After the readout, every document at once
- Top-line abstract, CSR, manuscript and Module 2 from one locked analysis
- NCCN, formulary and EU joint assessment dates tied to each document
- Code and output ready for HTA appendices
For mid-market pharma, biotech and diagnostics
Publish sooner.
Reach coverage sooner.
Silogram turns the SQL, R and Python in your analysis repository into manuscripts, abstracts, clinical study reports and payer dossiers, with every number linked to the code that made it, or flagged until it is.
Designed to support 21 CFR Part 11 and HIPAARead-only access to your repositoryNever trains AI models on your documents
Built to the standards your reviewers check
- ICH E3
- ICMJE
- CONSORT 2025
- STARD 2015
- AMCP Format 5.0
- EU HTA Regulation
- CDISC ADaM
- 21 CFR Part 11
Every number, linked to the code that made it.
Writers, statisticians, reviewers and agents work from the same verified definitions and values. When the analysis changes, every document shows what moved.
Live numbers with tracked changes
Every number in the text is a live value from the analysis, with its file, line and commit one click away. Typed numbers are flagged before sign-off.
- A sync updates every linked number and shows what moved
- The number audit finds numbers typed by hand
- Word export with real tracked changes
The cohort, read from the code
Silogram reads the SQL, R and Python and writes each eligibility step, variable and endpoint in plain language, with the patients left after each step.
- CDISC ADaM names in plain English
- Analysts verify each definition
- Verification goes stale when the code changes
Proof the code produces the numbers
A runner re-runs your analysis at a commit in a sandbox with no network access and checks that it produces every value, table and figure the documents cite.
- Runs inside your network, next to the data
- Only the declared outputs come back
- Every run is in the audit trail
Dates tied to the decisions they unlock
Link each document to the coverage, formulary, guideline or approval decision it supports. See when it is likely and what a week of delay costs.
- Most-likely and 90% dates from real progress
- NCCN, MolDX, formulary, EU JCA and more
- Priced with your own revenue estimate
How it works.
From the repository your statisticians already use to a signed document your reviewers can trust.
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Connect
Point Silogram at the Git repository that holds your SQL, R and Python: GitHub, GitLab or Bitbucket, with a read-only token.
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Draft and check
Writers and approved agents draft in your house style. Each number links to an analysis value or gets flagged; reviewers suggest, writers decide.
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Sign and submit
Approvers sign a digest of the exact text, the document locks, and the access plan shows when the decision it supports is likely.
One locked analysis.
Every document payers and regulators read.
Your analysis repositorymain · 4f2a9c1
- Congress abstractWithin the character limit
- ManuscriptICMJE, CONSORT, STARD
- Clinical study reportICH E3
- Module 2 summariesCTD 2.5 and 2.7
- Formulary dossierAMCP Format 5.0
- MolDX and EU JCACoverage and HTA dossiers
Change a number once. Every document shows what moved.
Coverage decisions wait for the paper.
Formulary dossiers prefer peer-reviewed studies. NCCN Category 1 needs a publication. Medicare's molecular test program pays from the date a test passes its technical assessment.
8 months
median from an oncology results press release to the full paper.1
36%
of FDA cancer drug approvals in 2010–2014 had no peer-reviewed efficacy paper within 30 days.2
28 days
before an NCCN panel meeting is the deadline for outside submissions.3
3–4 weeks
for a MolDX technical assessment once the published evidence is in place.4
Two markets. One bottleneck.
Mid-sized teams carry big-pharma evidence loads: one readout or validation study becomes a stack of documents, all due at once.
From validation study to covered test
- Validation paper and MolDX package with the same traced numbers
- NCCN submission and technical assessment dates on the plan
- STARD 2015 and TRIPOD+AI checklists built in
Questions teams ask first.
Do you need our patient-level data?
No. Silogram reads code and aggregate outputs. Workspaces default to no PHI, and a scanner blocks likely patient identifiers. When you reproduce outputs from code, the runner sits inside your network next to the data; only the declared outputs come back.
Which AI models and agents work with it?
Any model your company has approved, with your own keys, and any agent that speaks MCP or REST. Agents read verified context; everything they write arrives as a tracked suggestion that a person accepts or rejects.
Is it 21 CFR Part 11 compliant?
Silogram is designed to support Part 11 and HIPAA: an append-only audit trail, electronic signatures bound to the exact text signed, approval locks and access controls. Compliance also depends on your validation and procedures, so we provide the requirement list, test evidence and templates.
Do you train AI models on our documents?
No. Your documents and house style stay in your workspace and are never used to train models.
How does a pilot work?
Ninety days on one live document. We connect its analysis repository with a read-only token, learn your house style from past papers, and measure the time from locked outputs to submission against your recent history. The pilot fee is credited to an annual plan.
What does it replace?
Copying numbers from tables into Word, re-checking them by hand, and tracking plans in spreadsheets. It works alongside your writers, agencies and statistics team rather than replacing them. See how it compares.
Sources
- 1Valsecchi et al. J Cancer Policy. 2025. PubMed 40268192.
- 2Lammers et al. Blood Cancer J. 2017. PMC5802585.
- 3NCCN. Guidelines submission process FAQs (November 2024).
- 4Palmetto GBA. MolDX General FAQs.