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Biomedical data scientist Sylvia Plevritis is an expert in computational modeling of cancer risk and treatment options hidden in the remarkable quantity of data available today. Rarely is a tumor made up of a single mutation, she says, but more commonly of a mix of different mutations. Such heterogenous tumors may require complex combinations of drugs to produce the most effective treatments. That’s where computers can help.
Using mathematical simulations, Plevritis is helping patients and their doctors understand the genetic makeup of a given cancer for the purpose of identifying drug combinations that stand a better chance of success. Some of the models Plevritis works with can be run in an hour or less and yet return invaluable guidance that can save a patient’s life.
Plevritis says these computational approaches can even help those without cancer understand their inherent genetic risks to assess whether and when additional screening or risk-reducing interventions are warranted.
Join host Russ Altman and biomedical data scientist Sylvia Plevritis as they dive into the promising intersection of computers and cancer care. You can listen to The Future of Everything on Sirius XM Insight Channel 121, iTunes, Google Play, SoundCloud, Spotify, Stitcher or via Stanford Engineering Magazine.
Connect With Us:
Episode Transcripts >>> The Future of Everything Website
Connect with Russ >>> Threads / Bluesky / Mastodon
Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook
Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
By Stanford Engineering4.8
127127 ratings
Biomedical data scientist Sylvia Plevritis is an expert in computational modeling of cancer risk and treatment options hidden in the remarkable quantity of data available today. Rarely is a tumor made up of a single mutation, she says, but more commonly of a mix of different mutations. Such heterogenous tumors may require complex combinations of drugs to produce the most effective treatments. That’s where computers can help.
Using mathematical simulations, Plevritis is helping patients and their doctors understand the genetic makeup of a given cancer for the purpose of identifying drug combinations that stand a better chance of success. Some of the models Plevritis works with can be run in an hour or less and yet return invaluable guidance that can save a patient’s life.
Plevritis says these computational approaches can even help those without cancer understand their inherent genetic risks to assess whether and when additional screening or risk-reducing interventions are warranted.
Join host Russ Altman and biomedical data scientist Sylvia Plevritis as they dive into the promising intersection of computers and cancer care. You can listen to The Future of Everything on Sirius XM Insight Channel 121, iTunes, Google Play, SoundCloud, Spotify, Stitcher or via Stanford Engineering Magazine.
Connect With Us:
Episode Transcripts >>> The Future of Everything Website
Connect with Russ >>> Threads / Bluesky / Mastodon
Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook
Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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