Our Stories.

 
From data to drugs in 2021
Year-in-review Laura Kleiman Year-in-review Laura Kleiman

From data to drugs in 2021

We showed that our AI technology can quickly sift through massive amounts of data to find the most consequential evidence. We then deployed our technology to rigorously analyze 16,000 published studies and identify the most promising non-cancer generic drugs for the treatment of prostate cancer.

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2020 was an extraordinary year for Reboot Rx
Year-in-review Laura Kleiman Year-in-review Laura Kleiman

2020 was an extraordinary year for Reboot Rx

We received a $1.5 million donation, which enabled us to launch Reboot Rx and hit the ground running in 2020 towards our goal of saving the lives of cancer patients with existing non-cancer generic drugs. We built our evidence synthesis pipeline and a working prototype of our AI technology that efficiently prioritizes drug repurposing candidates at scale, and we completed a proof of concept of our technology.

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Reboot: COVID-Cancer Project: a proof-of-concept of our evidence synthesis technology
COVID-19 and Cancer Laura Kleiman COVID-19 and Cancer Laura Kleiman

Reboot: COVID-Cancer Project: a proof-of-concept of our evidence synthesis technology

Cancer patients who contract COVID-19 and their doctors need to quickly find information about potential treatments, but there’s so much data that it’s impossible to make sense of it all. We applied our AI technology to rapidly aggregate the most relevant studies on COVID-19 and cancer. Now that we’ve completed this proof-of-concept, we’re scaling this approach to synthesize the cancer data for all non-cancer generic drugs. This will enable us to find the most promising generics to repurpose for cancer.

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We are excited to announce our new collaborations
Laura Kleiman Laura Kleiman

We are excited to announce our new collaborations

We have partnered with computer scientists at IBM Research’s Science for Social Good Initiative and Byron Wallace’s group at Northeastern University to build our evidence synthesis technology. Together we are using AI and machine learning to identify and synthesize data on non-cancer generic drugs being tested as cancer treatments.

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