Free for independent researchers

Clinical Research Built for the Physician

Submit de-identified patient observations using cryptographic tokens. Organize peer-reviewable studies. Export CONSORT-ready data with AI assistance — no IRB headaches, no IT department, no cost.

Start Your Study See How It Works
✓
HIPAA Safe Harbor
✓
CONSORT & STROBE
✓
CDISC SDTM Export
✓
FHIR R4 Compatible
✓
20 Specialty Templates
0
Active Studies
0
Case Submissions
20
Specialty Templates
20
Clinical Calculators
18
Peer Review Components
⚠

Traditional EDC is gatekeeping research

Academic EDC systems require institutional access, IT setup, and IRB approval even for retrospective chart reviews.

⚠

PHI liability blocks data sharing

Physicians have clinically rich data that could advance science — but HIPAA compliance makes sharing prohibitively complex.

⚠

Case series never reach peer review

Promising observations stay in filing cabinets because there’s no structured, exportable, checklist-compliant format.

How it works

From patient encounter to
publication-ready data in 4 steps

No data governance training required. Your patient identifiers never leave your browser.

1

Generate a Token

Type your local chart number. hyJournal creates a SHA-256 hash in your browser. Only the token is submitted — never the patient ID.

SHA-256 · Client-side · Irreversible
2

Submit Observations

Fill structured forms: ICD-10 diagnoses, RxNorm-normalized drugs, MedDRA-coded AEs, biomarkers, and validated outcome scales.

CRF-style · Specialty templates
3

Organize a Study

Create study arms, pre-register your protocol with a cryptographic hash, and invite co-investigators.

Pre-registration · K-anonymity gate
4

Export for Publication

Run AI statistics, complete CONSORT/STROBE checklists, generate a manuscript skeleton, and export in 6 formats.

ICMJE compliant · SDTM · FHIR R4
hyJournal — Patient Token Generator
// Step 1: Doctor enters their local chart identifier
const localId = "CHART-2026-04821";
const physicianEmail = "[email protected]";
 
// Step 2: SHA-256 runs in YOUR browser — raw ID never transmitted
const hashBuffer = await crypto.subtle.digest("SHA-256", encode(email + "::" + localId));
 
// Step 3: Only this 32-char token is ever submitted to the server
const patientToken = "a4f2b31c9e8d7f62bd5c...";
 
→ Token generated. HIPAA Safe Harbor: confirmed. Patient identity: unrecoverable.
$

Privacy architecture

Mathematically impossible to recover
patient identity — by design

Implements HIPAA Safe Harbor (45 CFR §164.514(b)(2)) — all 18 identifiers suppressed.

What we store
  • 32-character SHA-256 token (irreversible)
  • Age bucket — 18-25, 26-35, 36-45, 46-55, 56-65, 65+
  • Geographic region — Northeast / Southeast / etc.
  • Relative dates from enrollment Day 0
  • ICD-10 diagnosis codes
  • RxNorm-normalized drug names + RxCUI codes
  • MedDRA-coded adverse events (SOC → PT)
  • Quantitative biomarker values + outcome scores
  • SHA-256 content hash — immutable audit trail
What we never store
  • Patient name
  • Date of birth or exact age
  • Address, zip code, or county
  • Phone or fax number
  • Email address
  • Social security number
  • Medical record number (MRN)
  • Account or certificate numbers
  • Device identifiers or IP addresses
  • Photos or biometric identifiers

Platform features

Everything a peer-reviewable
study needs — built in

📋

CONSORT & STROBE Checklists

25 items for RCTs, 22 for observational. Each evaluated against your data with ✓/⚠/✗ status and fix guidance.

Peer-review ready
🔒

Pre-Registration with Hash Proof

Lock your protocol before data collection. SHA-256 hash + UTC timestamp — equivalent to ClinicalTrials.gov for independent studies.

Anti-HARKing
📊

AI-Powered Statistics

Normality checks, test selection, multiplicity correction, Clinical Scenario Evaluation power analysis. No R or Python required.

CDISC-ready
🪮

20 Clinical Calculators

eGFR, MELD, SOFA, APACHE-II, CHADS₂-VASc, ASCVD, PHQ-9, GAD-7, DAS-28, KOOS, CDAI, NIHSS, MMSE, Framingham CHD, Wells DVT.

Evidence-based
💊

RxNorm Drug Normalization

Real-time canonical drug name + RxCUI code. Prevents spelling variation across submitters. Pulls expected AEs from OpenFDA.

RxNorm + OpenFDA
🤖

AI Manuscript + Reviewer Agent

Generate Intro/Methods/Results skeleton. Reviewer agent verifies PMIDs are real and statistics match your dataset.

Claude-powered
🏥

IRB Application Assistant

Generate a complete IRB narrative from your protocol including the de-identification method, risk/benefit, and data protection sections.

IRB-ready
📈

Longitudinal Visit Schedules

Screening / Baseline / Week 4 / Month 6 / EOS windows with tolerance bands. Track dropout, LTFU, and protocol deviations.

EDC-style
📊

Publication Figure Generator

Box + violin, Kaplan-Meier, forest plots, CONSORT flowcharts, Bland-Altman, heatmaps at 300 DPI JAMA style.

JAMA style

Export formats

Six formats — from SPSS to FDA

Every export is designed to slot directly into the workflow of the journal, regulator, or EHR system receiving it.

📊
CSV (SPSS-ready)
RCT Bench variable naming
🏛
CDISC SDTM
FDA submission-compatible
🔗
HL7 FHIR R4
EHR-importable Bundle
📋
Codebook (CDASH)
CDISC variable dictionary
📁
JSON (Structured)
Full schema, programmatic
📄
CONSORT Flowchart
Enrollment → Analyzed

Specialty templates

20 templates with pre-loaded
biomarkers and outcome scales

💉 Peptide Therapy / Anti-aging
🏃 Sports Medicine / Orthopedic
🧪 Endocrinology
❤ Cardiology
🔬 Oncology
🧠 Neurology
🤺 Psychiatry
🧟 Gastroenterology
🦴 Rheumatology
🌿 Integrative Medicine
🧬 Longevity / Biohacking
💊 Metabolic / Obesity
🔫 Nephrology
🦠 Infectious Disease
🛡 Immunology
👁 Dermatology
⚕ General Practice
Gynecology
⚗ Urology
🧟 Pulmonology

PeptideProtocol.wiki × GeneOS × hyJournal

Miami BPC-157 decentralized clinical evidence collaboration

A new standard for clinics: capture real longitudinal outcomes, connect protocol-defined biomarkers, and turn distributed physician evidence into a publication-grade scientific record.

Physician network open

Build the evidence record the future of science runs on.

Physician recruitment open

Participating Miami-area physicians contribute a shared clinical evidence stream: protocol-aligned observations, longitudinal follow-up, biomarker packages, and publication artifacts. PeptideProtocol.wiki provides the living protocol layer, GeneOS provides encrypted marker intelligence, and hyJournal unifies the research record for analysis and publication.

1

Join the physician network

Bring your practice, specialty, research experience, and capacity into a shared Miami evidence initiative.

2

Capture the measurable signal

Use the common protocol, timepoints, and marker definitions to create comparable clinic-to-clinic evidence.

3

Publish an enduring record

Transform tokenized observations, biomarker provenance, and analysis into a peer-review-ready publication package.

P

Protocol layer

PeptideProtocol.wiki carries versioned procedures, evidence context, investigator-facing protocol material, and recruitment attribution—not participant data.

G

Intelligence layer

GeneOS produces protocol-defined genomic or expression-marker summaries with assay, panel, quality-control, and analysis-version provenance.

J

Study layer

hyJournal receives only approved marker codes and normalized de-identified values for the defined timepoint, then governs analysis and publication drafts.

Expression-marker workflow: BPC-157 is the opening peptide because GeneOS makes it possible to define measurable baseline-to-follow-up marker packages alongside clinic-recorded outcomes. The shared assay, panel, timepoints, QC provenance, and analysis version make every contributing site part of one comparable evidence network.
Decentralized science, built to last: clinics collect the data, GeneOS packages encrypted marker intelligence, and hyJournal assembles the auditable research record. The publication objective is a Bitcoin-inscribed protocol and manuscript hash: an enduring, independently verifiable record of the study release and its scientific artifact history. This collaboration is positioned to pioneer a permanent peptide-study publication record on Bitcoin while giving clinics the protocol, provenance, analysis, and publication infrastructure mainstream science expects.

Apply as a participating physician

Join the clinic network and help establish the next standard for decentralized clinical evidence.

Journal compatibility

Satisfies ICMJE requirements
out of the box

ICMJE requires a data sharing statement for all clinical trial manuscripts. hyJournal auto-generates it.

Nature Medicine
NEJM Evidence
JAMA Network Open
PLOS ONE
BMC Research Notes
F1000Research
Cureus
Frontiers in Medicine

Get started today

Start contributing to
medical knowledge

Build the protocol, evidence stream, analysis, and publication record from one encrypted research workspace.

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hyJournal does not store Protected Health Information (PHI). All patient records are cryptographically tokenized client-side using SHA-256 before transmission.