🧬 Pharmaceutical AI Agent

Comprehensive Visual Architecture Flows for Medical Affairs Research System

🔄 Complete System Flow

📋 Overview

This comprehensive diagram shows the complete end-to-end journey from user input to final report delivery, including all system components and their interactions.

  • User Interface Steps: Molecule selection → Indication discovery → Country selection
  • Backend Processing: Multi-agent analysis → Independent sections → Quality assurance
  • Technical Infrastructure: Session management → LLM integration → Storage systems
  • Quality Control: Citation verification → Medical review → Compliance checks
graph TD %% User Interface Layer A[User Login] --> B[New Analysis Dashboard] B --> C[Molecule Selection] %% Step 1: Molecule Selection C --> D{Select Data Source} D -->|GBQ Database| E[GBQ Molecule Search] D -->|DailyMed FDA| F[FDA Label Search] E --> G[Molecule: Empagliflozin Selected] F --> G %% Step 2: Indication Discovery G --> H[AI Discovers Related Indications] H --> I[User Selects Indications] I --> J["Selected: Type 2 Diabetes
Heart Failure
Chronic Kidney Disease"] %% Step 3: Drug Class & Product Comparison J --> K[AI Suggests Comparisons] K --> L[Drug Class Comparison] K --> M[Product Comparison] L --> N["GLP-1 Agonists
SGLT2 Inhibitors
DPP4 Inhibitors"] M --> O["Dapagliflozin
Canagliflozin
Ertugliflozin"] %% Step 4: Multi-Country Guidelines N --> P[Select Countries] O --> P P --> Q["United States: ADA Guidelines
Europe: ESC Guidelines
China: CDS Guidelines
India: RSSDI Guidelines
Russia: RDA Guidelines"] %% Step 5: Clinical Studies Q --> R[AI Discovers Clinical Studies] R --> S["Study 1: EMPA-REG OUTCOME
Study 2: CANVAS Program
Study 3: CREDENCE
Study 4: EMPEROR-Reduced
Study 5: DAPA-HF
Study 6: VERTIS CV"] %% Step 6: Document Corpus Formation S --> T[Document Corpus Created] T --> U["Total Documents: 247
Data Size: 2.8 GB
Processing Time: 45 min"] %% Backend Processing Architecture U --> V[Long-Running Session Created] V --> W[Background Processing Starts] %% Document Processing Pipeline W --> X[Multi-Method Document Processing] X --> Y[OCR Extraction] X --> Z[Vision LLM Analysis] X --> AA[PDF Structure Parsing] X --> BB[Table Extraction] Y --> CC[Consensus Validation] Z --> CC AA --> CC BB --> CC %% Multi-Agent Analysis CC --> DD[6 Specialized Agents Activated] %% Track A - Clinical Focus DD --> EE[Track A: Clinical Analysis] EE --> FF[Efficacy Analysis Agent] EE --> GG[Safety Profile Agent] EE --> HH[Clinical Evidence Agent] %% Track B - Strategic Focus DD --> II[Track B: Strategic Analysis] II --> JJ[Competitive Landscape Agent] II --> KK[Regulatory Guidelines Agent] II --> LL[Market Access Agent] %% LLM Processing FF --> MM[Claude Opus
Medical Reasoning] GG --> NN[Claude Opus
Safety Analysis] HH --> OO[Claude Sonnet
Evidence Synthesis] JJ --> PP[GPT-4
Competitive Analysis] KK --> QQ[Claude Sonnet
Regulatory Review] LL --> RR[Gemini Pro
Market Analysis] %% Independent Section Generation MM --> SS[Independent Section: Efficacy] NN --> TT[Independent Section: Safety] OO --> UU[Independent Section: Evidence] PP --> VV[Independent Section: Competitive] QQ --> WW[Independent Section: Regulatory] RR --> XX[Independent Section: Market Access] %% Cross-Validation SS --> YY[Cross-Track Validation] TT --> YY UU --> YY VV --> YY WW --> YY XX --> YY %% Citation Verification YY --> ZZ[Citation Integrity Check] ZZ --> AAA[99% Citation Accuracy Verified] %% Report Stitching AAA --> BBB[Intelligent Report Stitching] BBB --> CCC[Consistency Check] BBB --> DDD[Transition Generation] BBB --> EEE[Executive Summary Creation] CCC --> FFF[Final Report Assembly] DDD --> FFF EEE --> FFF %% Quality Assurance FFF --> GGG[Quality Assurance System] GGG --> HHH[Medical Accuracy Review] GGG --> III[Regulatory Compliance Check] GGG --> JJJ[Statistical Validation] GGG --> KKK[Language Quality Check] HHH --> LLL{QA Score > 90%?} III --> LLL JJJ --> LLL KKK --> LLL LLL -->|No| MMM[Human Expert Review] LLL -->|Yes| NNN[Report Ready for Delivery] MMM --> NNN %% Final Delivery NNN --> OOO[Multi-Format Report Generation] OOO --> PPP[PDF Report] OOO --> QQQ[Excel Data Tables] OOO --> RRR[Interactive Dashboard] %% User Notification PPP --> SSS[User Notification] QQQ --> SSS RRR --> SSS SSS --> TTT[Analysis Complete
Ready for Download] %% Progress Tracking (Parallel Process) V --> UUU[Real-Time Progress Tracking] UUU --> VVV["Progress: 0% - Initialization
Progress: 25% - Document Collection
Progress: 50% - Processing
Progress: 75% - Analysis
Progress: 100% - Complete"] %% Error Handling & Recovery W --> WWW[Session Monitoring] WWW --> XXX{Session Healthy?} XXX -->|No| YYY[Auto-Recovery] XXX -->|Yes| ZZZ[Continue Processing] YYY --> ZZZ %% Data Storage Architecture T --> AAAA[Distributed Storage] AAAA --> BBBB[Redis: Session Metadata] AAAA --> CCCC[PostgreSQL: Persistence] AAAA --> DDDD[MinIO: Large Documents] %% Styling classDef userInterface fill:#e1f5fe,stroke:#01579b,stroke-width:2px classDef dataSource fill:#f3e5f5,stroke:#4a148c,stroke-width:2px classDef processing fill:#e8f5e8,stroke:#1b5e20,stroke-width:2px classDef aiAgent fill:#fff3e0,stroke:#e65100,stroke-width:2px classDef llmModel fill:#fce4ec,stroke:#880e4f,stroke-width:2px classDef quality fill:#f1f8e9,stroke:#33691e,stroke-width:2px classDef storage fill:#e3f2fd,stroke:#0d47a1,stroke-width:2px classDef output fill:#f9fbe7,stroke:#827717,stroke-width:2px class A,B,C,I,P userInterface class D,E,F,G dataSource class X,Y,Z,AA,BB,CC,W processing class FF,GG,HH,JJ,KK,LL,DD,EE,II aiAgent class MM,NN,OO,PP,QQ,RR llmModel class GGG,HHH,III,JJJ,KKK,LLL,MMM quality class AAAA,BBBB,CCCC,DDDD storage class PPP,QQQ,RRR,TTT output
247
Documents Processed
2.8GB
Data Volume
6
Specialized Agents
99%
Citation Accuracy

👤 User Journey Flow

🎯 Detailed 7-Step User Journey

This diagram shows the complete user workflow with dynamic corpus expansion and multi-source data integration.

  • Step 1: User enters molecule name (GBQ + FDA/DailyMed)
  • Step 2: LLM discovers indications → User multi-selects
  • Step 3: System populates drug class + similar molecules
  • Step 4: Corpus auto-expands with similar molecule data
  • Step 5: LLM searches 5-region guidelines + User fills gaps
  • Step 6: Clinical studies categorized → User selects
  • Step 7: Full analysis engine launches → Multi-format reports
graph TD %% Detailed 7-Step User Journey Flow A[👤 User Login] --> B[🏠 Dashboard] %% Step 1: Molecule Entry B --> C1[📝 Step 1: Enter Molecule Name] C1 --> C2[🔍 Search GBQ + FDA/DailyMed] C2 --> C3[💊 Empagliflozin Found] %% Step 2: Indication Discovery C3 --> D1[🧠 Step 2: LLM Discovers Indications] D1 --> D2[📋 AI Analysis:
• Inherent Knowledge
• GBQ Corpus
• FDA Data] D2 --> D3[✅ User Multi-Selects:
• Type 2 Diabetes
• Heart Failure
• CKD] %% Step 3: Drug Class & Product Comparison D3 --> E1[⚖️ Step 3: System Populates] E1 --> E2[🏷️ Drug Class: SGLT2 Inhibitors] E2 --> E3[🔄 Similar Molecules:
• Dapagliflozin
• Canagliflozin
• Ertugliflozin] %% Step 4: Corpus Auto-Expansion E3 --> F1[📈 Step 4: Corpus Auto-Expands] F1 --> F2[🔄 Parallel Data Collection] F2 --> F3[📚 Similar Molecule Data Added
from GBQ + FDA] %% Step 5: Geographic Guidelines F3 --> G1[🌍 Step 5: Geographic Guidelines] G1 --> G2[🔍 LLM Web Search:
• US • EU • APAC
• LATAM • MEA] G2 --> G3[📤 User Uploads Gap Documents] G3 --> G4[📋 5-Region Guidelines Complete] %% Step 6: Clinical Studies G4 --> H1[📊 Step 6: Clinical Studies] H1 --> H2[🔍 Web Search + Categorization] H2 --> H3[📑 Categories:
• Phase I/II/III
• RWE • Meta-Analyses
• Safety • Efficacy] H3 --> H4[✅ User Selects Studies] %% Step 7: Full Analysis H4 --> I1[🚀 Step 7: Analysis Engine Launches] I1 --> I2[🤖 Multi-Agent Processing
Vertex AI + Azure AI + Claude] I2 --> I3[📈 Progress Tracking 0-100%] I3 --> I4[📋 Multi-Format Reports
PDF • XML • Interactive] %% Styling classDef step fill:#e3f2fd,stroke:#1976d2,stroke-width:3px classDef llm fill:#fff3e0,stroke:#f57c00,stroke-width:2px classDef user fill:#e8f5e8,stroke:#2e7d32,stroke-width:2px classDef system fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px classDef final fill:#ffebee,stroke:#c62828,stroke-width:3px class C1,D1,E1,F1,G1,H1,I1 step class D2,G2,H2,I2 llm class D3,G3,H4 user class E2,E3,F2,F3,G4,H3 system class I4 final class A,B start class C,D,E,F,G,H,I selection class J,K processing class L,M,N,O progress class P,Q,R,S,T complete

🎯 Intelligent Suggestions

AI automatically discovers relevant indications and suggests optimal comparisons

🌍 Global Coverage

Multi-country regulatory guidelines and approval status tracking

📈 Real-Time Progress

Live updates on analysis progress with detailed status information

📋 Multiple Formats

Professional reports in PDF, Excel, and interactive dashboard formats

⚙️ Technical Architecture Flow

🏗️ Backend System Architecture

This diagram shows the comprehensive backend system architecture with all technical components and their interactions.

  • Frontend Layer: React dashboard + REST API gateway
  • Session Management: Redis + PostgreSQL + MinIO for GB-scale data
  • Multi-Agent System: 6 specialized agents with parallel processing tracks
  • Quality Assurance: Citation validation + medical review + compliance checks
  • Background Processing: Celery workers for long-running analytical tasks
graph TB %% Frontend Layer subgraph "Frontend Layer" UI[React Dashboard] API[REST API Gateway] end %% Session Management Layer subgraph "Session Management" SM[Session Manager] Redis[(Redis Cache)] PG[(PostgreSQL)] MinIO[(MinIO Storage)] end %% Data Sources Layer subgraph "Data Sources" GBQ[Google BigQuery] DM[DailyMed API] GL[Guidelines Sources] CS[Clinical Studies] end %% LLM Integration Layer subgraph "LLM Integration" LM[LiteLLM Manager] GPT[OpenAI GPT-4] Claude[Vertex AI Claude] Gemini[Vertex AI Gemini] GSDK[Google AI SDK] end %% Processing Layer subgraph "Document Processing" DP[Document Processor] OCR[OCR Engine] VLM[Vision LLM] TE[Table Extractor] CV[Consensus Validator] end %% Multi-Agent System subgraph "Multi-Agent System" direction TB AO[Agent Orchestrator] subgraph "Track A - Clinical" EA[Efficacy Agent] SA[Safety Agent] CE[Evidence Agent] end subgraph "Track B - Strategic" CA[Competitive Agent] RA[Regulatory Agent] MA[Market Access Agent] end end %% Independent Section Generation subgraph "Section Generation" ISG[Independent Section Generator] ES[Efficacy Section] SS[Safety Section] CS2[Competitive Section] RS[Regulatory Section] EVS[Evidence Section] MAS[Market Section] end %% Quality Assurance subgraph "Quality Assurance" QAS[QA System] CV2[Citation Validator] MR[Medical Reviewer] RC[Regulatory Compliance] HR[Human Review Queue] end %% Report Generation subgraph "Report Generation" IRS[Intelligent Report Stitcher] CC[Consistency Checker] TG[Transition Generator] ESG[Executive Summary Generator] RF[Report Formatter] end %% Background Processing subgraph "Background Processing" Celery[Celery Workers] TaskQueue[Task Queue] Monitor[Session Monitor] end %% Flow Connections UI --> API API --> SM SM --> Redis SM --> PG SM --> MinIO %% Data Collection SM --> GBQ SM --> DM SM --> GL SM --> CS %% Document Processing Flow GBQ --> DP DM --> DP GL --> DP CS --> DP DP --> OCR DP --> VLM DP --> TE OCR --> CV VLM --> CV TE --> CV %% LLM Integration CV --> LM LM --> GPT LM --> Claude LM --> Gemini LM --> GSDK %% Agent Processing LM --> AO AO --> EA AO --> SA AO --> CE AO --> CA AO --> RA AO --> MA %% Section Generation EA --> ISG SA --> ISG CE --> ISG CA --> ISG RA --> ISG MA --> ISG ISG --> ES ISG --> SS ISG --> CS2 ISG --> RS ISG --> EVS ISG --> MAS %% Quality Assurance Flow ES --> QAS SS --> QAS CS2 --> QAS RS --> QAS EVS --> QAS MAS --> QAS QAS --> CV2 QAS --> MR QAS --> RC QAS --> HR %% Report Generation Flow QAS --> IRS IRS --> CC IRS --> TG IRS --> ESG CC --> RF TG --> RF ESG --> RF %% Background Processing SM --> Celery Celery --> TaskQueue TaskQueue --> Monitor Monitor --> API %% Final Output RF --> MinIO MinIO --> API API --> UI %% Styling classDef frontend fill:#e3f2fd,stroke:#1976d2,stroke-width:2px classDef session fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px classDef data fill:#e8f5e8,stroke:#388e3c,stroke-width:2px classDef llm fill:#fff3e0,stroke:#f57c00,stroke-width:2px classDef processing fill:#fce4ec,stroke:#c2185b,stroke-width:2px classDef agents fill:#e0f2f1,stroke:#00695c,stroke-width:2px classDef quality fill:#f1f8e9,stroke:#558b2f,stroke-width:2px classDef background fill:#e8eaf6,stroke:#3f51b5,stroke-width:2px class UI,API frontend class SM,Redis,PG,MinIO session class GBQ,DM,GL,CS data class LM,GPT,Claude,Gemini,GSDK llm class DP,OCR,VLM,TE,CV processing class AO,EA,SA,CE,CA,RA,MA agents class QAS,CV2,MR,RC,HR quality class Celery,TaskQueue,Monitor background

🚀 Scalable Architecture

Microservices-based design with horizontal scaling capabilities

🔄 Parallel Processing

Multi-track agent processing for enhanced speed and accuracy

💾 Distributed Storage

Redis, PostgreSQL, and MinIO for optimal data management

🤖 Multi-LLM Integration

LiteLLM for seamless integration with GPT-4, Claude, and Gemini

📊 Data Flow Diagram

📈 Dynamic Corpus Expansion & Processing Pipeline

This diagram shows how the corpus dynamically expands at multiple stages and data flows through progressive transformations.

  • Stage 1-2: Initial molecule + indication data collection
  • Stage 4: Auto-expansion with similar molecule data
  • Stage 5: Geographic guideline collection (5 regions)
  • Stage 6: Clinical studies categorization and selection
  • Processing: Multi-method extraction with web-grounded search
  • Analysis: Multi-agent processing with cross-validation
flowchart TD %% Stage 1-2: Initial Data subgraph "Stage 1-2: Initial Corpus" USER["👤 User Input:
Molecule: Empagliflozin"] IND["🧠 LLM Discovers Indications:
T2D, HF, CKD"] INIT["📚 Initial Corpus:
GBQ: 25 docs
FDA: 8 docs"] end %% Stage 4: Similar Molecules subgraph "Stage 4: Auto-Expansion" SIM["🔄 Similar Molecules Found:
Dapagliflozin, Canagliflozin
Ertugliflozin"] EXP1["📈 Corpus Expands:
+45 GBQ docs
+12 FDA labels"] CORPUS1["📚 Expanded Corpus: 90 docs"] end %% Stage 5: Geographic Guidelines subgraph "Stage 5: Geographic Guidelines" GEO["🌍 5-Region Search:
US • EU • APAC • LATAM • MEA"] WEB1["🔍 Web Search + Scrapers"] GAPS["📤 User Fills Gaps"] GUIDE["📋 Guidelines Added:
+85 documents"] end %% Stage 6: Clinical Studies subgraph "Stage 6: Clinical Studies" CLIN["📊 Web Search Clinical Studies"] CAT["📑 AI Categorization:
Phase I/II/III • RWE
Safety • Efficacy"] SEL["✅ User Selection"] STUD["📈 Studies Added:
+67 documents"] end %% Final Corpus subgraph "Complete Corpus" FINAL_CORPUS["📚 Final Corpus:
242 Documents • 2.8 GB
Multi-Source • Multi-Format"] end %% Document Processing subgraph "Processing Phase" PROC["🔄 Multi-Method Processing"] TEXT["📝 Text Extraction"] TABLES["📊 Table Data: 156 tables"] IMAGES["🖼️ Image Analysis: 89 figures"] META["🏷️ Metadata: Citations, Sources"] CORPUS["📚 Structured Corpus
Ready for Analysis"] end %% AI Analysis subgraph "AI Analysis Phase" AGENTS["🤖 6 Specialized Agents"] subgraph "Clinical Track" EFF["💊 Efficacy Data:
Primary endpoints
Secondary outcomes
Subgroup analyses"] SAF["⚠️ Safety Data:
Adverse events
Laboratory values
Drug interactions"] EVI["📈 Evidence Synthesis:
Meta-analyses
Real-world data
Quality assessment"] end subgraph "Strategic Track" COMP["⚖️ Competitive Analysis:
Market positioning
Head-to-head comparisons
Pricing strategies"] REG["🏛️ Regulatory Status:
Approval timelines
Label differences
Guidelines positioning"] MKT["💼 Market Access:
Reimbursement status
Health economics
Payer perspectives"] end end %% Section Generation subgraph "Section Generation" INDEP["🔒 Independent Sections"] SEC1["📋 Efficacy Section
12 pages, 45 citations"] SEC2["📋 Safety Section
8 pages, 32 citations"] SEC3["📋 Competitive Section
10 pages, 28 citations"] SEC4["📋 Regulatory Section
15 pages, 67 citations"] SEC5["📋 Evidence Section
9 pages, 38 citations"] SEC6["📋 Market Section
7 pages, 21 citations"] end %% Quality Assurance subgraph "Quality Assurance" QA["✅ Quality Validation"] CITE["🔍 Citation Check:
231 of 231 verified"] MED["🩺 Medical Review:
Accuracy score: 96%"] COMP2["📊 Compliance Check:
All requirements met"] CONF["📈 Confidence Score: 94%"] end %% Report Assembly subgraph "Report Assembly" STITCH["🧩 Intelligent Stitching"] EXEC["📄 Executive Summary
2 pages"] TOC["📑 Table of Contents"] MAIN["📖 Main Report
61 pages total"] APPEND["📎 Appendices
Data tables, references"] end %% Final Output subgraph "Output Layer" FINAL["📤 Final Deliverables"] PDF["📄 PDF Report
Professional format"] EXCEL["📊 Excel Workbook
Data tables and charts"] DASH["🖥️ Interactive Dashboard
Web-based exploration"] end %% Flow Connections USER --> DC DC --> DOC1 DC --> DOC2 DC --> DOC3 DC --> DOC4 DC --> DOC5 DC --> DOC6 DOC1 --> TOTAL DOC2 --> TOTAL DOC3 --> TOTAL DOC4 --> TOTAL DOC5 --> TOTAL DOC6 --> TOTAL TOTAL --> PROC PROC --> TEXT PROC --> TABLES PROC --> IMAGES PROC --> META TEXT --> CORPUS TABLES --> CORPUS IMAGES --> CORPUS META --> CORPUS CORPUS --> AGENTS AGENTS --> EFF AGENTS --> SAF AGENTS --> EVI AGENTS --> COMP AGENTS --> REG AGENTS --> MKT EFF --> INDEP SAF --> INDEP EVI --> INDEP COMP --> INDEP REG --> INDEP MKT --> INDEP INDEP --> SEC1 INDEP --> SEC2 INDEP --> SEC3 INDEP --> SEC4 INDEP --> SEC5 INDEP --> SEC6 SEC1 --> QA SEC2 --> QA SEC3 --> QA SEC4 --> QA SEC5 --> QA SEC6 --> QA QA --> CITE QA --> MED QA --> COMP2 QA --> CONF CITE --> STITCH MED --> STITCH COMP2 --> STITCH CONF --> STITCH STITCH --> EXEC STITCH --> TOC STITCH --> MAIN STITCH --> APPEND EXEC --> FINAL TOC --> FINAL MAIN --> FINAL APPEND --> FINAL FINAL --> PDF FINAL --> EXCEL FINAL --> DASH %% Styling classDef input fill:#e8f5e8,stroke:#2e7d32,stroke-width:3px classDef collection fill:#e3f2fd,stroke:#1976d2,stroke-width:2px classDef processing fill:#fff3e0,stroke:#f57c00,stroke-width:2px classDef analysis fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px classDef sections fill:#e0f2f1,stroke:#00695c,stroke-width:2px classDef quality fill:#f1f8e9,stroke:#558b2f,stroke-width:2px classDef assembly fill:#fce4ec,stroke:#c2185b,stroke-width:2px classDef output fill:#e8f5e8,stroke:#388e3c,stroke-width:3px class USER input class DC,DOC1,DOC2,DOC3,DOC4,DOC5,DOC6,TOTAL collection class PROC,TEXT,TABLES,IMAGES,META,CORPUS processing class AGENTS,EFF,SAF,EVI,COMP,REG,MKT analysis class INDEP,SEC1,SEC2,SEC3,SEC4,SEC5,SEC6 sections class QA,CITE,MED,COMP2,CONF quality class STITCH,EXEC,TOC,MAIN,APPEND assembly class FINAL,PDF,EXCEL,DASH output
156
Tables Extracted
89
Figures Analyzed
231
Citations Verified
61
Pages Generated