DDforDD
Pharmaceutical Mechanism Intelligence

Understand how drugs work, where they intervene, and what evidence supports them

DDforDD unifies mechanistic biology, clinical trials, FDA labels, company financials, and competitive intelligence in one evidence-grounded platform.

6
Territories
141
Drugs
717+
Trials
2,071+
Claims
13
AI Tools
13
Data Pipelines

Core Capabilities

Five pillars of pharmaceutical intelligence

Mechanism Mapping

253 nodes · 32 pathways · 6 territories

Interactive pathway graphs built on React Flow. Drill from territory to pathway to node to drug. Every edge shows directionality, evidence grade, and source.

Drug Intelligence

141 drugs · 106 approved · 9 FDA label sections

Full drug profiles: mechanism, targets, patents, PK, adverse effects, indication status, headlines, financials. FDA labels downloaded and structured from openFDA.

Evidence Engine

2,071+ claims · 10 evidence grades · contradiction detection

Every claim is traceable to its source: FDA label, Phase 3 RCT, SEC filing, peer review, or preprint. Inspect confidence scores. See where evidence conflicts.

Trial & Commercial Signals

717+ trials · 30+ companies · 3 CI scores

Daily trial sync from ClinicalTrials.gov. Quarterly financials from SEC EDGAR. Target crowding, trial momentum, and evidence strength scores — all decomposable.

AI Analysis & Workspaces

13 AI tools · team workspaces · REST API

Claude-powered insights with structured efficacy extraction from FDA labels. Private team overlays, saved briefings, and a ChatGPT-compatible API.

Platform Tour

From territory to insight in six clicks

1

Choose a Territory

Start with one of 6 therapeutic territories: Immunology, Oncology, Neurology, Gastroenterology, Cardiology, or Endocrinology. Each territory has its own pathway network.

6 territories · 32 pathways · 29–34 drugs each

View territories →
2

Explore a Pathway Map

Open an interactive mechanism graph. See evidence-graded edges, color-coded node types (receptors, enzymes, cytokines, transcription factors), and drug intervention overlays.

253 nodes · 330 edges · 21 drugs per pathway

Open immunology pathways →
3

Drill Into a Drug

Click any drug to see its full profile: mechanism summary, molecular targets, FDA label sections, clinical trial results, patent portfolio, PK parameters, and adverse effects.

141 drugs · 9 FDA label sections · Generate AI Brief button

Browse immunology drugs →
4

Inspect the Evidence

Every claim shows its evidence grade (LABEL_REGULATORY to NEWS_SECONDARY), confidence score, source URL, and extraction method. No black boxes. See where claims conflict.

2,071+ claims · 10 evidence grades · contradiction detection

5

Compare Efficacy & Momentum

Ask the AI assistant to compare drugs within an indication. Get structured tables from FDA label data: primary endpoints, response rates, p-values, enrollment — all pre-extracted.

13 AI tools · PASI 75/90/100 comparisons · NCT-cited sources

6

Save, Brief & Collaborate

Generate analyst-grade briefings with one click. Save to your workspace. Add private notes and watchlists. Export as Markdown or JSON. Query the API programmatically.

Team workspaces · Markdown/JSON export · 8 API endpoints

See PRO features →

Why DDforDD

What makes this different from Citeline, Cortellis, or Evaluate

Mechanism-first, not molecule-list-first

Start from biology, not a drug catalog. Understand how pathways connect before evaluating which drugs intervene where.

Evidence-inspectable, not black-box summarized

Every claim has a grade, a source, and a confidence score. When evidence conflicts, we show the disagreement — not a flattened average.

Structured efficacy from FDA labels, not just linked PDFs

We download, parse, and structure the Clinical Studies section of every FDA label. Primary endpoints, response rates, and p-values are queryable, not buried in 50-page documents.

Commercial + biological + regulatory + temporal in one graph

Company financials, mechanism biology, regulatory status, and trial momentum in one platform. No tab-switching between 4 different tools.

Architecture

What lives under the hood

13 automated pipelines

FDA labels, ClinicalTrials.gov, SEC filings, headlines from 6 sources, patent data, stock prices — all on daily/weekly/quarterly crons

10 evidence grades

LABEL_REGULATORY, PHASE_3_RCT, PHASE_2_RCT, OBSERVATIONAL_HUMAN, PRECLINICAL, COMPANY_DISCLOSURE, PEER_REVIEW, PREPRINT, NEWS_SECONDARY, EXPERT_CURATION

13 AI tools

query_drugs, query_trials, query_financials, query_label, query_efficacy, query_evidence, query_scores, query_graph, query_changes, fetch_clinicaltrials_gov, generate_table, generate_chart, generate_brief

8 public API endpoints

Drugs, trials, indications, companies, scores, evidence — with OpenAPI 3.1.0 spec, compatible with ChatGPT Custom GPTs

Private workspaces

Team annotations, watchlists, saved briefings — private overlays that never leak into public content or AI outputs

Use Cases

Built for people who need answers, not dashboards

Pharma Strategy Lead

Where is the next open space for our portfolio?

Map mechanisms, see unaddressed pathways, and compare competitive intensity by target and indication.

Clinical Development Analyst

Which mechanisms have the strongest clinical evidence for our target indication?

Surface all drugs, trials, and FDA label efficacy data linked to mechanistic nodes — with evidence grading.

Business Intelligence Lead

What are competitors pursuing that we aren't?

Track company portfolios, trial activity, and commercial signals by mechanism or indication. Decomposable CI scores.

Medical Science Liaison

Can I trust this claim about a drug's effect?

Drill down to the original evidence. Every claim is source-linked, graded for reliability, and shows contradiction status.

See It In Action

Three minutes from question to insight

Prefer a live walkthrough? Request one →

Ready to see what you're missing?

Explore the atlas now or request a live walkthrough. We onboard teams weekly.

Ad-free. Independent. Evidence-grounded.