blockbuster-therapy-predictor

Predict which early-stage biotechnology platforms (PROTAC, mRNA, gene editing, etc.) have the highest potential to become blockbuster therapies. Analyzes clinical trial progression, patent landscape maturity, and venture capital funding trends to generate investment and R&D prioritization scores. Trigger when: User asks about technology investment potential, platform selection, or therapeutic modality comparison.

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Repository: GeorgeDoors888/GB-Power-Market-JJ
Last source activity: April 16, 2026 at 00:11
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name	blockbuster-therapy-predictor
description	Predict which early-stage biotechnology platforms (PROTAC, mRNA, gene editing, etc.) have the highest potential to become blockbuster therapies. Analyzes clinical trial progression, patent landscape maturity, and venture capital funding trends to generate investment and R&D prioritization scores. Trigger when: User asks about technology investment potential, platform selection, or therapeutic modality comparison.
version	1.0.0
category	Pharma
tags	["investment","prediction","biotech","clinical-trials","patents"]
author	AIPOCH
license	MIT
status	Draft
risk_level	Medium
skill_type	Tool/Script
owner	AIPOCH
reviewer
last_updated	2026-02-15

Blockbuster Therapy Predictor

Comprehensive analytics tool for forecasting breakthrough therapeutic technologies by integrating multi-dimensional data sources including clinical development pipelines, intellectual property landscapes, and capital market indicators.

Features

Multi-Source Data Integration: Aggregates clinical trials, patents, and funding data
Predictive Scoring: Calculates Blockbuster Index combining maturity, market potential, and momentum
Technology Landscape Mapping: Tracks 10+ emerging therapeutic platforms
Investment Intelligence: Provides data-driven R&D and investment recommendations
Trend Analysis: Identifies acceleration patterns and inflection points

Usage

Basic Usage

# Run complete analysis with all technologies
python scripts/main.py

# Analyze specific technologies
python scripts/main.py --tech PROTAC,mRNA,CRISPR

# Output in JSON format
python scripts/main.py --output json

Parameters

Parameter	Type	Default	Required	Description
`--mode`	str	full	No	Analysis mode: full or quick
`--tech`	str	None	No	Comma-separated list of technologies to analyze
`--output`	str	console	No	Output format: console or json
`--threshold`	float	0	No	Minimum blockbuster index threshold (0-100)
`--save`	str	None	No	Save report to file path

Advanced Usage

# Analyze high-potential technologies only (index ≥70)
python scripts/main.py \
  --threshold 70 \
  --output json \
  --save high_potential_report.json

# Quick analysis of specific platforms
python scripts/main.py \
  --mode quick \
  --tech CAR-T,ADC,Bispecific \
  --output console

🏆 BLOCKBUSTER THERAPY PREDICTOR Report
Generated: 2026-02-15 10:30:00
Technologies analyzed: 10

📊 Technology Rankings
Rank  Technology       Blockbuster Index    Maturity    Market Potential    Momentum    Recommendation
🥇 1   mRNA             85.2                 78.5        92.1                88.0        Strongly Recommended
🥈 2   CAR-T            82.3                 85.2        78.5                75.0        Strongly Recommended
🥉 3   CRISPR           79.8                 72.3        88.2                68.0        Recommended

{
  "generated_at": "2026-02-15T10:30:00",
  "total_routes": 10,
  "rankings": [
    {
      "rank": 1,
      "tech_name": "mRNA",
      "blockbuster_index": 85.2,
      "maturity_score": 78.5,
      "market_potential_score": 92.1,
      "momentum_score": 88.0,
      "recommendation": "Strongly Recommended",
      "key_drivers": ["Multiple Phase III trials", "Rapid patent growth"],
      "risk_factors": ["Regulatory uncertainties"],
      "timeline_prediction": "First product expected in 2-4 years"
    }
  ]
}

Blockbuster Index = (Market Potential × 0.5) + (Maturity × 0.3) + (Momentum × 0.2)

Blockbuster Index	Recommendation	Action
≥ 80	Strongly Recommended	Prioritize R&D investment
60-79	Recommended	Active monitoring and early partnerships
40-59	Watch	Monitor milestones; reassess in 6-12 months
< 40	Cautious	Minimal investment; consider divestment

Technology	Category	Description
PROTAC	Protein Degradation	Proteolysis Targeting Chimera
mRNA	Nucleic Acid Drugs	Messenger RNA therapy platform
CRISPR	Gene Editing	CRISPR-Cas gene editing technology
CAR-T	Cell Therapy	Chimeric Antigen Receptor T-cell therapy
Bispecific	Antibody Drugs	Bispecific antibody technology
ADC	Antibody Drugs	Antibody-Drug Conjugate
RNAi	Nucleic Acid Drugs	RNA interference therapy
Gene Therapy	Gene Therapy	AAV vector gene therapy
Allogeneic	Cell Therapy	Universal/Allogeneic cell therapy
Cell Therapy	Cell Therapy	General cell therapy platform

pip install -r requirements.txt

dataclasses
enum

Risk Indicator	Assessment	Level
Code Execution	Python scripts executed locally	Medium
Network Access	No external API calls in mock mode	Low
File System Access	Read/write report files only	Low
Instruction Tampering	Standard prompt guidelines	Low
Data Exposure	Output files saved to workspace	Low

# Python dependencies
pip install -r requirements.txt