Viral Sentry AI (VirSentAI) - Automated Zoonotic Surveillance & Drug Repurposing Agent

Abstract

Zoonotic viruses capable of jumping from animal reservoirs into human populations represent a persistent and unpredictable menace to global health. To confront this challenge, we developed Viral Sentry AI (VirSentAI), an autonomous agent designed to close the gap between viral emergence and therapeutic response. Unlike static analysis tools, VirSentAI operates as a continuous sentinel, automatically scanning public databases (e.g., NCBI) for new viral genomes and executing a three-stage agentic surveillance workflow, with distinct, specialized AI architectures for generated text, macromolecule sequences, and drug chemical data. First, the system is using gemma-2-9b, utilizing this Large Language Model to parse unstructured submission records and extract critical meta-information that provides context to the raw data. In the second stage, the system employs a novel deep-learning topology, virsentai-v2-hyena-dna-16k, a fine-tuned HyenaDNA model capable of processing complete viral genomes up to 160,000 bases. This architecture captures subtle, long-range genomic dependencies to predict human infectivity with high precision. Upon flagging a high-risk pathogen, the agent autonomously triggers a downstream therapeutic module as the stage three. It extracts NCBI viral protein sequences and utilizes a PLAPT (Protein-Ligand Affinity Prediction Transformer) model to calculate affinity interactions against the ChEMBL-curated set of approved therapeutics, instantly identifying candidates for drug repurposing. In rigorous cross-validation on a curated dataset of 31,728 complete viral genomes, the surveillance module demonstrated robust discriminatory power, achieving an AUROC of 0.95 in classifying human host potential. By integrating state-of-the-art genomic modeling with automated lead compound screening, VirSentAI offers a proactive, end-to-end solution for pandemic preparedness. The platform is freely accessible at https://muntisa.github.io/virsentai, with source code available at https://github.com/muntisa/virsentai.

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