What do you expect from a Clinical Trial Supply Optimization solution? Unlike a simple forecasting tool, where the expectation is to have an IMP packaging release plan to cover the average demand, you usually start working with a supply optimization software solution to help you to: reduce the trial supply costs minimize drug waste mitigate […]

Visualizing your clinical trial supply forecasts at portfolio-level helps strategic and operational decision-making. By intuitively interacting with your optimized data at this level, you have a clear overview of your portfolio and can immediately identify areas of improvement. Using an advanced optimization tool for clinical trial supply management, combined with business intelligence dashboards, such as […]

For decades, risk in clinical trial supply has been mitigated by maintaining buffers of drug available throughout the supply chain. Buffers are necessary to cover the inherent variability in the demand of clinical trials. When not consumed by patients during the trial, these buffers result in unused drug, or “overage”. When investigational medicines are readily available and not expensive, having higher overage in a study can be accepted by the company in order to ensure no risk to patient service level.

N-SIDE has signed with Sanofi an amendment to their agreement to use N-SIDE’s risk-based production planning optimization solution This agreement comes at the successful conclusion of the pilot study conducted by Sanofi and N-SIDE using N-SIDE’s innovative solution to optimize end-to-end production planning at the clinical program level. N-SIDE is happy to continue the collaboration […]

Critical decisions are taken during protocol design. It is essential to maintain patient centricity and respect site constraints, but it is also an opportunity to evaluate the supply impact. Different scenarios can be investigated with an advanced simulation and optimization tool that accurately models both the clinical design and the supply aspects of the protocol. […]

Pharmaceutical organizations are putting more and more pressure on clinical supply chain managers to minimize study overage. Study overage represents the kits that will expire unused at the investigational sites, local depots and central depot. Some overage is absolutely needed, both as insurance against the unexpected events that can occur during the trial and as a result of the design of the protocol and distribution network. 
But often the question is raised (and not only by higher management): is the requested amount of overage absolutely necessary or is it possible to decrease it?