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bioRxiv · 10.1101/2024.04.25.591003

CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments

Qu, Y.·Huang, K.·Cousins, H.·Johnson, W. A.·Yin, D.·Shah, M. M.·Zhou, D.·Altman, R. B.·Wang, M.·Cong, L.
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Abstract

Performing effective gene-editing experiments requires a deep understanding of both the CRISPR technology and the biological system involved. Meanwhile, despite their versatility and promise, Large Language Models (LLMs) often lack domain-specific knowledge and struggle to accurately solve biological design problems. We present CRISPR-GPT, an LLM agent system to automate and enhance CRISPR-based gene-editing design and data analysis. CRISPR-GPT leverages the reasoning capabilities of LLMs for complex task decomposition, decision-making, and interactive human-artificial intelligence (AI) collaboration. This system incorporates domain expertise, retrieval techniques, external tools, and a specialized LLM fine-tuned with open-forum discussions among scientists. CRISPR-GPT assists users in selecting CRISPR systems, experiment planning, designing gRNAs, choosing delivery methods, drafting protocols, designing assays, and analyzing data. We showcase the potential of CRISPR-GPT by knocking-out four genes with CRISPR-Cas12a in a human lung adenocarcinoma cell line and epigenetically activating two genes using CRISPR-dCas9 in human melanoma cell line. CRISPR-GPT enables fully AI-guided gene-editing experiment design and analysis across different modalities, validating its effectiveness as an AI co-pilot in genome engineering.

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Qu, Y., Huang, K., Cousins, H., Johnson, W. A., Yin, D., Shah, M. M., Zhou, D., Altman, R. B., Wang, M., Cong, L.. 2024-04-26. CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments. https://doi.org/10.1101/2024.04.25.591003

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