As published in Clinical Trials Arena
By Miranda McLaren
Cut drug wastage, reduce risk, and optimise supply with advanced, integrated technologies designed to deliver increased visibility, flexibility and accuracy.
An accurate drug supply forecast is essential for a successful clinical trial. Without it, sponsors risk a shortage of investigative medicinal product (IMP) for patients, resulting in major trial delays. To prevent the risk of stockout, many studies overestimate drug demand, ultimately wasting valuable product. Considering the high cost of drug manufacturing, this can set budgets back significantly.
Though time-consuming and subject to human error, trial professionals often rely on a manual process and spreadsheets to develop their forecast. When forecasting manually, drug supply managers may believe they only have 30 percent of drug waste in their clinical trials. However, the more realistic value is closer to 70 percent, according to deeptech software company, N-SIDE. This alarmingly high figure is primarily due to the numerous unknown variables that surface during the course of the trial.
“Most companies don’t track their level of drug waste,” says N-SIDE’s director, solution engineering, Antoine Remiot. “They begin the trial expecting about a 30 percent overage. But then the recruitment is delayed, they don’t get the expiry extension they were counting on, or something else happens, and that percentage increases with little to no visibility by the team.”
There is clearly a significant need for study teams to gain more visibility and control of their drug supply throughout the trial. While some vendors have attempted to address this need, the relative simplicity of many forecasting solutions on the market has limited their success.
It was within this landscape that the advanced machine-learning capabilities of the N-SIDE Supply App stood out to Suvoda. Through a potential integration of N-SIDE’s forecasting models with Suvoda’s own highly flexible Interactive Response Technology (IRT), an exciting opportunity to revolutionise drug supply operations began to emerge.
The power of IRT data
IRT helps clinical supply teams manage patient and drug supply logistics. The system houses important patient information used for the automation of dosage levels, visit schedules, dispensation, and more. By feeding this real-time data into N-SIDE’s forecasting tool, sponsors can use the N-SIDE Supply App to monitor live information about recruitment, dispensing, and inventory, etc. at any given time.
The increased access to data helps them assess how mid-trial events might impact their supply strategy. Should supply suddenly be at risk of going too high or too low, users are presented with a range of mitigating options, which are then managed in the IRT.
The partnership between Suvoda and N-SIDE was announced earlier this year. “When we looked at partnering with a forecasting company, it was clear to us that N-SIDE has the best-in-class software out there, especially compared to other tools that simply automate what you do in a spreadsheet,” says Anthony Encarnacao, Suvoda’s vice president, global partnerships.
“N-SIDE has machine learning algorithms based on tens of thousands of studies. They have real-life clinical programmes where they’ve saved tens of millions of dollars for top 10 pharma companies. Every existing N-SIDE customer we spoke with had only great things to say about their software.”
For N-SIDE, the benefits of a partnership with Suvoda were clear. Compared to other IRT solutions, Suvoda’s resupply algorithms have the flexibility that is needed in studies, especially those with complex designs. This enables users to handle adjustments to the forecast without reconfiguring the system.
“Using flexible software like Suvoda IRT can reduce the cost up to 10 or 20 percent because it allows you to tweak some parameters in the system that you cannot adjust in other systems,” explains Remiot.
This flexibility becomes extremely valuable when you consider that so much of a clinical trial is unknown at the start, forcing sponsors to approximate recruitment numbers, titration probabilities, treatment duration, and weight distribution, etc. Integrating real-time IRT data with a best-in-class forecasting solution enables the ongoing optimisation of the original forecast, creating a solution that literally keeps getting better and more accurate.
“With clinical trials, you never know what’s going to happen,” remarks Remiot. “We take the data from Suvoda’s IRT and use our machine learning capabilities to refine the previous assumption to generate an updated forecast. You’re not relying on original assumptions, which might be six months old. It’s more accurate, it reduces costs, and it avoids risk.”
This precision is made possible by N-SIDE’s advanced mathematical models and tight confidence interval.
“We’re even seeing benefits of operational efficiency, with customers indicating that the simple ability to automatically pull the IRT actuals into the N-SIDE Supply App decreases their study team workload by a couple of hours a week,” adds Thurman Hamlet, senior director, global partnerships at Suvoda. “We have established well-defined processes that allow our teams to quickly identify areas where we can continuously improve together, whether it’s our services teams designing integrations for cross-study analyses, or us sitting down together and looking at more innovative ways to structure predictive resupply algorithms.”
The two companies have already used the integrated solution in more than 100 clinical studies. The feedback has certainly been positive, with many sponsors continuing to use the solution across their portfolio. Encarnacao remarks, “I’ve been working with clinical trial technology for almost 30 years, and this is one of the fastest adoption rates I have seen. From a technology partnership perspective, it has definitely been a triumph.”
Drug supply has been a high-risk pain point in the clinical trial world for many years, but this new solution is changing the game. By combining advanced technology from two leaders in the clinical trial space, this new approach reduces costly wastage while ensuring the right drugs get to the right patients on time.