Founding Director of Integrated Cancer Research at Tech Publishes ‘A Patient’s Guide to Cancer: Understanding the Causes and Treatments of a Complex Disease’

Georgia Tech College of Sciences (April 3rd, 2023)

There are times when John McDonald, emeritus professor in the School of Biological Sciences and founding director of Georgia Tech’s Integrated Cancer Research Centeris asked to share his special insight into cancer.

“Over the years, I’ve gotten calls from non-scientist friends and others who have been diagnosed with cancer, and they call me to get more details on what’s going on, and what options are available,” said McDonald, also a former chief scientific officer with the Atlanta-based Ovarian Cancer Institute.

That’s the primary motivation why McDonald wrote A Patient’s Guide to Cancer: Understanding the Causes and Treatments of a Complex Disease, which was published by Raven Press LLC (Atlanta) and is now available at Amazon or Barnes and Noble in paperback and ebook editions. The book describes in non-technical language the processes that cause cancer, and details on how recent advances and experimental treatments are offering hope for patients and their families.

A book for the proactive patient.

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Dr. McDonald To Be Honored by Georgia Center for Oncology Research and Education (CORE)

Georgia Tech College of Sciences (January 24th, 2023)

John McDonald, emeritus professor in the School of Biological Sciences and founding director of Georgia Tech’s Integrated Cancer Research Center, has been named one of “Today’s Innovators” in cancer care by the Georgia Center for Oncology Research and Education (CORE).

McDonald, who also served as the chief scientific officer of the Ovarian Cancer Institute, will be honored during the “Toast to the Trailblazers” event that is part of CORE’s 20th Anniversary Celebration, set for Saturday, February 18 of this year, at the Atlanta History Center.

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Researchers investigate gene network to identify “cancer driver genes”

 

Drug Target Review (December 14th, 2021)

A team at the Georgia Institute of Technology, US, have found that an important class of genetic changes in cancer patients may be happening in places where scientists do not normally look: the network of gene-gene interactions associated with cancer onset and progression. Their discovery may uncover new targets for gene therapies.

Cancer chemotherapy has undergone a paradigm shift in recent years with traditional treatments such as broad-spectrum cytotoxic agents being complemented or replaced by drugs that target specific genes believed to drive the onset and progression of the disease. This more personalised approach to chemotherapy became possible when genomic profiling of individual patient tumours led researchers to identify specific “cancer driver genes” that led to the onset and development of cancer.

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Top Opportunities for Artificial Intelligence to Improve Cancer Care

 

Health IT Analytics (November 29th, 2021)

As artificial intelligence (AI) continues to grow in the healthcare field, researchers are findings new ways to utilize its capabilities. In chronic disease management and prevention, especially in cancer research, AI has been critical in the diagnosis, decision-making, and treatment process.

According to the National Cancer Institute, AI, machine learning, and deep learning can all be used to improve cancer care and patient outcomes.

“Integration of AI technology in cancer care could improve the accuracy and speed of diagnosis, aid clinical decision-making, and lead to better health outcomes. AI-guided clinical care has the potential to play an important role in reducing health disparities, particularly in low-resource settings,” NCI wrote on Cancer Detection & Diagnosis Research.

With the use of AI, researchers can create the next stage of precision oncology.

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Machine Learning Predicts Cancer Treatment Response

 

machine learning algorithm

Health IT Analytics (October 29th, 2021)

The Georgia Institute of Technology and Ovarian Cancer Institute researchers are using machine learning algorithms to predict how patients will respond to cancer-fighting drugs.

Advances in machine learning and artificial intelligence are allowing researchers to create more targeted precision medicine-based treatment using predictive analytics. By analyzing large amounts of complex data, clinicians can provide individualized treatments, improving patient outcomes.

“In medicine, we need to be able to make predictions,” professor at the School of Biological Sciences and director of the Integrated Cancer Research Center in the Petit Institute for Bioengineering and Bioscience at the Georgia Institute of Technology, John F. McDonald, said in a press release.

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