Research News
Discover PrimeGen: Revolutionizing Primer Design with AI-Powered Agents!
We are thrilled to announce the publication of a groundbreaking paper in
Nature Biomedical Engineering by Dr. Meng Yang, Visiting Faculty at Graduate Affairs, Faculty of Medicine, Chulalongkorn University, and Prof. Nattiya Hirankarn, Associate Dean for Graduate Affairs!
Their latest research introduces PrimeGen, an innovative multi-agent system powered by large language models (LLMs) that is set to transform the labor-intensive process of primer design for targeted next-generation sequencing (tNGS).
What is PrimeGen?
PrimeGen acts as an intelligent co-pilot for scientists, utilizing GPT-4o as its central controller to streamline complex primer design workflows. This sophisticated system coordinates specialized AI agents, each designed to handle specific tasks, including:
- Interactive Search Agent: Efficiently retrieves gene targets from vast databases.
- Primer Agent: Designs primer sequences for various scenarios, ensuring high amplification uniformity and minimizing dimer formation.
- Protocol Agent: Generates executable robot scripts for liquid handling robots, using retrieval-augmented generation (RAG) and prompt engineering.
- Experiment Agent: Equipped with a vision language model (VLM) for real-time anomaly detection and reporting during experiments, capable of self-correction or alerting human operators when needed.
Why is this important?
Traditional primer design is often complex, iterative, and time-consuming, especially for highly multiplexed panels where the risk of primer dimer formation increases exponentially. PrimeGen addresses these challenges by offering an automated, efficient, and highly accurate solution.
The effectiveness of PrimeGen has been experimentally demonstrated across diverse applications, including:
- Whole-genome sequencing of SARS-CoV-2
- Expanded carrier screening for severe hereditary disease genes (accommodating up to 955 amplicons!)
- Drug resistance mutation detection in Mycobacterium tuberculosis (MTB)
- Plasmid sequencing for protein mutant analysis in enzymatic engineering
This development highlights the immense potential of collaborative AI agents, orchestrated by generalist foundation models, to advance biomedical research and accelerate scientific discovery!
#PrimeGen #AIDrivenScience #BiomedicalResearch #PrimerDesign #NextGenSequencing #LLM #ChulalongkornUniversity #NatureBiomedicalEngineering #ResearchNews #Innovation
of the People’s Republic of China’s programme titled ‘National Key
Research and Development Program of China’ (2022YFF1202200)