AI's Promising Potential in the Fight Against CancerSeptember 8, 2023
Generative AI has brought fast-paced change to nearly every industry, from the way we create and consume content to the way we do business. This incredible technology—capable of generating human-like text, images, and even entire worlds—is driving innovation and sparking new possibilities at an unprecedented pace. Now, a recent study from the UK-based startup Etcembly may be a preview of its historical impact in cancer treatment.
In the study, Etcembly used generative AI to create a novel cancer immunotherapy named ETC-101, which demonstrated remarkable effectiveness in specifically targeting cancer cells while sparing healthy tissue.
Etcembly's AI engine, EMLy, was trained on a massive dataset of cancer cells and immune cells. It was able to identify patterns in the data that would have been nearly impossible for human researchers to find, and it used these patterns to design ETC-101. EMly also played a crucial role in creating a pipeline of other potential immunotherapies for cancer and autoimmune diseases. Notably, the treatment was developed in just 11 months, which is twice as fast as traditional drug development methods.
This study highlights the transformative potential of AI in health care and drug development. It’s also another in a growing line of groundbreaking research studies that are using AI to advance cancer research and explore new treatment possibilities.
The world's most extensive trial of its kind revealed that AI can be safely used in breast cancer screening and significantly reduce radiologists' workload. The trial involved over 80,000 women in Sweden, comparing AI-supported screening directly with standard care. The results showed that AI screening was as effective as two radiologists working together, did not increase false positives, and led to a 44% reduction in radiologists' screen-reading workload. Importantly, AI detected 41 more cancers in patients than the human reviewers, demonstrating its potential to improve early detection.
Separately, researchers at MIT and the Dana-Farber Cancer Institute recently developed a machine-learning model that can determine the origin of tumors in cancer patients when doctors are uncertain about where the cancer started. This crucial development could help doctors choose the most effective treatments and may provide more patients with personalized, targeted treatments instead of broad-spectrum therapies that are often more effective and have fewer side effects. The model's predictions were accurate in identifying the cancer's origin, matching survival outcomes, and improving treatment responses.
In addition to AI’s potential for detecting and treating cancer, AI is showing its strengths in a variety of other ways. AI-powered tools like IBM’s Watson for Oncology are being used to help doctors diagnose diseases more accurately and efficiently and make recommendations for treatments. AI-powered robots are performing surgery more precisely and safely than human hands can manage. AI-powered devices are monitoring patients’ vital signs remotely, creating chatbots that provide patients with support and information about appointments and medication, and analyzing massive health care data sets to identify trends and patterns in disease spread and treatment effectiveness.
These developments are rightfully bringing excitement for a future where AI can help create transformational impact in health care. However, as Norwegian historian Christian Lous Lange noted in his 1921 Nobel Prize acceptance speech, “Technology is a useful servant but a dangerous master.” When technology like AI is harnessed for societal benefit and applied thoughtfully, it can improve lives, enhance productivity, and solve complex problems with greater accuracy and fewer resources. However, overreliance on AI and unvalidated AI recommendations can lead to significant drawbacks like loss of privacy, misinformation, and even tragic outcomes.
It’s crucial to consider the risks and implications of generative AI, particularly in a consequence-rich field like health care. AI is programmed by humans and carries flaws and biases in its outputs. It’s also been found to simply make up information. AI recommendations in health care will continue to generate excitement, but they must be met with skepticism and rigorous examination by real people who have real expertise.
Capitol Technology University’s programs in Computer Science, Artificial Intelligence, and Data Science can prepare you to lead the AI revolution in health care while ensuring it’s used to support, rather than replace, health care professionals. To learn more, visit the AI program page or contact our Admissions team at email@example.com.