Biomedical AI Technology Is Taking Cancer Treatment by Storm

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AI technology is proving to be the perfect assistant for biomedical startups as they reshape cancer treatment determination.

  • The training dataset is so diverse it will help in determining and tailoring the appropriate course of treatments for a given cancer.
  • Venture capitalists are seeing the writing on the wall and are investing, heavily, in this medical area.

Biomedical startups are using artificial intelligence (AI) to predict patient’s responses to cancer therapies and develop tailored cancer treatments.

In a perfect world, we would not have a need for treatments because then cancer would not be a concern. But this is not a perfect world. Our immune system fights potentially cancerous cells every day. but it’s when it loses the fight that the storm begins. if I were to be an optimistic person, I’d tell you cancer does not kill nearly as many people as it used to. But I’m not.

What I can tell you, however, is that today we have several roads we could take when treating cancer. All with various degrees of success, all with varying degrees of harshness. Unfortunately, sometimes treatment seems very promising for a certain case, only for it to fail at the end.

In recent years, with the rise of AI, biomedical entrepreneurs have realized that they can enhance the success rates of drugs in clinical trials. They would ultimately be customizing therapies for individual patients.

What’s happening is that AI is analyzing the data from clinical trials and extensive gene and protein research. It then identifies patterns that correlate with either a positive response or resistance to treatment.

Basically, by predicting which drugs work best, these startups are developing tests that assist doctors in tailoring treatments. All this so the patient doesn’t suffer more than they must.

Terri Shieh-Newton, a member of the law firm Mintz, Levin, Cohn, Ferris, Glovsky, and Popeo, emphasizes the role of AI in integrating diverse datasets and minimizing biases that may arise from more limited data collections. However, she also stresses the importance of human judgment in carefully selecting and training algorithms with appropriate datasets.

The results are so promising that venture firms are placing significant bets on the potential of these startups, with several companies securing substantial funding. Notable examples include Artera, which disclosed $90 million in venture funding, Vivodyne, launching with $38 million, and Enable Medicine, revealing a $60 million financing round.

In September 2022, ArteraAI, for example, introduced a test that aids treatment decisions for prostate cancer patients. It utilized clinical trial data from tens of thousands of patients across various solid tumors, including prostate cancer, to train its algorithms. The test, performed on digitized pathology slides, provides prognostic and predictive information based on clinical variables, such as patient age and protein levels.

Enable Medicine utilizes AI to analyze RNA sequencing and other data to identify features associated with the response to cancer immunotherapy. This includes studying interactions between immune cells and exploring ways to reverse non-responses.

The biomedical startup landscape is not limited to these companies either.

When we aren’t racing to beat, kill, annihilate, and erase each other, we are capable of so much good, aren’t we?

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