Healthcare is evolving rapidly with the advent of AI, and the same applies to many different sectors and industries. Thus far in medicine, AI has been utilized for a wide range of tasks ranging from automating notes during a clinical visit to personalizing individual patient treatment plans by enhancing drug interaction safety. These applications, along with numerous others, corroborates the influence AI will have on the field of medicine in the foreseeable future.
AI now could also revolutionize the early detection of cancer: a key goal due to its substantial influence on the extent of disease severity. Recently, researchers at MIT and Microsoft have used AI to do exactly this by developing a molecular sensor system called CleaveNet which employs peptides to detect proteases—enzymes found in abundance in cancer cells.
The role of AI in this particular application comes into play through the actual design of the peptides. CleaveNet was created through a protein language model that predicts amino acid sequences of peptides.
AI optimizes the accuracy of peptide-protease interactions by ensuring each peptide can be cut by only one protease. Accuracy in the system allows healthcare providers to understand the particular form of cancer affecting the human body since proteases vary according to cancer type.
In the past, researchers had to rely on the “trial-and-error” method when utilizing this system and as a result, peptides were often cut by more than a single protease, limiting accuracy. With the rise of AI, however, researchers can explore trillions of possible peptide combinations, significantly elevating the overall cancer detection success of the system.
Researchers also note that the usage of AI in this particular manner could enable the creation of an extensive catalog of protease biology. Proteases are involved in additional health problems like heart disease and neurodegeneration, so this atlas could prove to be important for the detection of these chronic diseases as well.
Overall, this recent development serves as a major success of AI usage in healthcare. As AI grows globally, it is time to embrace its applications while also being mindful of certain limitations and clinical ethics.
