Summary
Once the population and variables are defined, the remaining methodological sections of the protocol need to be completed: sample size, statistical analyses, timeline, missing data, regulatory, and references. The Study Designer then offers several export formats as well as export from a custom Word template. Three advanced sections round out the tool: custom sections, data schema, and automatically generated scripts.
Sample size
The Sample size section contains a Markdown editor to describe and justify the required number of subjects.
A built-in calculator (available in edit mode) lets you quickly estimate the sample size for three types of tests:
- Comparison of two proportions — you enter the expected proportions (p1 and p2)
- Comparison of two means — you enter the expected effect size
- Chi-squared test — you enter the expected effect size
For each test, you set the alpha risk (default 0.05) and power (default 0.80). The result shows the number of subjects per group and the total. A button lets you insert the result directly into the editor.
An estimation tool
The built-in calculator is a quick estimation aid. For complex designs (survival analyses, cluster studies, non-inferiority studies…), use dedicated power calculation software and report the result in the editor.
Missing data
The Missing data section is a Markdown editor to describe the missing data handling strategy: expected rate, imputation method, sensitivity analysis, etc.
Statistical analyses
The Statistical analyses section has two parts:
Structured analyses
You can add predefined analyses that reference the variables in your study. The main available types are:
- Regression — logistic, linear, Cox, propensity score matching (PSM), random forest, neural network, or XGBoost. For each model, you select the outcome variable and the covariates. Cox regression additionally requires a time variable.
- Table 1 — the classic descriptive table. You select the variables to display and the grouping variable.
- Comparison — Kaplan-Meier, t-test / Wilcoxon, ANOVA. You select the outcome variable and the grouping variable.
- Chi-squared / Fisher — cross-tabulation of two categorical variables.
- Other — for any analysis type not listed above. You provide a custom name and description.
Each analysis is summarized as a card with the referenced variables displayed as badges.
Software
A Markdown editor lets you specify the programming languages (R, Python…), software, and libraries used for the analysis, as well as important parameters.
Timeline
The Timeline section lets you define the main phases of the study.
The project start date and end date fields set the overall period. You then add phases (e.g., “Data collection”, “Statistical analysis”, “Writing”) with a name, start and end dates, description, and color for each.
Phases can be reordered by drag and drop. A Gantt chart is automatically generated to visualize the project schedule.
Regulatory
The Regulatory section is a Markdown editor to describe applicable regulatory procedures: data protection authority declaration, ethics committee approval, informed consent, applicable regulatory framework, etc.
References
The References section lets you manage the citations referenced in the protocol. Several methods are available:
- DOI lookup — enter a DOI to automatically retrieve the publication metadata
- BibTeX / RIS import — paste an export from your reference manager (Zotero, Mendeley, EndNote…)
- Manual entry — fill in the fields one by one (authors, title, journal, year, pages, DOI…)
Each reference is displayed as a collapsible card with all its fields. Available reference types include: journal article, book, chapter, conference, thesis, technical report, web page, software, and other.
You can choose the citation style (Vancouver or APA) in the section settings. Numbered references can be cited in the Markdown editors of other sections via built-in citation buttons.
References can be reordered by drag and drop.
Advanced sections
Three additional sections are accessible via the Advanced tab in the sidebar.
Custom sections
Lets you add as many free-form sections as needed. Each section has a title and content in Markdown. This is useful for protocol aspects not covered by the predefined sections (e.g., data management plan, monitoring, funding).
For data scientists
The Model & schema and Scripts sections are intended for data scientists and data engineers. They allow configuring the mapping to a clinical data warehouse and generating the corresponding SQL queries.
Model & schema
This section lets you describe the mapping between your source database and a standard data model. You define:
- The patient table — which table contains patients, with columns for ID, birth date, sex, and death date.
- The visit table — which table contains visits or admissions, with columns for visit ID, start and end dates, and care site.
- The event tables — one or more tables containing clinical events (labs, diagnoses, drugs, procedures…), with columns for code, value, date, and foreign keys to patients and visits.
- The gender values — which value represents “Male”, “Female”, and “Unknown” in your database.
Four presets are available — OMOP CDM v5.4, OMOP CDM v5.3, MIMIC-IV, MIMIC-III — to automatically pre-fill table and column names. You can also create, save, export, and import your own presets.
Scripts
For SQL scripts to be generated correctly, the data model and schema must be configured first.
Displays the automatically generated SQL scripts from your criteria, concept sets, and variables. The interface features a code editor (Monaco) with three files:
0_cohort.sql— the cohort construction query (inclusion and exclusion criteria)1_filtered_views.sql— filtered views by concept sets2_wide_format.sql— the variable extraction query in wide format
These scripts are read-only (they are generated, not manually edited). You can copy or download them individually, or download them all as a ZIP file.
What are the scripts for?
The generated SQL scripts are a starting point for data extraction. They automatically translate the criteria and variables defined in the Study Designer into actionable SQL queries. You can then adapt them to your database environment.
Exporting the protocol
The Export section offers five formats to export your protocol.
JSON
Exports the complete project in a technical format (JSON) that can be re-imported into the Study Designer. This is the ideal format for backup and sharing between colleagues.
Word (.docx)
Generates a structured Word document with a title page, table of contents, and all protocol sections formatted. This is the appropriate format for submission to an ethics committee for example.
Excel (.xlsx)
Generates an Excel workbook with multiple sheets: project summary, author list, variables table, timeline, and custom sections. A Data collection sheet is also included: it contains the columns you configure in the setup panel (patient ID, admission dates, etc.) and one column per defined variable.
Before export, a panel lets you customize the data collection columns: add, remove, rename, and reorder columns by drag and drop.
Markdown
Exports the protocol as plain text in Markdown format. This format is useful for version control (Git) or integration into a wiki.
Export from a template
This option lets you use your own Word (.docx) template as the export base. You upload a Word file containing placeholders (tags) that the Study Designer will replace with the protocol data.
Placeholders use the format [[placeholder_name]]. You can place them anywhere in your Word document: in the body text, headers, footers, tables, etc.
Available placeholders
Here is the complete list of recognized placeholders:
| Placeholder | Content |
|---|---|
[[acronym]] | Study acronym |
[[title]] | Study title |
[[version]] | Protocol version |
[[status]] | Protocol status (translated) |
[[study_type]] | Study type (translated) |
[[start_date]] | Start date |
[[end_date]] | End date |
[[authors]] | Author list (name, role, institution, email) |
[[context]] | Study context (plain text) |
[[primary_objective]] | Primary objective |
[[primary_endpoint]] | Primary endpoint |
[[secondary_objectives]] | Secondary objectives (list) |
[[secondary_endpoints]] | Secondary endpoints (list) |
[[inclusion_criteria]] | Inclusion criteria |
[[non_inclusion_criteria]] | Non-inclusion criteria |
[[concept_sets]] | Concept sets (with code list) |
[[anchors]] | Temporal anchors |
[[variables]] | Variables (with anchor, window, aggregation) |
[[sample_size]] | Sample size |
[[software]] | Analysis software |
[[missing_data]] | Missing data |
[[regulatory]] | Regulatory procedures |
[[data_sources]] | Data sources |
[[references]] | References |
How to use a template?
Create a Word document with your institution’s layout (logos, headers, styles). Place the [[...]] placeholders where the protocol data should appear. Then upload this file in the Study Designer via the “Export from template” button. The generated document will keep your layout with the protocol data inserted in the right places.
Key takeaways
- The sample size can be estimated using the built-in calculator, then justified in the editor.
- Statistical analyses offer structured analyses (regression, Table 1, comparison, Chi-squared…) that directly reference the protocol variables, plus an editor to describe the languages, software, and libraries used.
- The timeline automatically generates a Gantt chart from the defined phases.
- The references section supports DOI, BibTeX, and RIS import, and citations are integrated into Markdown editors.
- Advanced sections (Advanced tab) include custom sections, the data model and schema, and automatically generated SQL scripts.
- Five export formats are available: JSON (backup), Word (submission), Excel (data collection), Markdown (version control), and Word template (custom layout with
[[...]]placeholders).