ChatGPT Plugin

Inductive

State-of-the-art ADMET models

Brand: Inductive Bio

Category: AI
Primary Subcategory: Scientific & Biomedical Research Data

Integration details

Description

Inductive's absorption, distribution, metabolism, excretion, and toxicity (ADMET) models predict the chemical and pharmacokinetic properties that determine whether a molecule can become a viable drug. By surfacing these predictions directly in your conversation, scientists can evaluate compounds, triage ideas, and prioritize which molecules to synthesize, without leaving their existing workflow. Through this MCP server, users can access Inductive’s models for the physicochemical properties LogD (lipophilicity) and pKa (acid/base ionization), key drivers of solubility and permeability.

Integration type: Plugin
Verification status: Not applicable
Platform: ChatGPT
Category: AI
Primary Subcategory: Scientific & Biomedical Research Data
Secondary Subcategories: None listed
Brand: Inductive Bio
Access: Account required
First tracked: 2026-08-21
Tool count: 2
Market: US

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Primary Subcategory

Competing in ChatGPT Scientific & Biomedical Research Data

View Category

Listed in alphabetical order

Primary Subcategory

Biohub ESMComing soonGet notified

ClairwaveComing soonGet notified

ClinicalTrials.govComing soonGet notified

Dewey DataComing soonGet notified

G-RESComing soonGet notified

InductiveComing soonGet notified

Tools

2 tools agents can invoke

List the molecular property prediction models you can run (for example global logD and pKa). Returns each model's id, assay name, and units. Use the returned model ids with predict_properties. Backed by the Inductive Bio prediction API.
list_available_models
Predict molecular properties for one or more molecules using Inductive Bio's models. Provide up to 25 SMILES strings and up to 10 model ids to run (from list_available_models); returns predicted values per molecule and model. Backed by the Inductive Bio prediction API.
predict_properties

FAQs

Inductive ChatGPT Plugin FAQ

How the directory, categories and Discoverability Score work.

Read the methodology

How do I improve Inductive's ChatGPT Plugin discoverability?

The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.

What are Inductive alternatives on ChatGPT?

As of 2026-11-02, Inductive competes with Biohub ESM, Clairwave, ClinicalTrials.gov, Dewey Data, G-RES, Genomic Intelligence, GovBot County Hazards, Helical Platform and 10 more in ChatGPT Scientific & Biomedical Research Data, ranked by public Discoverability Score.

Where is this profile measured?

This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.