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AI has entered the design stage of biology. For medicine, that creates remarkable opportunities. For biosecurity, it raises equally important questions. Image used for representational purposes only
\n | Photo Credit: Getty Images<\/p>\n
Did cataclysmic events happen over the week in healthcare – developments that made us sit up and take note, fume a little, wonder much and record everything? Bringing to you, five major themes that caught our attention this past week, and then, some more.<\/p>\n
AI technology is forever invading our columns here, opening up the possibilities of what can happen in the future, and indeed, bringing the future to our door steps today. The last week, there was news about researchers using\u00a0AI to design, hold your breath – viruses. A particular type of virus actually – a bacteriophage. Infectious Diseases specialist Dr. Abdul Ghafur explains what happens when AI begins to design pathogens. Referring to the Stanford experiment that produced the bacteriophages (bacteria- eating viruses), he explains: \u201cIt does not show that AI can casually manufacture dangerous human viruses; it shows that computers are beginning to move from analysing biological information towards proposing biological designs that scientists can physically build. This requires appropriate governance and safeguards.\u201d<\/p>\n
\u201cThe computer did not create a virus. It did not touch a test tube or handle a living cell. What it did may ultimately be more consequential: it helped decide what the virus\u2019s genome should be,\u201d he writes. Of the 285 AI-generated designs physically synthesised and tested in the laboratory, 16 produced functioning phages. Some were able to overcome bacterial resistance that defeated the original virus. What is new, is not the physical manufacture of a virus. AI has entered the design stage of biology. For medicine, that creates remarkable opportunities. For biosecurity, it raises equally important questions, he says.<\/p>\n
Further, in the cardiac diseases sector,\u00a0AI heart disease prediction tools show promise but are not ready for clinical use,\u00a0Afshan Yasmeen\u00a0writes, quoting a review. Published in\u00a0BMC Medical Informatics and Decision Making, an open-access journal. The review assessed 30 studies published since 2017 on AI-based models developed to predict future cardiovascular disease among adults without established heart disease. Researchers say \u201cMany models demonstrate good discrimination, but very few studies examine whether the predicted risks correspond to what actually happens in different populations.\u201d For more on this, hit the link above.\u00a0<\/p>\n