MetaMind: A multi-agent transformer-driven framework for automated network meta-analyses.

ABSTRACT:

Background

Network meta-analysis (NMA) can compare several interventions at once by combining head-to-head and indirect trial evidence. However, identifying, extracting, and modelling these often takes months, delaying updates in many therapeutic areas.

Objective

To develop and validate MetaMind, an end-to-end, transformer-driven framework that automates NMA processes-including study retrieval, structured data extraction, and meta-analysis execution-while minimizing human input.

Methods

MetaMind integrates Promptriever, a fine-tuned retrieval model, to semantically retrieve high-impact clinical trials from PubMed; a multi-agent LLM architecture--Mixture of Agents (MoA)-- pipeline to extract PICO-structured (Population, Intervention, Comparison, Outcome) endpoints; and

SUBMITTER: Livieratos A 

PROVIDER: S-EPMC12904386 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature