Dr. Robert Nagourney In The News

Here are informative videos, TV segments, and articles where our founder Dr. Robert Nagourney discusses cancer biology and how we use laboratory testing to help select the most effective and least toxic drug treatment.

Dr. Nagourney has appeared multiple times on "Extra" for his work with celebrity clients.

The Future of Cancer Research Lies Behind Us

- Robert A. Nagourney, MD

In this episode of The Moss Report Podcast, Ralph W. Moss speaks with Dr. Robert Nagourney about his well-documented approach to precision oncology. Nagourney’s strategy takes a step away from genetic sequencing. By taking a biopsy of a tumor, he claims to be able to deduce what treatments will be effective for an individual. Also in this episode is a discussion about repurposed drugs for cancer treatment, including the use of Metformin.

News Wire

Dr. Nagourney’s Effective Cancer Treatment Shows Promising Results

One prominent practicing oncologist, Dr. Robert Nagourney, has pioneered a technique that is currently having double the success rate of standard cancer treatment.

Wall Street Journal

Every Cancer Patient Is One in a Billion

The disease’s endless variety is reminiscent of Tolstoy’s observation about unhappy families.

Technology

Networks

Repurposing and Combining Drugs – An Effective Cancer Treatment Strategy

Nagourney is having success investigating whether a unique combination of existing and approved cancer drugs might be more effective compared to “off-the-shelf” treatments.

USA TODAY

Mom of six fought terminal breast cancer to live for her kids.

"A complete pathological response. Complete pathological response in this setting is associated with a 90% chance of being disease-free at three years."

Digital Journal

Killing cancer first in a lab may replace generic treatment

In one meta-analysis of over 2500 peer-reviewed, published outcomes, patients who received “active” drugs selected in the laboratory had a 2.04 fold higher response rate ( P < 0.001) and a 1.44 fold higher one-year survival (p = 0.02).