Artificial intelligence (AI) has opened new possibilities in many fields. The power of AI to increase time to result and efficiency is unparalleled when the AI is tuned correctly, and the appropriate questions are asked and addressed. Gene editing/therapy is no exception and AI has already begun to make big contributions.
An example of AI supporting the design of a gene editing enzyme is observed by the novel ZFdesign software. Zinc Finger nucleases are a class of proteins that specifically target a region within a genome to make an edit to a the DNA. Due to the complexity of the binding interactions, it is difficult to engineer zinc fingers at variable regions within a genome. ZFdesign allows for more precise zinc finger design at reduced cost and time. The AI modeling is based on a prediction of nearly 50 billion DNA zinc finger interactions. This technology enables researchers to overcome significant obstacles and increase the design of zinc finger nucleases at a pace that has never previously been achieved. (https://www.nature.com/articles/s41587-022-01624-4)( New Zinc-Finger Technology Makes For Faster, Better Genetic Editing (bio-itworld.com)
Another example of AI supporting gene editing and cell engineering is observed in the design of gene editing experiments. AI can be useful in predicting off-target effects, optimization of target selection and delivery, and identification of novel targets. A great example of AI in cell engineering can be observed from Kiromic Biopharma’s Diamond AI platform. The platform is a cognitive and predictive AI to access Kiromic’s data library and differentiate between disease-specific and normal genes. This platform can be used to harmonize new surface tumor targets which can then be used to create commercialized cell therapies focused on immunooncology. (https://kiromic.com/science/technology/diamond-artificial-intelligence-platform/)
SOHM’s ABBIE technology will be directly impacted by AI in next-generation designs of the platform technology as well as internal and client-based AI-modeled engineering targets. As ABBIE depends on targeting genomic DNA like Zinc finger nucleases, AI will aid in increasing its specificity to reduce off target effects for safety. AI will also aid in increasing its integration efficiency and providing other novel uses of the technology in many fields of biology and medicine. The ABBIE technology potential will grow in parallel with other advances in this exciting AI-driven era.
Dr. David Aguilar, COO
