Extensive digitisation of genomic data is an important prerequisite for synergies between genetic engineering, biotechnology and artificial intelligence.
AI makes it possible to search through huge amounts of molecular genetic information in very short periods of time, collecting suitable data to use as a basis for designing new gene variants and gene combinations (generative AI).
The ‘AlphaFold’ program developed by Google DeepMind is the best-known example of biotechnology and AI convergence. For the first time, this program makes it possible to predict the three-dimensional structure of proteins, even if no experimental data is available.
CRISPR-GPT, which was developed by several US universities and Google DeepMind, demonstrates the enormous potential of generative AI in genetic engineering. This large language model agent is designed to assist in the selection of target genes and suitable CRISPR/Cas variants to improve targeting accuracy. Besides making predictions about possible side effects, it can also produce corresponding laboratory protocols.
Publication date / last update:
March 2026