Overview

Permuted Block Design (also called Random Permuted Blocks or Blocked Randomization) is the most widely used algorithm for simple parallel-arm clinical trials. It creates balanced blocks of treatment assignments that are internally shuffled to maintain allocation concealment while guaranteeing balance within each block.

How it works

1. A block of size n is generated with treatment assignments in the correct allocation ratio.
2. Within each block, the assignments are randomly permuted (shuffled).
3. Subjects are assigned in sequence — when one block is exhausted, a new block is generated.

Example — Block size 4, 1:1 allocation (TRT : PBO):

Each block contains 2 TRT and 2 PBO assignments, shuffled randomly:

Block 1: [TRT, PBO, TRT, PBO]
Block 2: [PBO, PBO, TRT, TRT]
Block 3: [TRT, PBO, PBO, TRT]

At any point within a block, the number of TRT and PBO subjects will not differ by more than block_size / 2.

When to use

Use Permuted Block Design when:

• The trial has a single site (or balance at the site level is not required).
• Stratification by subject characteristics is not needed.
• You want a simple, well-understood algorithm accepted by all major regulatory agencies.

For multi-site trials or when subject-level stratification is needed, use Stratified Permuted Block Design instead.

Who uses this screen

The Randomization configuration screen is used by the Study Administrator to set up and manage the algorithm, study groups, eligibility questions, and notifications. Site staff (Investigators, CRCs) interact with randomization through the subject data capture workflow at the designated randomization event — they do not access this configuration page directly.

If you cannot open the Randomization app or the Edit buttons are greyed out, verify that the study is in Design status. Configuration changes are not permitted while the study is in Available, Locked, or Frozen status.

Typical workflow

1. Open the study and navigate to Randomization in the left sidebar.
2. Open the Blinding Method and Algorithm settings card and select Permuted Block Design.
3. Save the algorithm selection — the Permuted Block Settings card appears.
4. Open Permuted Block Settings and configure study groups, block size, and list generation method.
5. Configure Select event to Randomize — choose which study event triggers randomization.
6. (Optional) Configure Additional data before Randomization — add eligibility questions.
7. Configure Email Notification — choose which roles receive alerts on randomization.

Step-by-step configuration

Step 1 — Open the Randomization app

Sign in to your ClinicalDataS instance, open the study, and select Randomization from the left sidebar under Installed Apps.

The Randomization page lists all configuration cards. If the study is in a non-Design status, most Edit buttons are disabled. To enable editing, change the study status to Design via the Change Status button on the study home page.

Step 2 — Select the Permuted Block Design algorithm

Click Edit on the Blinding Method and Algorithm settings card.

Field	Options	Description
Blinding Method	Single Blind	CRC and study staff can see the subject's study group.
	Double Blind	Only Sponsor and Study Administrator know the subject group.
Randomization Algorithm	Permuted Block Design	Single-list randomization using balanced permuted blocks.
	Stratified Permuted Block Design	Separate lists per site/stratum combination.
	Big Stick Design	Allows imbalance up to a predefined MTI before forcing balance.
	Minimization Design	Covariate-adaptive allocation minimizing group imbalance.

Select Permuted Block Design, then click Save.

The page reloads and the Permuted Block Design settings card appears below Blinding Method and Algorithm settings.

Step 3 — Configure Permuted Block Settings

Click Edit on the Permuted Block Design card.

Setting	Description
Study Group	One row per treatment arm. Each row requires: Label (display name), Code (short identifier, e.g. TRT, PBO), Weight (allocation ratio weight), Description (optional). Use + Add more study group to add arms.
Block size	One or more positive integers separated by commas. Each block size must be divisible by the total weight sum of all study groups. For a 1:1 allocation (total weight = 2), valid sizes are 2, 4, 6, 8, …
Define different ways to generate randomization list	How the randomization list is created — see options below.

List generation options:

Option	Description
User manually generate a pre-randomization list	Go to Randomization List, click Generate, enter the block size, and click Submit to create the list before any subject is randomized.
Generate at real-time when a new subject is randomized (recommended)	The system checks and generates a new randomization code automatically at the moment a subject is enrolled and the randomization process starts.
Flexible, allow pre-generation and realtime	Uses the pre-generated list first; if no pre-generated list exists, falls back to real-time generation.

Block size guidance

Allocation ratio	Minimum block size	Common choices
1:1	2	4, 6, 8
1:1:1	3	6, 9
2:1	3	6, 9
1:2:1	4	8

Security note: Small block sizes (e.g. 2 or 4 for a 1:1 ratio) make it easier to guess the next assignment near the end of a block. For open-label or unblinded trials, use larger block sizes to maintain allocation concealment.

Click Submit to save the settings.

Step 4 — Select event to Randomize

Click Edit on the Select event to Randomize card.

Field	Description
Select Event	Choose the study event at which randomization takes place. Only non-repeat events are supported. Use Reload to refresh the list if you recently added events. Click Manage Events to navigate to the event setup page.
Randomization form name	Optional. Override the default name of the randomization CRF. Leave blank to use the system default.
Position of randomization form	Where the randomization form appears within the selected event. Default: At first position.

Click Submit to save.

Step 5 — Additional data before Randomization (optional)

Click Edit on the Additional data before Randomization card to define eligibility questions that site staff must answer before a subject can be randomized.

Three question types are supported:

Section	Behaviour	Example
Inclusion question	Must be answered Yes to proceed.	"NYHA Class II or III confirmed"
Exclusion question	Must be answered No to proceed.	"Active malignancy"
Open question	Free-text or other answer type; no pass/fail logic.	Any additional data collection

The Options toggle lets you replace the default Yes/No labels with custom text (e.g. Có/Không, Agree/Disagree) for studies in other languages.

Use + Add inclusion question / + Add exclusion question / + Add open questions to add rows. Click Submit to save.

Step 6 — Email Notification

Click Edit on the Email Notification card to configure which roles receive an automated email when a subject is randomized.

Field	Description
Send email notification to following recipients	Check one or more roles: Study Administrator, Study Sponsor, Site Monitor, Study Monitor, Investigator, Clinical Research Coordinator.
Also send email to following recipients	Enter individual email addresses (up to 30), separated by colons. Useful for external stakeholders not in the system.
Email Subject	Subject line of the notification email.
Email Content	Rich-text body of the notification email. Click View all Variables to insert dynamic placeholders (e.g. subject ID, randomization date).

Click Submit to save.

Limitations

• No site-level balance — if enrollment is uneven across sites, some sites may finish with imbalanced treatment arms.
• No subject-level stratification — prognostic factors can still be unbalanced between arms by chance, which is more of a concern in small trials. Use Stratified Permuted Block Design if stratification is required.

Regulatory acceptance

Permuted Block Design is accepted by FDA, EMA, PMDA, and ICH E9. Reference ICH E9 §3.4 for guidance on randomization in clinical trials.

Related topics

• Randomization Configuration — all configuration cards and blinding options
• Stratified Permuted Block Design — adds site and covariate stratification
• Big Stick Design — tolerates short-term imbalance within a predefined MTI
• Minimization Design — covariate-adaptive allocation