifying cancer-causing mutations, Watson’s rationale and insights will continually improve, providing the latest combined wisdom of the world’s leading cancer institutes for oncologists.
Most of the 1,6-million Americans who are diagnosed with cancer each year* receive surgery, chemotherapy or radiation treatment. Yet when these standard treatments fail and as genetic sequencing becomes increasingly accessible and affordable, some patients are beginning to benefit from treatments that target their specific cancer-causing genetic mutations.
However, the process is time-consuming and requires clinicians to sift through and reconcile a deluge of genetic information – for example a single patient’s genome represents more than 100 gigabytes of data – in addition to health information such as electronic medical records, journal studies, and clinical trial information.
Watson can help clinicians quickly sift through this data and provide comprehensive insights on cancer-causing mutations and medical literature that is potentially relevant. It typically takes weeks for clinicians to analyse each mutation and the available medical literature to then identify tailored treatment options for a patient.
Watson completes the genetic material and medical literature review process in only a few minutes, producing a report and data visualisation of the patient’s case, and evidence-based insights on potential drugs that may be relevant to an individual patient’s unique DNA profile identified in the medical literature. The clinician can then evaluate the evidence to determine whether a targeted therapy may be more effective than standard care for the patient.
“Determining the right drug combination for an advanced cancer patient is alarmingly difficult, requiring a complex analysis of different sources of Big Data that integrates rapidly emerging clinical trial information with personalised gene sequencing,” says Norman Sharpless, MD, director, University of North Carolina Lineberger Comprehensive Cancer Center.
“We are partnering with IBM in an effort to solve this decision problem with the help of cognitive technology and to improve the decisions we make with our patients to maximise their chance for cure.”
In the initial phase of the program, participating organisations will apply Watson to the DNA data of patients who are battling all types of cancer, including lymphoma, melanoma, pancreatic, ovarian, brain, lung, breast and colorectal cancer.
“When you are dealing with cancer, it is always a race,” says Dr Lukas Wartman, assistant director of cancer genomics at The McDonnell Genome Institute at Washington University in St. Louis.
“As a cancer patient myself, I know how important genomic information can be. Unfortunately, translating cancer-sequencing results into potential treatment options often takes weeks with a team of experts to study just one patient’s tumour and provide results to guide treatment decisions. Watson appears to help dramatically reduce that timeline.”
“This collaboration is about giving clinicians the ability to do for a broader population what is currently only available to a small number – identify personalised, precision cancer treatments,” says Steve Harvey, vice president, IBM Watson Health.
“The technology that we’re applying to this challenge brings the power of cognitive computing to bear on one of the most urgent and pressing issues of our time – the fight against cancer – in a way that has never before been possible.”
The new programme builds on IBM Research advancements in analytics and existing Watson collaborations to develop a genome data analysis solution for clinicians. Partners involved in the program will use Watson Genomic Analytics, a new solution specifically designed for genomic analysis. Watson Genomic Analytics is a cloud-based service for evidence gathering and analysis.
It looks for variations in the full human genome and uses Watson’s cognitive capabilities to examine data sources such as treatment guidelines, research, clinical studies, journal articles and patient information. The solution then provides a list of medical literature that is relevant to the case along with drugs that have been identified in the literature.
The patient’s doctor then reviews this information alongside underlying evidence to make more informed treatment decisions. Watson Genomic Analytics constantly gets smarter, as the system learns from patient data.
“We believe our ongoing collaboration with IBM to apply Watson to the challenge of genomic medicine will be a terrific boon to the field of cancer genomics,” said Robert Darnell, MD, PhD, president and CEO, New York Genome Center.
Additional cancer centres are expected to join the programme later in the year.