Augmentation for Toxicological Research

A teaser

In modern molecular toxicology, researchers face a critical bottleneck: extracting, indexing, and synthesizing disparate biological, clinical, and structural data from heterogeneous public databases (e.g., NCBI PubMed, PubChem PUG-REST, EMBL-EBI OLS, and AlphaFold) is manual, slow, and prone to cognitive overload. We present a custom full-stack, single-screen interactive Directed Acyclic Graph (DAG) platform designed to orchestrate high-throughput computational toxicology pipelines. By employing an auto-arranging, cable-driven topological sorting algorithm, the system dynamically maps and sequences data-retrieval and synthesis nodes. When multiple modules occupy the same execution level, a user-configurable sequence priority override resolver prevents race conditions and strictly schedules processing. Furthermore, we introduce separated Heuristic Guidelines and API Directives that feed directly into live endpoints and server-side LLM payloads, allowing researchers to inject custom query parameters and constraints. This work demonstrates a highly safe, interactive, and modular environment for rapidly profiling toxic substances while adhering to strict chemical safety guardrails.

Identifying the clinical and structural characteristics of venoms, neurotoxins, and synthetic compounds requires consulting multiple siloed databases. An analyst must typically query PubChem for structural properties, search PubMed for toxicological literature, query ontology databases like ChEBI or Gene Ontology to index biochemical families, fetch 3D structures from AlphaFold, and finally compile a synthesized safety and medical countermeasure profile.

This process is highly disjointed. To address this, we engineered an interactive computational toxicology environment. The platform allows users to model data flows visually using a DAG visual canvas, configure retrieval parameters under double-click menus, and execute complex workflows sequentially. The primary research and engineering objectives of this software are:

  1. Visual Automation of Siloed Pipelines: Unifying chemical property, literature, ontology, and structural coordinate retrieval.
  2. Topologically Sound Execution (Cables and Override Priorities): Running the entire pipeline in a clean, fully sequential sequence determined dynamically by connection “cables”, using manual override priorities exclusively to resolve same-step ties.
  3. Decoupled Rule Injection: Separating qualitative guidelines (Heuristic Guidelines) from precise execution queries (API Directives) to feed downstream APIs and the LLM panel.

Eliminating “UI Slop” and Aesthetic Integrity

In designing this application, we explicitly rejected the modern trend of decorating scientific tools with flashy system logs, ping speeds, or meaningless terminal displays (often referred to in design circles as “tech-larping” or “AI slop”).

The canvas instead relies on deep slate color schemes, Inter typography, and JetBrains Mono accentuation to establish visual authority. Micro-animations (powered by motion) give smooth, spring-based movement to drag-and-drop nodes and connector paths, creating a highly tactile experience.

The software can be tested at this link, after applying for access and being approved.

Call for Co-Authors

Are you a dedicated researcher, writer and someone who can take constructive critique the right way and want to make an impact on the scientific community?

The paper “Nilsson, J.-P. (2026). The Cognitive Exoskeleton: A Structured Pipeline for Augmented Intelligence in Scientific Formulation and Evidence Synthesis. Zenodo. (https://doi.org/10.5281/zenodo.19951693)” is under Peer Review and upon feedback there might be a need for an extra hand to addres the concerns and meet the deadline.

There is also another project that involves developing a software solution (PECO-Buddy) to assist researchers in formulating research questions, which also include being part of a group that writes the webinar and research letter for said project. Contact the project lead at email jan-p.nilsson@resintox.org for more information.

The Cognitive Exoskeleton is an external spinoff-commentary from the PECO-Buddy project, which is developed with Evidence-Based Toxicology Collaboration.