Use when creating biotech pitch decks, translating scientific data for investors, preparing fundraising presentations, or developing investor Q&A. Transforms complex scientific and clinical data into compelling investor narratives for biotech fundraising.
Strategic communication tool that translates complex biotechnology innovations into compelling business narratives optimized for venture capital, pharmaceutical partnerships, and public market investors.
Key Capabilities:
✅ Use this skill when:
❌ Do NOT use when:
lay-summary-genIntegration:
market-access-value (commercial assessment), competitor-trial-monitor (competitive landscape)business-model-canvas (strategy development), investor-relations-prep (ongoing communications)Convert technical concepts into investor-friendly language:
from scripts.narrative_engine import BiotechNarrativeEngine
engine = BiotechNarrativeEngine()
# Translate technical description
translation = engine.translate_science(
technical_description="""
Our proprietary AAV9-based gene therapy utilizes a codon-optimized
transgene under control of a liver-specific promoter to restore
functional enzyme in patients with MPS I deficiency.
""",
audience="generalist_vc",
preserve_accuracy=True
)
print(translation.business_narrative)
# "One-time gene therapy delivering a functional copy of the missing enzyme,
# potentially curing MPS I rather than managing symptoms"
Translation Strategies:
| Technical Concept | Business Translation | Why It Works |
|---|---|---|
| "CRISPR-Cas9 gene editing" | "Precision genetic medicine platform" | Platform implies scalability |
| "Phase II clinical data" | "De-risked asset with human proof-of-concept" | Reduces perceived risk |
| "Off-target effects" | "Industry-leading specificity profile" | Competitive framing |
| "MOA via JAK-STAT pathway" | "Novel mechanism addressing root cause" | Value proposition |
Structure pitch deck flow for maximum impact:
# Generate complete narrative arc
narrative = engine.build_narrative(
company_stage="series_b",
science_type="gene_therapy",
clinical_stage="phase_2",
target_market="rare_disease",
key_differentiation="one_time_cure"
)
# Access each component
print(narrative.hook) # Opening grab
print(narrative.problem) # Market pain point
print(narrative.solution) # Your approach
print(narrative.traction) # Validation to date
print(narrative.ask) # Funding request
Narrative Structure:
Calibrate message depth for funding round:
# Optimize for different stages
seed_narrative = engine.optimize_for_stage(
base_narrative=narrative,
stage="seed",
focus="team_and_vision" # Seed cares about team and big idea
)
series_a_narrative = engine.optimize_for_stage(
base_narrative=narrative,
stage="series_a",
focus="proof_of_concept" # Series A needs validation
)
ipo_narrative = engine.optimize_for_stage(
base_narrative=narrative,
stage="ipo",
focus="commercial_readiness" # IPO requires near-term revenue
)
Stage Requirements:
| Stage | Key Questions | Focus Areas |
|---|---|---|
| Seed ($500K-$2M) | Can you execute? | Team, vision, early validation |
| Series A ($10-30M) | Does it work? | POC data, IP position, market entry |
| Series B ($30-75M) | Will it scale? | Phase 2/3 data, BD traction, team expansion |
| Series C/IPO ($100M+) | Commercial execution | Registration trials, launch prep, revenue path |
Adapt tone and depth for different investor types:
# Calibrate for specific investor
calibrated = engine.calibrate_for_audience(
narrative=narrative,
investor_type="healthcare_vc", # vs "generalist_vc" or "pharma_corp"
technical_depth="moderate", # Depth of scientific detail
risk_tolerance="high" # Early vs late stage framing
)
Investor Types:
Scenario: Phase 2 biotech raising Series B.
# Generate complete pitch narrative
python scripts/main.py \
--science "Small molecule inhibitor targeting mutant KRAS G12C" \
--stage "phase_2" \
--indication "lung_cancer" \
--data "ORR 45%, median PFS 6.5 months" \
--competition "Mirati, J&J" \
--output series_b_narrative.json
Narrative Elements:
Scenario: Novel delivery platform company raising seed.
platform_narrative = engine.generate_platform_narrative(
platform_technology="Lipid nanoparticle for CNS delivery",
differentiator="Crosses BBB with 50x improvement over existing LNPs",
applications=["Alzheimer's", "Parkinson's", "brain_cancer"],
stage="seed",
target="platform_value_creation"
)
Platform Story Arc:
Scenario: Surgical robotics company Series A.
device_narrative = engine.generate_device_narrative(
device_type="surgical_robot",
clinical_benefit="50% reduction in complications, 30% faster recovery",
regulatory_path="510k_de_novo",
reimbursement="CPT_code_established",
stage="series_a"
)
Device-Specific Elements:
Scenario: Out-licensing asset to big pharma.
# Generate BD materials
python scripts/main.py \
--mode partnership \
--asset "Phase 2 ready asset" \
--indication "NASH" \
--data_package "Phase 1b complete, biomarker validated" \
--partner_profile "novo_nordisk" \
--output bd_presentation.json
Partnership Framing:
Building comprehensive fundraising materials:
from scripts.narrative_engine import BiotechNarrativeEngine
from scripts.slide_generator import SlideGenerator
from scripts.qa_prep import QAPreparation
# Initialize
engine = BiotechNarrativeEngine()
slides = SlideGenerator()
qa = QAPreparation()
# Step 1: Generate core narrative
narrative = engine.build_narrative(
company_stage="series_a",
therapeutic_area="oncology",
modality="cell_therapy",
clinical_stage="phase_1",
key_differentiation="allogeneic_off_the_shelf"
)
# Step 2: Create slide-by-slide guidance
slide_guide = slides.generate_guide(
narrative=narrative,
n_slides=12,
include_visual_suggestions=True
)
# Step 3: Prepare Q&A
qa_prep = qa.generate_qa(
narrative=narrative,
investor_type="healthcare_vc",
depth="comprehensive"
)
# Step 4: Export complete package
engine.export_package(
narrative=narrative,
slides=slide_guide,
qa=qa_prep,
output_dir="series_a_pitch_package/"
)
Narrative Quality:
Translation Accuracy:
Investor Alignment:
Before Presentation:
Translation Errors:
❌ Oversimplification → "Our drug cures cancer" (misleading)
❌ Jargon overload → Technical terms without explanation
❌ Hiding risks → No mention of side effects or competition
Narrative Mistakes:
❌ Technology in search of problem → Cool science, no market
❌ Ignoring competition → "We have no competitors"
❌ Unrealistic projections → $10B revenue in Year 3
Stage Mismatch:
❌ Seed deck with Phase 3 projections → Too far ahead
❌ IPO presentation to seed investors → Wrong focus
Available in references/ directory:
vc_presentation_best_practices.md - Venture capital pitch guidelinesbiotech_valuation_models.md - Valuation methodologies by stageregulatory_pathway_guides.md - FDA/EMA approval timelinesmarket_sizing_methodologies.md - TAM/SAM/SOM calculationsinvestor_question_bank.md - Common Q&A by investor typecompetitive_landscape_templates.md - Positioning frameworksLocated in scripts/ directory:
main.py - CLI interface for narrative generationnarrative_engine.py - Core story architecturescience_translator.py - Technical to business translationslide_generator.py - Deck structure and visual guidanceqa_preparation.py - Investor Q&A preparationcompetitive_analyzer.py - Market positioning analysisrisk_framer.py - Risk mitigation messagingstage_optimizer.py - Funding round calibration| Parameter | Type | Default | Required | Description |
|---|---|---|---|---|
--science | string | - | Yes* | Scientific description of technology |
--stage | string | - | Yes* | Funding stage (pre-seed, seed, series-a, etc.) |
--audience | string | - | Yes* | Target audience type (generalist-vc, healthcare-vc, etc.) |
--section | string | - | No | Section to rewrite (hook, problem, solution, etc.) |
--content | string | - | No | Content to rewrite |
--input | string | - | No | Input file path |
--output, -o | string | - | No | Output file path |
*Required depending on subcommand
# Generate narrative from science description
python scripts/main.py generate --science "CRISPR gene therapy for sickle cell" --stage series-a --audience healthcare-vc
# Rewrite specific section
python scripts/main.py rewrite --section technology --content "We use AAV vectors..." --audience generalist-vc
# Analyze existing pitch deck
python scripts/main.py analyze --input pitch.pptx --stage series-a
| Risk Indicator | Assessment | Level |
|---|---|---|
| Code Execution | Python script executed locally | Low |
| Network Access | No external API calls | Low |
| File System Access | Read/write files | Low |
| Data Exposure | May process confidential business info | Medium |
| Regulatory | Does not ensure SEC compliance | Medium |
# Python 3.7+
# No additional packages required (uses standard library)
💼 Business Note: Successful biotech fundraising requires balancing scientific credibility with business appeal. This tool helps structure narratives, but the underlying science and team execution ultimately determine success. Always maintain integrity—overpromising destroys credibility with sophisticated investors.