The method

HDDT: Hypothesis-Driven Diligence Testing

HDDT is the analytical engine behind every Biotica Bio authority asset. It decomposes an opportunity into testable claims, grades the evidence for and against each one, and produces a human-reviewed, source-linked conclusion.

Request an HDDT SnapshotSee a worked example

What HDDT is

A structured test, not a narrative

A generic report tells a story. HDDT tests a set of claims and reports where the evidence supports the story and where it does not.

Every engagement begins with a thesis — the thing an investor, partner, or founder needs to be true. That thesis is broken into discrete hypotheses that can each be examined against evidence.

For each hypothesis we collect supporting and contradicting evidence, grade it, and record the uncertainty. The output is a defensible read that a careful reader can inspect claim by claim.

Coverage

The six diligence dimensions

A full HDDT tests an opportunity across six dimensions. A Snapshot covers the most decision-relevant subset.
01

Biology feasibility

Is the underlying mechanism biologically plausible?

Assess whether the proposed mechanism is consistent with established biology and what would have to hold for it to work in the target context.

02

Translational maturity

How far is the science from a decision-relevant milestone?

Evaluate model relevance, reproducibility signals, and the distance between current data and clinically or commercially meaningful readouts.

03

Comparator and failure-mode analysis

What happened to programs that came before?

Map related companies, platforms, and indications, and characterize the failure modes that a new program must avoid or explain.

04

Financeability and next-investor fit

Is there a credible next financing and a rational next investor?

Review financing history in the category, milestone realism, and whether the story fits the mandate of a plausible next investor.

05

Regulatory and clinical path realism

Is the proposed path to approval realistic?

Consider predicate paths, likely regulatory expectations, and the clinical plan against the maturity of the underlying evidence.

06

Authority asset readiness

Can the evidence be published as a durable, citable asset?

Determine whether conclusions are source-linked, uncertainty-aware, and structured enough to become a machine-readable authority page.

Evidence grading

How each claim is scored

Every hypothesis receives one of five confidence grades, based on the quality, consistency, and directionality of the available evidence.
Strong
Multiple independent, consistent sources support the claim.
Moderate
Reasonable support, but with gaps or limited replication.
Weak
Thin or preliminary evidence; claim is under-supported.
Contradicted
Credible evidence points against the claim.
Unresolved
Evidence is absent or too mixed to score.

Support / refute scoring

Both sides of every claim

We deliberately record contradicting evidence and open questions. A claim scored Contradicted or Unresolved is often more useful than one waved through.

Support is not enough on its own

A claim with only supporting evidence and no search for contradiction is a marketing claim, not a diligence finding. HDDT requires the counter-case.

Uncertainty is a finding

Where evidence is thin or mixed, we say so. Naming the unresolved questions is part of the deliverable.

Human-supervised AI workflow

Where automation helps, and where judgment stays

AI accelerates the mechanical parts. People own the conclusions.
  1. 1

    Input evidence

    Public literature, filings, and (optionally) supervised dataroom materials.

  2. 2

    Hypothesis decomposition

    The thesis is broken into discrete, testable claims.

  3. 3

    Evidence search

    AI-assisted retrieval and synthesis across sources, with human review.

  4. 4

    Support / refute scoring

    Each claim is graded for supporting and contradicting evidence.

  5. 5

    Investor narrative

    Findings become an investor-readable diligence conclusion.

  6. 6

    Published authority asset

    The narrative is published as a citation-backed, structured page.

  7. 7

    Visibility measurement

    Search and AI-answer discoverability are tracked as a downstream effect.

Anti-hype box

HDDT does not replace investor judgment, clinical diligence, legal review, regulatory counsel, or scientific peer review. It structures the evidence so that better judgment becomes easier.

Outcomes

What teams use HDDT output for

The deliverable is built to support real decisions — not to replace counsel, peer review, or your own judgment.

Prioritize diligence questions

Know which claims are supported, which are shaky, and which contradictions to press before the next meeting.

Shape the investor narrative

Publish only what the evidence supports, with sources attached — so the story survives skeptical reading.

Benchmark against comparators

See how similar programs failed or financed, and what that implies for milestone and differentiation claims.

Publish durable authority

Turn the reviewed conclusion into a citation-backed page that investors, partners, and search systems can actually use.

See how HDDT reads a real opportunity.

Walk through an anonymized worked example, or scope your own.

View the exampleRequest a scoping call