IBM Watson, Pfizer join forces on cancer drug discovery
IBM Watson and Pfizer teamed up in a new arrangement that will bring supercomputing capabilities to cancer drug discovery.
Pfizer, in fact, will employ Watson for Drug Discovery’s machine learning, natural language processing and other cognitive reasoning technologies to identify new drugs, combination therapies and patient selection strategies in immuno-oncology.
Immuno-oncology is an approach to cancer treatment that uses the body’s immune system to help fight cancer, the companies said.
Oncology researchers at Pfizer will use Watson to analyze massive volumes of disparate data, including licensed and publicly available data as well as Pfizer’s proprietary data. Employing Watson, Pfizer researchers will analyze and test hypotheses to generate evidence-based insights.
According to Pfizer, many researchers believe that the future of immuno-oncology lies in combinations tailored to unique tumor characteristics, which could transform the cancer treatment paradigm and enable more oncology patients to be treated.
“Pfizer remains committed to staying at the forefront of immuno-oncology research,” Mikael Dolsten, president of Pfizer Worldwide Researchand Development, said in a statement. “We are hopeful that by leveraging Watson’s cognitive capabilities in our drug discovery efforts, we will be able to bring promising new immuno-oncology therapeutics to patients more quickly.”
The newly-launched Watson for Drug Discovery is a cloud-based offering designed to help life sciences researchers discover new drug targets and alternative drug indications. Part of Watson’s appeal is the volume of information it can absorb.
The average researcher reads between 200 and 300 articles in a given year, while Watson for Drug Discovery has taken in 25 million Medline abstracts, more than a million full-text medical journal articles and 4 million patents, all of which is regularly updated, according to IBM executives.
Also, they noted, Watson for Drug Discovery can help researchers look across disparate data sets to surface relationships and reveal hidden patterns through dynamic visualizations.
Twitter: @Bernie_HITN
Email the writer: bernie.monegain@himssmedia.com
