The Augmented Researcher Assistant
A concept for AI-assisted pharmacology literature monitoring
AI-Assisted Research Tooling
A custom AI tool concept designed to automatically scrape newly published pharmacology papers, summarise them, and flag potential drug interactions for a human researcher to review. Not yet built.
- Planned — In Development. Not a built or live tool.
01 — The Problem
Pharmacology literature moves faster than any one researcher can read. Interaction-relevant findings are easy to miss, and an AI that decides on their behalf is not acceptable in a clinical-adjacent context.
02 — Objective
Design an automation that monitors new pharmacology publications, produces structured summaries, and flags possible drug interactions for a human researcher to confirm — never to decide autonomously.
03 — Approach — what I did
- Define the publication sources and retrieval schedule for new pharmacology papers.
- Design the orchestration layer in an automation tool (Make.com, Zapier) or in Python.
- Design a summarisation prompt with a fixed output structure and explicit evidence fields.
- Define the interaction-flagging rules and the review queue a researcher would work through.
04 — Tools used
05 — Process
06 — Output
- A designed architecture and prompt specification. No tool has been built yet.
07 — What I learned
- How pharmacology domain knowledge shapes what an automation should flag rather than decide.
- How to design a human-in-the-loop checkpoint into an automation from the start.
08 — Limitations
- This project is at concept and design stage. Nothing has been built, deployed or tested.
- No papers have been scraped, no summaries generated and no interactions flagged. No example outputs are shown, because none exist yet.
09 — Skills demonstrated
10 — Project evidence
This is a planned project in development. It is presented as a design concept only — there are no results, outputs or screenshots to show.