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Genetic Analytics

Unprecedented Drug Approval Can Benefit Pancreatic Cancer Patients

May  24,  2017
News From Pancreatic Cancer Action Network

For the first time, the U.S. Food and Drug Administration (FDA) has approved a cancer drug based only on molecular characteristics of the patient’s tumor – and not on the organ site. The presence of the molecular alteration, known as microsatellite instability (MSI), is assessed in eligible pancreatic cancer patients through the Pancreatic Cancer Action Network’s state-of-the art Know Your Tumor® precision medicine service.

Every pancreatic tumor is different. The Pancreatic Cancer Action Network strongly recommends molecular profiling of your tumor to help determine the best treatment options.

A Patient Central Associate can help you determine if you or a loved one is eligible for Know Your Tumor. Molecular profiling provides detailed information about the genetic and protein changes that are present in each patient’s tumor – and these findings can help inform treatment decisions.

“We’ve often said that pancreatic cancer patients shouldn’t be treated with a one-size-fits-all approach,” said Lynn Matrisian, PhD, MBA, chief science officer for the Pancreatic Cancer Action Network. “Sometimes molecular profiling can reveal characteristics in a patient’s pancreatic tumor that are more frequently seen in a colorectal tumor – or a tumor of the lung or breast – and there may be drugs that work particularly well in tumors with these characteristics.”

The drug approved by the FDA is called Keytruda (pembrolizumab) and is produced by Merck. It functions by blocking the cancer cells’ ability to avoid an immune attack. Tumors with high MSI have been shown to be particularly susceptible to treatment with Keytruda.

“High MSI status can be found in pancreatic tumors, though it’s not common,” Matrisian said. “Patients who undergo molecular profiling get a glimpse into the molecular workings of their tumor, discovering clues that could allow them the opportunity to be treated with a drug, like Keytruda for high-MSI tumors, that is more likely to result in a positive response.

“We applaud the FDA and Merck for approving Keytruda for any solid tumor that displays high MSI. We are hopeful that this type of approval will pave the way for future molecularly targeted cancer drugs that aren’t specific to the organ site of the tumor.”

To learn more about Know Your Tumor, molecular profiling or any topic related to pancreatic cancer treatment or diagnosis, contact Patient Central. We are here to help.

Healthcare Analytics require a systematic methodology to analyze big data such as cancer genomic data.

The following webinar presented 30 May 2017 provides just such a methodology:



Microsoft R Server solutions

This webinar will provide a walkthrough of Campaign Optimization. Marketing campaigns are not only about what you say, but also when you say it. Effective campaigns driven by advanced analytics systematically test and learn delivery timing to optimize open rates, click through rates and conversion rates. This solution is the first of this kind that demonstrates how you can leverage the power of R on multiple platforms: we will show the solution deployed on HDInsight Spark Clusters as well as on SQL Server with R Services.

The goal of the Microsoft R Server Solution is to demonstrate time to value and show how easy it is to build solutions by using the templates. These solutions are fully customizable and extensible and you can experience this with a few clicks and a Azure Subscription.


PDF of webinar is located at the following link:

Campaign Optimization Example

Pancreatic Cancer: Progress and Challenges in a Rapidly Moving Field

Eric A. Collisson and Kenneth P. Olive

Eric A. Collisson

Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California.Department of Medicine, University of California, San Francisco, San Francisco, California

DOI: 10.1158/0008-5472.CAN-16-2452 Published March 2017

Cortana Intelligence and Machine Learning Blog

Predicting Traits from Genomic Data Using the Microsoft Azure Linux Data Science VM




Predicting phenotypes from genomic data using FaST-LMM on Microsoft Azure's Linux Data Science Virtual Machine