ClawKit Logo
ClawKitReliability Toolkit
Back to Registry
Official Verified

pharmaclaw-market-intel-agent

Fetches and analyzes FAERS (FDA Adverse Event Reporting System) data from openFDA API. Supports drug names and SMILES (resolves via PubChem). Generates: events list, yearly trends (counts), top reactions/outcomes as JSON + matplotlib bar chart PNGs.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/cheminem/pharmaclaw-market-intel-agent
Or

Pharma Market Intel Agent - FAERS Query Skill

Overview

Query real-world post-market safety data for drugs. Useful for market intel on safety profiles, emerging risks, competitor analysis.

Key outputs:

  • JSON summaries (trends, top reactions/outcomes)
  • PNG bar charts (yearly reports, top 10 reactions/outcomes)
  • Sample recent events

Rate limits: openFDA ~240 req/min. Counts are fast (no full data).

Chemistry-Query Structure

Parse user queries into this model for standardized chaining:

from dataclasses import dataclass
from typing import List, Optional

@dataclass
class ChemistryQuery:
    drug: str  # Drug name or SMILES
    query_type: str = 'faers'  # 'faers', 'pubchem', etc.
    metrics: Optional[List[str]] = None  # ['yearly_trends', 'top_reactions', 'top_outcomes', 'events']
    limit_events: int = 20

Example:

{
  \"drug\": \"aspirin\",  // or \"CC(=O)OC1=CC=CC=C1C(=O)O\"
  \"query_type\": \"faers\",
  \"metrics\": [\"yearly_trends\", \"top_reactions\"]
}

Quick Start / Workflows

1. Basic Query (All Metrics)

exec skills/pharma-market-intel-agent/scripts/query_faers.py --drug aspirin --output ./aspirin_faers

Generates:

  • aspirin_faers/aspirin_summary.json
  • *.png plots
  • Recent events JSON

2. SMILES Input

exec ... --drug \"CC(=O)OC1=CC=CC=C1C(=O)O\"  # Aspirin SMILES

Auto-resolves to name via PubChem.

3. Custom Limit

exec ... --drug ozempic --limit-events 50 --output ozempic_analysis

Chaining Examples

  • With chemistry-query: Resolve/validate SMILES first, then FAERS.
  • pharma-tox-agent: Feed top reactions for tox prediction.
  • pharma-ip-expansion-agent: Check safety for IP expansion targets.
  • traction-agent: Market risk scoring from FAERS trends.
# Agent workflow:
1. Parse ChemistryQuery
2. Resolve SMILES if needed (pubchempy or query_faers handles)
3. Run query_faers.py
4. Read PNGs/JSONs into response
5. Chain if metrics require

ClinicalTrials.gov Integration

Query clinical trial data from ClinicalTrials.gov API v2. Search by drug, condition, phase, and status. No API key needed.

Quick Start

# Search by drug
exec skills/pharma-market-intel-agent/scripts/query_trials.py --drug "sotorasib" --output ./sotorasib_trials

# Search by condition + filters
exec ... --condition "breast cancer" --phase PHASE3 --status RECRUITING --limit 10 --output ./bc_trials

# Search by both
exec ... --drug "pembrolizumab" --condition "NSCLC" --output ./pembro_trials

# SMILES input (auto-resolves via PubChem)
exec ... --drug "CC(=O)OC1=CC=CC=C1C(=O)O" --output ./aspirin_trials

Outputs

  • {drug}_trials_summary.json — Full structured summary with trials list and aggregate stats
  • {drug}_trials_by_phase.png — Bar chart by phase
  • {drug}_trials_by_status.png — Bar chart by status
  • {drug}_trials_timeline.png — Timeline of trial start dates

Metadata

Author@cheminem
Stars3875
Views1
Updated2026-04-07
View Author Profile
AI Skill Finder

Not sure this is the right skill?

Describe what you want to build — we'll match you to the best skill from 16,000+ options.

Find the right skill
Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-cheminem-pharmaclaw-market-intel-agent": {
      "enabled": true,
      "auto_update": true
    }
  }
}
Safety NoteClawKit audits metadata but not runtime behavior. Use with caution.

Related Skills

pharmaclaw-pharmacology-agent

Pharmacology agent for ADME/PK profiling of drug candidates from SMILES. Computes drug-likeness (Lipinski Ro5, Veber rules), QED, SA Score, ADME predictions (BBB permeability, aqueous solubility, GI absorption, CYP3A4 inhibition, P-gp substrate, plasma protein binding), and PAINS alerts. Chains from chemistry-query for SMILES input. Triggers on pharmacology, ADME, PK/PD, drug likeness, Lipinski, absorption, distribution, metabolism, excretion, BBB, solubility, bioavailability, lead optimization, drug profiling.

cheminem 3875

pharmaclaw-catalyst-design

Organometallic catalyst recommendation and novel ligand design for drug synthesis reactions. Recommends catalysts (Pd, Ru, Rh, Ir, Ni, Cu, Zr, Fe) for reaction types (Suzuki, Heck, Buchwald-Hartwig, metathesis, hydrogenation, click, etc.) from curated database with scoring. Designs novel ligand variants via RDKit (steric, electronic, bioisosteric modifications). Chains from chemistry-query/retrosynthesis (receives reaction type + substrate) and feeds into IP Expansion (novel ligands as patentable inventions). Triggers on catalyst, ligand, organometallic, cross-coupling catalyst, reaction conditions, catalyst selection, ligand design, cone angle, bite angle, phosphine, NHC, palladium catalyst, ruthenium catalyst.

cheminem 3875

chemistry-query

Chemistry agent skill for PubChem API queries (compound info/properties, structures/SMILES/images, synthesis routes/references) + RDKit cheminformatics (SMILES to molecule props/logP/TPSA, 2D PNG/SVG viz, Morgan fingerprints, retrosynthesis/BRICS disconnects, multi-step synth planning). Use for chemistry tasks involving compounds, molecules, structures, PubChem data, RDKit analysis, SMILES processing, synthesis routes, retrosynthesis, reaction simulation. Triggers on chemistry, compounds, molecules, chemical data/properties, PubChem, RDKit, SMILES, structures, synthesis, reactions, retrosynthesis, synth plan/route.

cheminem 3875

Drug Team

Skill by cheminem

cheminem 3875

pharma-pharmacology-agent

Pharmacology agent for ADME/PK profiling of drug candidates from SMILES. Computes drug-likeness (Lipinski Ro5, Veber rules), QED, SA Score, ADME predictions (BBB permeability, aqueous solubility, GI absorption, CYP3A4 inhibition, P-gp substrate, plasma protein binding), and PAINS alerts. Chains from chemistry-query for SMILES input. Triggers on pharmacology, ADME, PK/PD, drug likeness, Lipinski, absorption, distribution, metabolism, excretion, BBB, solubility, bioavailability, lead optimization, drug profiling.

cheminem 3875