Obesity is a major public health problem, affecting millions of people around the world. I am one of them. That is, after all, why I have efforted to curate this online community. Obesity can lead to a number of health problems, including heart disease, stroke, type 2 diabetes, and some types of cancer.
There are a number of treatments available for obesity, but until the advent of GLP-1ra treatments, many of them were not very effective or have significant undesireable side effects. In recent years, there has been growing interest in the use of artificial intelligence (AI) for the treatment of obesity.
AI has the potential to revolutionize the treatment of obesity in a number of ways. First, AI can be used to identify new drugs that are more effective and have fewer side effects than current drugs. Second, AI can be used to develop new delivery methods for drugs that make them easier to take and more effective. Third, AI can be used to personalize the treatment of obesity by tailoring the dose and type of drug to each individual patient.
Today, Eli Lilly and XtalPi announced a $250 million deal to use XtalPi's AI technology to identify potential drug candidates for the treatment of obesity. XtalPi's technology uses machine learning to analyze large datasets of chemical compounds. This could allow the two companies to identify compounds that have the potential to be effective drugs for obesity.
The pairing of AI and GLP-1 meds specifically, has the potential to again revolutionize the treatment of obesity. By leveraging AI to identify new drugs, develop new delivery methods, and personalize treatment, AI could help millions more around the world lose weight and improve their overall health.
How AI could be used to treat obesity with GLP-1 meds
Here are some specific ways that AI could be used to treat obesity with GLP-1 meds:
Identify new GLP-1 receptor agonists: AI could be used to screen large libraries of chemical compounds for those that have a high affinity for the GLP-1 receptor. This could lead to the identification of new GLP-1 receptor agonists that are more effective at reducing weight than current drugs.
Develop new delivery methods: AI could be used to design nanoparticles that can deliver GLP-1 directly to the liver, where it is needed most. This could make GLP-1 meds easier to take and more effective.
Personalize treatment: AI could be used to predict how each patient will respond to different GLP-1 meds. This could help doctors to tailor the dose and type of GLP-1 med to each individual patient, which could lead to better outcomes.
The personalized treatment opportunity is the one that gets me particularly excited. Imagine a world where your body's chemistry is so understood (because of AI learning), that you are delivered a weekly/monthly/annual shot that addresses the exact hormones your body has become deficient in.
Now that is something to get excited about.