Paired with a single database effort, AI could capture, interpret, correlate, and evaluate millions of data points to better support researchers.

The National Cancer Institute has spent an estimated $115 billion on research and developing treatments over 45 years, yet approximately 39.6% of men and women will be diagnosed with cancer at some point during their lifetimes, of which an estimated 600,000 will die each year, according to NCI. What’s preventing our great medical minds from developing effective treatments and cures for cancer and other terminal illnesses?

Recent breakthroughs in immunotherapy, gene sequencing and other areas hold great promise. But for many people facing terminal illness, the clock will run out before they can benefit. We need to find ways to speed up the search for cures, and to develop life-sustaining treatments that can give time and hope to those who are suffering.

Some of the barriers to moving quickly are institutional and cultural. The culture in government and research institutions, mostly spearheaded by academia, is not driven by the same focus on quick results that we have in the private sector.

Researchers could use AI to expedite analysis of data to produce better treatments more quickly and efficiently.

There are, however, some areas—such as access to data and rapidly developing new technologies—where government and medical research can learn and benefit from advances in the private sector. Here are two:

Create massive databases.

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The scientific community needs to establish open access to a robust database of all known information about the diseases it is researching. This database could be managed by non-corporate governmental entities. For instance, the National Cancer Institute could oversee all data on cancer, while the National Institute of Health could manage data on other terminal diseases.

An openly accessible data hub would provide researchers in the public and private sector with the most current information, including:

  • All known data on the disease (i.e., causes, energy sources, symptoms, molecular structure, compromised pathways within the body).
  • Patient histories of all known victims of the disease (this information would be completely anonymous so as not to compromise patient privacy).
  • Data on all known therapies and their recorded outcomes (including traditional medical and pharmaceutical treatments and alternative therapies).

The level of collaboration and information sharing needed for success would require a massive culture change. The National Institute of Health would need to lead the charge in building public awareness, while public and private sector organizations as well as the government provide appropriate funding and support. Improving patient outcomes should be the primary gauge of success throughout.

How much more quickly could cures be found if medical researchers were aligned in their efforts, collaborated proactively and frequently with other researchers, and had open access to a centralized database with analytical capabilities? This leads us to our next technological support necessity:

Capitalize on artificial Intelligence.

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Artificial intelligence, or AI, is a growing part of our future largely due to its timesaving capabilities and programmable accuracy. Used in everything from manufacturing to microscopic surgery, AI holds the potential for massive data congregation and analysis. Think about how AI can quickly and efficiently analyze data to beat a chess master at his own game. It is time for us to train this functionality and focus it on finding a cure for terminal illnesses.

Software programs such as the powerful IBM Watson have the ability to quantify, categorize, and interpret large bodies of information quickly. Researchers could use AI to expedite analysis of data to produce better treatments more quickly and efficiently.

AI can also be used to create a predictive algorithm to determine the probability and degree of a given treatment’s success. Paired with the single database effort outlined above, AI could capture, interpret, correlate, and evaluate millions of data points to better support researchers. The scientific community could then focus time and effort on solutions, with much less busywork involved.

In addition to these timesaving, analytical, and collaborative benefits, AI could be used to analyze the effectiveness of alternative therapies for terminal illness. By using AI to record, categorize, and analyze reported alternative medicine data along with other aggregated content, we will gain a clearer view of the effectiveness of these therapies when compared side by side with traditional treatments.

For instance, many patients undergoing chemotherapy, radiation or other conventional treatments also use holistic and natural alternative therapies. Recording and analyzing this data would help us understand how these treatments improve patient outcomes. It would also reduce bias and conflicts between conventional and alternative therapies and help us better judge the effectiveness of patient-centered solutions.

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While speeding up the process of finding cures for terminal illnesses, AI can also help pave the way for treatments to help sustain life until cures are discovered. When examining life-sustaining treatments, AI can be can be used to gather data in four main areas:

  • Causes of the disease.
  • The disease itself.
  • Energy sources that support the disease.
  • Compromised pathways in the body affected by the disease.

Within each of these areas, there are numerous possible attack points to explore. With the support of AI, disease specialists can analyze and customize treatments as determined by each patient’s individual medical history. Capitalizing on AI’s algorithmic predictive capability opens new possibilities for personalized medicine, allowing treatment specialists to determine the best mix of conventional and alternative treatments to help to control disease processes and sustain each patient’s life.

A New Way Forward

Government and medical research institutions can learn a lot from the private sector’s embrace of new technologies in their fight against terminal diseases. The best companies continually review their processes to find ways to bring better products to market faster. In contrast, the clinical trials process is slow, cumbersome, complex, and bureaucratic, and has a poor history of success.

With a robust database, supported by AI and predictive algorithms, our best medical research minds have the opportunity to dramatically improve the process and the speed with which life-saving treatments are brought to market. Technology companies such as IBM and Tempus have already made tremendous progress in this area. Now it’s up to all medical research centers and government agencies to align their processes to capitalize on their technology. With these tools in place, our scientists can produce more viable cures and life-sustaining solutions for those who most desperately need them. We owe it to those who suffer from terminal illness to try.

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Robert Martin writes books with his granddaughter Keira Ely, including the bestsellers “The Case of the Missing Crown Jewels,” and “SuperClara — a Young Girl’s Story of Cancer, Bravery and Courage.” Robert founded the nonprofit Bridge to a Cure Foundation to fund life-sustaining treatments for children suffering from terminal illness.

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