Using Enrollment Thresholds

Case Studies

Problem: A classic struggle in the world of clinical trials is how to ensure there is ‘just enough’ drug at each study site throughout the trial – that is, how to achieve minimal wasting of precious investigational product, but minimize, at the same time, the risk that a site will run out of stock and miss enrollment opportunities that cause study delays as a result. How can your IRT (IWRS/IVRS) system help?

Solution: Veracity Logic’s VLIRT® system allows clients to assign individual enrollment thresholds for each site in the study. A site can be defined as a Low, Medium, or High enroller based on best industry information at the onset of the trial. Each enrollment level feeds into the study’s resupply and inventory management algorithms to determine the optimal amounts of drug to be provided to the site – at initial shipment, for baseline maintenance, and in terms of resupply alert levels for study drug. Recognizing that the one firm rule of clinical trials is that change will occur, enrollment thresholds in the VLIRT® system are easily configurable throughout the study – threshold designation can be changed by Project Managers as events dictate at any point in the trial without requiring custom coding or vendor involvement.

The application of enrollment thresholds is particularly useful when the design of the study doesn’t permit the use of predictive resupply functionality. Predictive resupply is not always a good option for low numbers of users and dosing visits, nor for studies where visits are too close together to handle a just-in-time approach to shipping. In such cases, enrollment thresholds can help project managers put study drug where it will do the most good throughout the trial.

Managing Users in the IRT

Case Studies

Managing Users is one of the key functions of an IRT system in a clinical trial. Typically, IRTs provide the important subject randomization and drug supply management activities for the study. Assigning access to the array of permissions that determine what each user can see and not see in each arena must be foolproof, easy to set up, speedy to change and maintain, and friendly when it comes to adding and subtracting Users throughout the life of the study.

When the Project Specification and the Project System don’t match…

Case Studies

Sometimes it’s a simple thing that gives quality management theory a challenge. For example:

Conventional practice for testing a clinical trial project system asserts the following: When tracing from a test result to the official Project Specification (PS), any discrepancy between the PS and the system requires failing the test step and then re-testing it again in a new test cycle after a correction interval. If we translate this assertion into other terms, the problem with this reasoning becomes obvious: The approach mandates that errors that occur only in the project specification document must result in failing the system – even though the system is perfectly correct. Impact on timelines and project costs are the unfortunate results of this convention.

A typical example: The PS for System XYZ, which outlines the setup configurations for the new project system, has an error in the table that describes the permitted treatment windows for each clinical visit. The PS says X plus or minus three days is permitted at Visit 2; the system is configured to allow four days. From client meetings and correspondence, it’s certain that four days is correct– that is, the system is entirely accurate. The only error that has occurred is that the team has forgotten to make the update to the project specification document prior to the start of testing.

Veracity Logic takes the following view in such cases: When there is certainty and collateral confirmation that only the PS document needs to be corrected, Testers are instructed to mark the test step as a Pass and open a new case in our Issue Tracking System for the required PS Update. A unique tracking number is generated for the case and a discrepancy note including this number is added by the Tester to the test case/step. The Validation Summary Report for the entire testing process captures both the number of Passed and Failed test steps and the number and location of PS Updates required to be corrected (and the PS re-approved) prior to releasing the system for Client User Acceptance Testing.

Enrollment Expectations and Site Management

Case Studies

Problem: Your clinical trial will be conducted at more than 50 clinical sites in the U.S. and another 40 internationally. The incidence of disease for the indication of interest varies widely based on geography, but your IRT algorithm treats sites as a unitary phenomenon–a sure path to cost inefficiencies. How can you leverage known statistical differences to control drug waste, shipping costs, and reduce problems with drug allocation?

Solution: As part of its CORE system, Veracity Logic’s IRT (IWR/IVR) includes the option to accommodate site diversity with respect to known enrollment thresholds. Clients can designate a site as an anticipated low, medium, or high enroller. For each enrollment threshold, users can specify differences in the initial drug allocation to a site, the baseline drug supply that is to be maintained at a site, and the alert levels which will let the system know when it’s time to ship more drug. IRT limitations no longer need to contribute to an overabundance of study drug at one site while the study team wrestles with an insufficient amount of drug at a site performing better. Site assignment to the low, medium, or high enrollment category can also be easily modified at any time the circumstances change.

Veracity Logic-Medrio Integration Spells Success

Case Studies

Through Integration of Medrio and Veracity Logic, Atlantic Research Group Expands Capabilities

Finding themselves under a strict timeline and in need of drug supply management, Atlantic Research Group was searching for a way to bolster their software repertoire. Using a free API from Medrio, they were able to access the comprehensive drug supply management capabilities of Veracity Logic without forfeiting Medrio’s top-shelf electronic data capture.

Why Visual Verification?

Case Studies

The Problem: On the one hand we’ve got statistics. On the other hand, we’ve got human lives. Because of the latter, our hearts tend to have zero tolerance for errors in clinical trial data. How do we find the right level of risk and quality control (QC)?

Let’s tempt the wrath of risk assessors everywhere and look at the issue. What’s the real purpose of QC? To be sure, it is NOT to achieve perfection. On that most of us can wholeheartedly agree, including the FDA.

The question is how to decide how much and which types of QC will help ensure the acceptable error margins we’ve set for ourselves.

That’s a whole other kettle of fish.

The Solution: What we strive to produce is a quality management system that works as a whole. Over time, we add and subtract QC tasks until the right balance emerges—one that satisfies both the risk assessment model and the passion for correct data.

At Veracity Logic, one of the steps in our total QC package is a little bit of bother known as “visual verify”. We’ve reached down into the data management archives, pulled it out, dusted it off, and propped it up on the mantel, remembering a time when it was axiomatic that any single-entry act in the double entry world of quality control had to be independently reviewed. One can almost hear the wooden wagon wheels creaking….

Every data change (DCR) and configuration change (CCR) we’re asked to make in an active IRT project system is executed by a qualified project team member and then subjected to an independent visual confirmation by another qualified member of the team. Successful verification is signed off by the reviewer and becomes part of the project record. Only then is the DCR/CCR regarded as complete.

One almost wants to hum the theme song from ‘Somewhere In Time’…

User Power: Managing Cohorts

Case Studies

The Problem:

The management of multiple cohorts is a standard offering of most IRTs. In the common sequential model, when Cohort 1 reaches a pre-designated limit the cohort is closed by the system and subjects can no longer be enrolled into that cohort. Problem: The design of your study is such that the maximum number of subjects in each of your four planned cohorts cannot be fixed at study startup, and more than one cohort can, in certain circumstances, be open simultaneously. How should the IRT be set up to provide this kind of adaptability?

The Veracity Logic Solution:

A typical approach to achieving flexible cohort functionality is to assign the task to the system development team. Programmers and configuration managers would modify code or system configurations during the trial as needed to adjust cohort parameters. Additional costs, time delays, and the need to produce change orders and approval documents for interparty communication, are three notable downsides to this approach.

Veracity Logic’s IRT platform supports an alternate strategy. In addition to system controls, we offer a user-friendly, manual approach that puts the power of change directly into the hands of authorized users. Cohort parameters are configurable, no coding changes required. Cohort limits can easily be modified and re-modified with the click of a button. Likewise, cohorts can be manually opened and closed, re-opened and re-closed on demand, all by the users themselves, and in the users’ own timeframes.

Dynamic Randomization — Striking a Balance

Case Studies

The Problem:

Randomization — that is, the truly random assignment of patients to a treatment group in a clinical trial — is the gold standard approach to producing statistically valid results in drug studies. Randomization is intended to eliminate bias — theoretically, the myriad of variable and potential variable differences between patients, both known and unknown, should even out over time in infinitely large samples. But study sample sizes in the real world are not infinite. In many cases, they’re not even what one would call ‘large,’ mathematically speaking. In real life scenarios, such as new drug trials, a study can wind up having a serious imbalance in prognostic factors and assignment to study treatment groups. Serious enough, in some cases, that imbalances can call study results into question.

The Solution:

Dynamic Randomization is an alternate strategy in the biostatistician’s toolbox. In a dynamic approach, there is no pre-existing randomization schedule as there is for studies using static randomization designs. Rather, the randomization table is dynamically built as the study proceeds. For each new patient to be randomized into the study, the IRT algorithm takes into account the balance/imbalance that will result from the assignment of the new patient to each treatment group, and assigns that patient to the group that will best serve the goal of balancing group size and, as study may require, key variables. Factors that might be considered include gender, age, stage of disease, or certain aspects of an individual’s past medical history. Dynamic randomization is sometimes referred to as a ‘minimization’ algorithm because it minimizes the imbalances in patient assignments. ICH has accepted the use of these dynamic techniques as a valid approach to randomizing subjects for drug trials.

Veracity Logic’s dynamic randomization algorithm is available as one of several randomization tools that are part of our standard CORE platform. When applied to a project, dynamic treatment assignment is tested as part of the standard project startup validation process. Three sample randomizations (with 150 subjects in each sample) are produced and provided to the client’s biostatisticians for review and approval prior to releasing the system for customer testing.

Predictive Inventory – Optimizing Drug Supply

Case Studies

The Challenge:

One of the greatest challenges in the conduct of a clinical trial is managing the expensive and often limited supply of investigational drug needed for the project. Anything that can help reduce waste and shipping costs while ensuring that clinical sites will have the drug they need when they need it is on the ‘most wanted’ list for the pharmaceutical industry. Since Interactive Response Technology (IRT) is one of the primary tools for drug assignment during a trial, the challenge has to be confronted by IRT vendors. How can control be achieved and maintained?

The Solution:

Veracity Logic’s Predictive Resupply algorithm is one of the tools for achieving efficient waste reduction while retaining an adequate drug supply where drug is needed. The algorithm takes into account a myriad of variables that impact on drug needs and timing. For example, the expected early withdrawal rate anticipated for a study can impact on the quantity of backlog maintained at a site for patient visits. Likewise, a study’s projected screen fail rate may determine the quantity of supply shipped to sites prior to randomization. The optimal number of inventory days at a site, the frequency of shipments desired by the sponsor, and shipping duration are also key impact variables that contribute to intelligent drug control.

Veracity Logic adds two more critical features to its proprietary predictive algorithm — the ability to control all key variables at the individual site level, and the ability to easily modify, on a configuration basis, the values assigned to each key variable throughout the clinical trial. In other words, we make Predictive Resupply sufficiently flexible to meet the changing, real-life needs of a study in progress.

Direct-to-Subject Shipping

Case Studies

The Challenge:

In order to help meet global enrollment targets, the Sponsor wanted to reduce the number of clinic visits each subject would need to make while still being able to assign drug every week. The goal was to find a way to deliver drug directly to subjects at home, and on a discretionary basis. Additionally, the Sponsor wanted to allow sites/subjects to be able to choose (and change their minds if need be) at a visit level whether to receive drug at home or by visiting the clinical site.

The Veracity Logic Solution:

A Direct-From-Depot option was added to the IRT system for all visits at which direct-to-home shipping would be allowed. At the Site level, the list of Resupply options in which the Site could participate was expanded to include the Direct-to-Subject option. At the Kit level, the system defined whether a particular kit type could be sent direct to Subjects (e.g., run-in kits were excluded from direct-to-subject). When all three key variables – Subject Activity, Site Resupply, and Kits – were in agreement, Direct-to-Subject shipping was enabled. The Subject visit was recorded, and an Activity Notification was sent to the warehouse with a request that the assigned kits be shipped to the subject’s address (on file at the warehouse).

Shipment options could be modified by each clinical site as needed throughout the study by means of a simple configuration change. By these methods, sites were able to easily adjust to the subject’s preferences while boosting enrollment and compliance.

Let Veracity Logic help with your study challenges!