Back to marketplace
Life Science Research logo
OpenAI

Build Life Science Research agents for evidence synthesis

Create research agents that turn complex biomedical sources into structured evidence handoffs.

Example outcome

Convert a biomedical research question into an evidence brief with sources, caveats, and follow-up experiments or searches.

Agent examples

Workflow guides for Life Science Research

4 guides

Synthesize evidence without losing caveats

Life Science Research workflows in LatchLoop help agents route biomedical questions across specialized resources and prepare evidence-aware summaries. The goal is not to replace expert review, but to organize source context, highlight limitations, and make follow-up research clear.

A strong life sciences agent starts with a precise question: gene function, variant interpretation, pathway evidence, trial landscape, dataset comparison, or literature synthesis. It should separate evidence types, note organism or assay context, and avoid clinical conclusions beyond the available sources.

Use local content to frame responsible research workflows while plugin skills remain in the catalog. These agents pair well with document and project tools when findings need to become a memo, review queue, or research plan.

Start with the literature synthesis workflow below to create an agent that prepares an expert-review-ready evidence brief.

Combine plugins

Build richer agents by pairing Life Science Research with complementary context

Outcome pages can describe combinations: one plugin for source context, another for project tracking, and another for delivery or notifications. Use Life Science Research as one layer in a larger agent workflow when the outcome needs more than one connected app.

Available plugin capabilities

gnomad-graphql-skillproteomexchange-skillgwas-catalog-skilleqtl-catalogue-skillrhea-skillncbi-blast-skillipd-skilluniprot-skill
Get Started

Build as fast as you can think.

LatchLoop works where you do to build with you.