Common Randomisation Methodologies Implemented in IRT

By Kevin Venner, Jennifer Ross

What is Randomisation in a Clinical Trial?

Randomisation is the process for how subjects are assigned to Treatment (groups, arms, etc.) in a clinical trial with introducing a deliberate element of chance. If randomisation is not utilized or utilized inappropriately, then assumptions may be made on upcoming Treatment assignments. Knowledge of what Treatment is being assigned next can consciously or unconsciously influence decisions on whether to enroll a subject or which subject to enroll next. This influence is called Selection Bias. When properly implemented, Randomisation protects against Selection Bias to ensure the observed Treatment effect is due to the Treatment itself and not due this bias.

Further, randomisation helps achieve the required number of subjects per Treatment, which is also known Treatment Balance. With the random allocation of subjects throughout the trial, it is expected that each Treatment will have similar subjects for evaluation.

Interactive Response Technology (IRT) enables the global execution of randomisation and medication management across multiple sites. This removes the need for site-specific code-envelopes and other burdensome manual randomisation processes. Instead of relying on an unblinded contact to track randomisation, the IRT maintains an auditable dataset including details of each subject’s randomisation transaction.

Determining how to design randomisation in the IRT begins by reviewing the clinical trial’s protocol. Typically, the protocol provides randomisation details such as the Treatments, allocation ratio, number of subjects enrolled (sample size) and other information as applicable (e.g., stratification factors, cohorts, etc.).

This article focuses on the most common randomisation methodologies implemented in IRT:

  1. Central Randomisation
  2. Stratified Randomisation with Blocks Pre-Allocated to Strata
  3. Stratified Randomisation with Blocks Allocated On-Demand to Sites

How is Central Randomisation Methodology Implemented in IRT?

Central Randomisation is when all subjects are randomised within the same scheme regardless of any subject characteristics or demographics. Clinical trials use a Central Randomisation design when Treatment safety and efficacy is evaluated across all randomised subjects, and no sub-group analysis is planned. This evaluation requires Study-Level Treatment balance.

For an example, assume a protocol’s randomisation design specifies:

  • Treatments: 2 (Active vs. Placebo)
  • Treatment Allocation Ratio: 1:1
  • Sample Size: 20
  • Stratification: None – N/A

To obtain the Study-Level Treatment balance given the sample size (N=20) and ratio (1:1), the IRT will need to randomly allocate 10 subjects to Active and 10 subjects to Placebo. This is achieved via a Blocked Randomisation List, sometimes referred as Randomisation Schedule. The Randomisation List is generated with a specified Block Size that includes randomly ordered Treatment assignments within each block. For example, if the Block Size is 4, then for every 4 records, 2 Active records and 2 Placebo records would appear in random order. This blocking technique is the basis for each type of Randomisation List utilized across the 3 common Randomisation Methodologies. See below for an illustration of a Blocked Randomisation List for Central Randomisation.

Example 1: Central Randomisation List

Sequence NumberRandomisation NumberTreatment CodeTreatment DescriptionBlock NumberSubjectID

The assignment of subjects to the randomisation records in the IRT is simple! At randomisation, the IRT identifies the next available record (based Sequence Number order) and assigns to the subject. The subject’s ID is permanently linked to their assigned Randomisation Number and Treatment.

Looking at the Central Randomisation design in the Example 1 list, the 1st, 2nd, 3rd subjects are assigned to Treatments A, A, and B, respectively.  The 4th subject will be assigned to Treatment B, which will complete the block.  When all 20 subjects are assigned, 5 blocks will be completed and Treatment allocation ratio of 1:1 will be maintained at the overall Study-Level.

What if a Clinical Trial Requires Sub-Group Level Treatment Arm Balance?

If Treatment effect differences are expected across certain subject sub-groups, then the randomisation design may need to maintain the Treatment Balance within specified subject sub-groups.  The clinical trial’s protocol defines these sub-groups as Stratification Factors. This sub-group level balance can be achieved within a Stratified Blocked Randomisation List.

For an example, assume a protocol’s randomisation design specifies:

  • Treatments: 2 (Active vs. Placebo)
  • Treatment Allocation Ratio: 2:1
  • Sample Size: 90
  • Stratified by:
    • Prior Treatment (Yes vs. No)
    • Symptom Score: (1 vs. 2 vs. 3)

Based on the above details, approximately 60 subjects will need to be assigned to Active, and 30 subjects assigned to Placebo. Within each cross-combination of the protocol’s Stratification Factor Levels (defined as Stratum), the blocks should maintain the 2:1 Treatment allocation ratio. The Randomisation List for this study can be designed with a Block Size of 6 (with 4 Active and 2 Placebo records) and the below Stratum definitions:

StratumPrior TreatmentSymptom ScoreStratum Description
1Yes1Prior Treatment: Yes; Symptom Score: 1
2Yes2Prior Treatment: Yes; Symptom Score: 2
3Yes3Prior Treatment: Yes; Symptom Score: 3
4No1Prior Treatment: No; Symptom Score: 1
5No2Prior Treatment: No; Symptom Score: 2
6No3Prior Treatment: No; Symptom Score: 3

Each Stratum is pre-allocated its own set of randomised blocks within the Randomisation List, which essentially creates a sub-list for each Stratum.  Example 2 below shows the 1st block in the Stratum 1 sub-list and the 1st block in the Stratum 6 sub-list.

Example 2: Stratified Randomisation List with Blocks Pre-Allocated to Stratum

Sequence NumberRandomisation NumberStratumStratum DescriptionTreatment CodeTreatment DescriptionBlock NumberSubjectID
10001100011Prior Treatment: Yes; Symptom Score: 1AActive10011
10002100021Prior Treatment: Yes; Symptom Score: 1AActive1001
10003100031Prior Treatment: Yes; Symptom Score: 1BPlacebo1001
10004100041Prior Treatment: Yes; Symptom Score: 1BPlacebo1001
10005100051Prior Treatment: Yes; Symptom Score: 1AActive1001
10006100061Prior Treatment: Yes; Symptom Score: 1AActive1001
60001600016Prior Treatment: No; Symptom Score: 3BPlacebo60012
60002600026Prior Treatment: No; Symptom Score: 3AActive6001
60003600036Prior Treatment: No; Symptom Score: 3AActive6001
60004600046Prior Treatment: No; Symptom Score: 3AActive6001
60005600056Prior Treatment: No; Symptom Score: 3AActive6001
60006600066Prior Treatment: No; Symptom Score: 3BPlacebo6001

To randomise subjects, the IRT first determines the subject’s Stratum, then identifies that Stratum’s sub-list and assigns the next sequential record. If the 1st subject has Prior Treatment = Yes and Symptom Score = 1, then they are assigned to Randomisation Number 10001 and Treatment A. If the 2nd subject has Prior Treatment = No and Symptom Score = 3, then they are assigned to Randomisation Number 60001 and Treatment B. As subjects are randomised within each Stratum, the blocks assignments are completed and the ratio of 2:1 is sustained.

Is this the only way IRT can randomise subjects within Stratification Levels?


The pre-allocation of blocks to stratum demonstrated above is the most common method for stratified randomisation, but there are situations where pre-allocation is not the best fit.

When Site is a Stratification Factor, it is highly possible that more Sites are added mid-study. If pre-allocating blocks to Site (creating a sub-list for each Site), then each time a Site is added in the IRT, a new list would also be needed. This incurs unnecessary downtime and subsequent costs.

To avoid this headache, utilize On-Demand Allocation of Blocks to Sites! The list is generated in the same way as the Central Randomisation List in Example 1, with no blocks pre-allocated to any specific Site. Then the IRT allocates blocks to each Site On-Demand.

As an example, assume a protocol’s randomisation design specifies:

  • Treatments: 2 (Active vs. Placebo)
  • Treatment Allocation Ratio: 1:1
  • Sample Size: 100
  • Stratified by: Site

A Blocked Randomisation List with a Block Size of 4 is generated without any blocks pre-allocated to Sites. At Randomisation, the IRT first checks if any blocks with available records exist for the subject’s Site. If no, then the IRT identifies / assigns the next set of available Block(s) to the subject’s Site and assigns the 1st record to the subject. If yes, then the subject is assigned to the next available record within the block(s) allocated to their Site.

The number of blocks to assign to each Site can be set based on each study’s preference. For ease, the example will demonstrate allocating just 1 block at a time.

Assume the 1st 3 subjects are at the following Sites:

  • SubjectID=1, Site 1234
  • SubjectID=2, Site 3232
  • SubjectID=3, Site 1234

Since the 1st subject is at Site 1234, the 1st Block (1001) is assigned to Site 1234. SubjectID = 1 is assigned to the 1st record in that Block (Randomisation Number 10012, Treatment A). The 2nd subject is at Site 3232, the IRT assigns the 2nd Block (1002) to the Site and 1st record in that Block (Randomisation Number 10006, Treatment B) to SubjectID = 2. The 3rd subject is at Site 1234, which has records available for assignment, thus the 2nd record in Block 1001 is assigned (Randomisation Number 10004, Treatment B) to SubjectID = 3.

Example 3: Stratified Randomisation with Blocks Allocated On-Demand to Stratum (Site)

Sequence NumberRandomisation NumberTreatment CodeTreatment DescriptionBlock NumberSiteSubjectID

As shown above, this approach sets up the Site stratification within the Blocked Randomisation List On-Demand. In this design, the IRT can allocate blocks to new Sites (or even Stratum!), without having to generate subsequent Randomisation Lists.

How Should Randomisation Numbers be Ordered in the Randomisation List?:

For simplicity, in the Examples 1 and 2, the Randomisation Number is ordered sequentially and equal to the Sequence Number. However, it may be necessary for Randomisation Numbers to appear in random (Scrambled) order for blinding purposes. Example 3 (On-Demand Allocation of Blocks to Sites) warrants Scrambled Randomisation Numbers since it involves assigning a single block at a time. Scrambling the Randomisation Numbers prevents anyone from identifying the Block Size. In the example, if the Randomisation Numbers were ordered sequentially, study personnel may be able to figure out that Randomisation Numbers are assigned in sets of 4, which is equal to the block size. To scramble or not to scramble should be agreed upon by sponsor’s Biostatistical Representative and the IRT List Generators.

Important: The Block Size is an Unblinding Parameter that should only be known to study personnel involved in the design and implementation of the Randomisation List. Knowledge of the block size can lead to potential Selection Bias!

Final Thoughts:

The IRT randomisation list approaches discussed in this article are just the surface of randomisation possibilities!  More complex methods for randomisation are achievable through IRT (e.g., Covariate Adaptive Randomisation (minimization), Target Adjusted Algorithms, Hierarchal Algorithms, Adaptive Designs, Master Protocols, etc.).

What is IRT and How Does it Impact Clinical Trials?

What is Interactive Response Technology (IRT) or Randomization and Trial Supply Management System (RTSM)?

An IRT system is known by many other names such as IVRS, IWRS, IXRS, RTSM but regardless of its name, the system delivers a wide range of features for managing patient enrollment and drug supply activities throughout the clinical trial lifecycle.

What are the benefits of using IRT to Support Patient Enrollment into a Clinical Trial?

Patient Enrollment, Randomization and Blind Protection – Utilizing the IRT to handle the enrollment and/or randomization automates the process and eliminates human error compared with manual methods. The system allows for complex protocol enrollment and randomization design and strictly controls sensitive information such as treatment arm and medication treatment assignments to maintain study blinding.

How are Patients Randomized using IRT?

The IRT will systematically randomize patients by assigning them to a treatment arm. There are several common methodologies which can be used such as central, subject stratified and/or site stratified randomization schemes. At the randomization visit, the IRT will assign the subject the appropriate treatment arm based on the programmed randomization methodology. The IRT will typically also assign the subject the appropriate medication kit which matches the randomized treatment arm.

What if I Choose not to use an IRT for Randomization?

To truly appreciate how efficiently an IRT randomizes patients in a double-blind trial, just look at how it was done prior to the availability of IRT. When an IRT is not utilized, each entry on the patient randomization list is associated with a treatment type and matching kit number. The number is sealed in an envelope bearing a sequence number. A block of envelopes and the associated kits are sent to the investigational site where envelopes are chosen in sequence. The matching kit is then dispensed to the patient. While this method is reasonably efficient on an extremely small scale, it is slow and only works with simple randomization designs. Plus, it is subject to human error.

When IRT handles randomization, the process is automated and centralized. It can accommodate complex stratification and randomization design that would not be possible with manual randomization. Randomization happens without human intervention, and therefore reduces human error. And, as with other aspects of study management, the system stores the data for easy tracking.  Automating the randomization and drug assignment process eliminates the need for paper envelopes or cards to be stored at the site where unblinded information could be compromised.

How does the IRT help protect the study blind?

An important function of the IRT is to protect unblinded study data from being disclosed inappropriately. For blinded studies, maintaining the blind is pivotal to the integrity of the trial because it eliminates bias in how patient is treated. Without this protection, the study results can be invalidated. Overall, the IRT acts almost as a force field that shields unblinded information, such as the treatment arm and medication type, from those who should not be privy to it. Access to functions in the system is controlled based on user privileges, so only users who should be privy to unblinded data in the IRT can view it. As with all of the activity recorded through the IRT, this information can be transferred to, or integrated with, another system. Controls are put in place so that unblinded data can only be sent securely to the intended recipient.

What About Emergency Unblinding?

The IRT commonly includes emergency unblinding functionality. This can be setup so that Principal Investigators are able to unblind patients at their sites in case of an emergency. When an emergency code break by the site occurs, the system immediately notifies the study team. Often times, that patient who was unblinded by the site is then automatically discontinued from the study, preventing further drug assignments by the IRT. The IRT can also provide access to the Medical Safety team who can unblind any patient at any site without impacting their ongoing participation in the study.

What are the benefits of using IRT for Supply Management?

Individual kits stored at the depot and site are not labeled for particular patients. Instead, kits are assigned to patients when they arrive for their visit. So, shipments to sites only contain enough product to meet patient demand over a certain period, and resupplies are triggered when inventories hit a designated level. This process maximizes drug availability at the site, since products are only allocated to patients when they come in for visits and minimizes drug wastage. The IRT is able to tailor the supply provided to each site since it knows what patients are at each site, their treatment arms, and the visit schedule.

Developing and maintaining an accurate forecast of product demand over the course of a clinical trial is essential to controlling costs. The IRT provides Supply Chain Managers with real-time updates of what is happening with patient enrollment and product inventory throughout the supply chain. This aids with budget preparation, prevents wastage that comes from stockpiling supplies, avoids the risk of stock-outs, and reduces emergency measures needed to replace expiring drugs.

An IRT can also keep track of product expiry dates and ensure there is sufficient time for the patient to take the medication before it expires. It can also send alerts to study managers if expirations are looming. This notification is particularly important with drugs that must be actively managed because they have short shelf lives. Perhaps most important of all, an IRT gives supply managers a global view of available supplies at main depot, secondary depot and site level. They can therefore adjust their inventory and distribution tactics to meet current trial conditions.

How does IRT Provide Inventory Management?

The IRT has a variety of features to manage the chain of custody of supplies in a trial – from the time supplies are packaged and released at the depot through to medication assignment as well as drug returns and destruction. After supplies are physically packaged and made available in the system, initiation and tracking of movement to another depot or site occurs.

As soon as the Sponsor activates a site in the IRT, the system triggers a request to the depot for an initial supply of medication. The depot fills the order and sends the shipment to the site. When an order arrives at the site, staff confirm its receipt in the IRT, and the drugs are made available for assignment to patients. As patients visit the site, they are assigned a medication kit from the site’s inventory. All the while, an algorithm within the system is monitoring the inventory at each site. If the inventory reaches a pre-determined low level, the supply engine will generate a request for the depot to send a resupply. Through this closed loop process, shipments are made to accommodate newly enrolled patients, subsequent visits, and any needed replacement stock.

Another significant benefit of the IRT that is often overlooked, is facilitating the task of drug accountability, returns, and destruction. This process is still often done manually in many studies, which is tedious and time consuming.  By switching the process electronically via the IRT, sites can save time, improve efficiency, and reduce data entry error.

How does IRT help with Patient Tracking and Reporting?

All patient and supply data stored in the IRT database are readily available in the form of reports and data lookups. This enables the clinical and drug management team to have access to real-time data, study metrics, and alerts. This allows ease of review of the study as it progresses and to subsequently make any necessary adjustments to things like the enrollment or site’s inventory settings to meet the specific condition of the trial at any given time.

Final Thought:

Essentially, an IRT increases trial efficiency and improves the quality of available information throughout a trial.

Find out more about our IRT Platform here.

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