In 2025, AI and machine learning will begin to amplify the impact of Crispr genome editing in medicine, agriculture, climate change, and the basic research supporting these fields. It’s worth saying up front that the field of AI is full of such great promise. There’s always a hype cycle with any major advancement in new technology, and we’re in that cycle right now. While the benefits of AI are often years away, genomics and life sciences research is seeing its impact now.
In my field, Crispr gene editing and broader genomics, we often work with huge datasets. can’t do it We don’t have the tools or the time, so we have to deal with it properly. Supercomputers may take weeks or months to analyze a subset of data for a particular question, so you must choose which questions to choose carefully. AI and machine learning are already removing these limitations, and we are using AI tools to rapidly search and discover large genomic datasets.
My lab recently used AI tools to find small gene-editing proteins that were sitting undiscovered in public genome databases because we didn’t have the capacity to process all the data we collected. A group at the Institute for Innovative Genomics, a research institution I founded at UC Berkeley 10 years ago, recently collaborated with members of the Department of Electrical Engineering and Computer Science (EECS) and the Center for Computational Biology to A large-scale language model, similar to those used by many chatbots, predicts new functional RNA molecules that are more thermostable compared to natural sequences. Just imagine what else is waiting to be discovered in the massive genomic and structural databases that scientists have collaborated on over the last few decades.
These types of discoveries have real-world applications. In the two examples above, smaller genome editors can help deliver therapeutics to cells more efficiently, and prediction of thermostable RNA molecules can help biomanufacturing processes generate drugs and other valuable products. It will help you improve. In the health and drug development space, the first Chrispr-based treatment for sickle cell disease was recently approved. Approximately 7,000 other genetic diseases are also awaiting similar treatments. AI helps accelerate the development process by predicting the best edit targets, maximizing Crispr accuracy and efficiency, and mitigating off-target effects. In agriculture, advances in AI-powered Crispr will create more resilient, productive, and nutritious crops and improve food security by allowing researchers to focus on the most fruitful approaches. promises to reduce time to market. In the climate space, AI and Crispr could open up new solutions for improving natural carbon capture and environmental sustainability.
Although still in its early stages, the potential to properly harness the combined power of AI and Crispr, perhaps two of the most profound technologies of our time, is clear and already underway.
