How AI Could be the Key to Cancer Treatments
For many years there has been a quest to find a cure for cancer. With so many different scientists and teams searching for these answers around the world, it has been exciting and encouraging to see the many different ways that cancer is treated, with Artificial Intelligence (AI) and Machine Learning (ML) two of the most incredible ways in which the detection, staging, and treatment of cancer has come on in leaps and bounds in recent years. The pharma, biotech and healthcare sectors are intertwined, and new technologies, medicines and other pharma products have to go through a robust series of processes to determine safety and effectiveness before gaining access to the market. Here, we look at the positives of AI and ML to cancer treatments across the world.
There are a few areas where AI could become an effective part of cancer treatments in the future. The first is where liquid biopsies are concerned. Tissue biopsies have been part of the process of diagnosing cancer for many years, but this is inherently a risky procedure due to its invasive nature. A potential solution to this risk is to use algorithms formulated from machine learning to conduct liquid biopsies. Lung cancer, for instance, is mostly diagnosed at Stage Four, when it is less likely that a patient will survive. With ML and AI programmes designed to detect ctDNA in blood samples, it could improve the rates of early cancer detection.
Another area where ML and Ai could prove decisive is in the area of imaging, which is one of the main areas of cancer detection. Latest AI technology under testing does seem to stand up to comparison with radiologists for detection accuracy rates, but of course this would require greater levels of research and testing before committing to greater use at the expense of physical radiologists.
These processes and actions where ML and AI have indicated high levels of effectiveness within cancer treatment programmes should just be the beginning. There are huge technological strides being made at all times in the biotech and pharma industries and once extensive testing has been completed, we could see that the equipment in place makes a big difference to the success stories of cancer survivors. Of course, there is more to beating cancer than utilising these technologies, but it could be a great improvement in increasing the numbers of survivors in the future.
Utilising Ai and other types of modern technology is the way to ensure that pharma continues to move in a forward, positive direction. Treatments for cancer, and the eventual cure for cancer, is always on the agenda when discussing new trends and improvements within pharma and biotech, and with the correct support and access to clinical trials and new markets, Ai could become a key factor in future cancer treatments. Understanding the potential is one thing, ensuring that there is effective implementation and employment of AI within healthcare settings where cancer treatment is taking place, is an entirely other thing. Connected thinking is always required within these sectors.