Some of my Bioclinica colleagues and I recently attended CBI's IRT 2016 conference in Philadelphia. While there were plenty of interesting topics discussed at the conference, one presentation particularly stuck out to me: the benefits of connecting supply chain forecasting for clinical trials more closely with interactive response technology (IRT) software. The reliance of effective clinical trial forecasting on IRT data is well understood within the clinical trial world, and was a big talking point at the conference. As IRT systems are moving into the next generation, is it time to combine the two?
One key benefit of moving in this direction is the efficiency of using a single solution to provide a clear picture not only of where your subjects are in the lifecycle of the study, but also of the demand they're going to require for upcoming visits. Most IRT systems are good at the former, but have limited capability to provide a detailed long-term vision of the supply chain. With embedded forecasting in the IRT, we could have the best of both worlds: real-time transactional IRT data continuously feeding a highly accessible visualization of the complete supply chain to the end of the study.
Consider a typical trial example where 50 subjects are expected to be randomized in Russia, but enrollment has been delayed in that region. However, enrollment has been faster than expected in Brazil. This would be bad news for the trial and its supply if too much supply has been shipped to Russia in preparation for subjects that won't be enrolled. With supply chain forecasting integrated directly in the IRT, you may be more willing to delay early decisions like this since you trust the forecasting and know you can efficiently and routinely check the status of subjects, where they're located and the current and expected enrollment rates. Most importantly, the system will tell you where supplies should be shipped exactly when that decision needs to be made. Historically, a miscalculation in forecast, like the example above, could result in wasted supply in one location and increased, unmet demand in another. To meet the unplanned demand, either additional product would have to be manufactured, packaged and shipped, or your plan would need to assume at the beginning a much larger overage in order to be able to react to such situations. In either case, the cost of your trial supply may be higher than it needs to be.
By understanding in real time, all the time, where subjects are from a timeline and geographical perspective, you’ll be able to build a better logistics plan when you're planning depot-to-depot transfers or planning resupply settings at a site level. The cost benefit to this integration is recognized through improved shipment planning and a reduction in logistics costs by decreasing the number of unnecessary shipments.
With all the potential benefits of combining supply chain forecasting and IRT software, it's surprising that not many companies are doing it. At Bioclinica, Optimizer, our powerful forecasting and demand planning technology, can interface and import actuals from the Trident IRT system. Optimizer allows us to adjust enrollment rates and predict for new subjects to give a transparent view of what the supply should be for the duration of a trial. This provides our customers with a great viewpoint of their trial. While this is a good start, we're in the process of rethinking how to leverage this capability further and how to make the systems work together seamlessly, enabling supply chain management to be more proactive and thereby reduce both cost and risk.
It's clear that the industry can benefit from moving toward a goal of integrating supply chain forecasting and IRT software. What are your thoughts on such an integration? Please leave a comment below or contact me at firstname.lastname@example.org; it would be great to hear your feedback.