HDDT-powered Diligence-as-Authority
Biotica Bio uses HDDT to test the scientific, commercial, financing, regulatory, and comparator claims behind a life-science opportunity — then converts the evidence into citation-backed reports and AI-search-ready authority pages.
The short version
We test the claims behind a life-science company, then publish the evidence as authority that investors, partners, and AI search can find.
HDDT is the analytical engine. GEO and SEO are the publication and distribution layer. Discoverability is a downstream effect of better authority content, not the product itself.
The problem
Investors need to know which claims must be true, what evidence supports them, what contradicts them, and what remains unresolved. That is a diligence question, not a marketing one.
Traditional SEO does not answer it. Generic AI reports do not answer it either — they produce fluent narratives without making the underlying claims inspectable.
HDDT is designed to make claims inspectable: each one is tested, scored for support and contradiction, and tied to sources.
What Biotica Bio does
The thesis is decomposed into discrete, testable hypotheses across biology, translation, comparators, financing, and regulation.
Each claim is graded for supporting and contradicting evidence, with uncertainty stated rather than hidden.
The reviewed conclusion becomes a citation-backed, machine-readable page that is discoverable to humans and AI systems.
Why HDDT matters
Not a generic SEO agency
Not an unsupervised AI report
How diligence becomes authority
Input evidence
Public literature, filings, and (optionally) supervised dataroom materials.
Hypothesis decomposition
The thesis is broken into discrete, testable claims.
Evidence search
AI-assisted retrieval and synthesis across sources, with human review.
Support / refute scoring
Each claim is graded for supporting and contradicting evidence.
Investor narrative
Findings become an investor-readable diligence conclusion.
Published authority asset
The narrative is published as a citation-backed, structured page.
Visibility measurement
Search and AI-answer discoverability are tracked as a downstream effect.
Who it is for
Need: Translate strong science into claims investors can evaluate.
What they get: A structured account of what must be true, what the evidence shows, and where the story is still unproven.
Need: Independent structure for the claims behind an opportunity.
What they get: Support/refute scoring and comparator failure context that speeds an investment read without replacing judgment.
Need: Consistent diligence signal across a cohort.
What they get: Repeatable HDDT snapshots that make portfolio companies easier to compare and coach.
Need: Credible external framing for early translational assets.
What they get: Citation-backed authority pages that help licensing and financing conversations start from evidence.
Need: A fast, sourced read on an external technology or category.
What they get: Comparator maps and translational risk views that inform partnering and BD decisions.
Example output
| Hypothesis | Evidence support | Evidence against / uncertainty | Confidence | Investor implication |
|---|---|---|---|---|
| The platform has a plausible biological mechanism. | Mechanism is consistent with published extracellular vesicle biology and prior anti-inflammatory cargo work. | Mechanistic support is largely in vitro; causal in vivo confirmation in the target tissue is limited. | Moderate | Plausible enough to justify diligence, but mechanism is not yet independently de-risked. |
| The delivery modality improves therapeutic index over conventional particles. | Early comparisons suggest improved tolerability at comparable exposure in a single model. | No head-to-head dose-ranging against a modern comparator; therapeutic index claim rests on limited data. | Weak | Central differentiation claim is under-evidenced and should be a priority diligence question. |
| The preclinical model is relevant to the proposed indication. | The chosen model is used in the field and captures a key inflammatory axis of the indication. | Model has known translational gaps; several comparators that succeeded here failed later in humans. | Contradicted | Historical failures in this model temper confidence; translational risk is material. |
The platform has a plausible biological mechanism.
ModerateThe delivery modality improves therapeutic index over conventional particles.
WeakThe preclinical model is relevant to the proposed indication.
ContradictedServices
Best for
Founders, angels, accelerators, and early-stage diligence.
A focused test of 5–8 core claims behind a company, technology, or investment thesis.
Deliverables
Best for
Seed-stage biotech companies preparing for investor conversations.
A full diligence narrative that tests the claims investors need to believe before funding the next milestone.
Deliverables
Best for
Biotech companies, funds, university spinouts, and regional innovation groups.
A published web asset that turns diligence into a durable, citation-backed, machine-readable authority page.
Deliverables
Best for
Investors, corporate strategy teams, and founders entering crowded or failed categories.
A research product that identifies what happened to related companies, platforms, indications, financing paths, and clinical programs.
Deliverables
Start with an HDDT Snapshot, or scope a full authority report.