Observability in Clinical Supply Management

We’ve been using the term “observability” when describing the Bluefin platform. In a general sense, an observability platform takes information and metrics and creates an analysis of where issues might arise. They rely on having a solid source of truth, meaning they have direct and up-to-date access to data from its original source.

We’ll come back to observability. Let’s briefly cover the current state of clinical supply forecasting.

Forecasts are created from an input of parameters which a forecasting tool then takes to make a prediction. After that, it’s up to the clinical supply manager to take action on that information. The forecasts are only as accurate as the information going in; and for many studies, early on, the information available may be vague. The clinical supply manager will adjust forecasts over time as actuals come in and try their best to avoid excessive expiry of product, or worse, a shortage.

When a forecast is accurate, it is incredibly valuable for understanding how the drug is progressing through the study and where supply chain issues might arise. When it isn’t accurate, it can give teams a false sense of security and result in shortages.

That reason is why Bluefin is designed as an observability platform, with forecasting as a core component. We firmly believe that a great forecast is only as good as the monitoring and insights around it. We’ve put a lot of engineering effort into making forecasts extremely fast to generate. This makes Bluefin able to generate real-time insights from the forecast scenario plus study and inventory actuals. Bluefin can predict ahead and highlight problem areas proactively.

Of course, a great observability platform also needs to be close to the source of truth. By setting up automated or regular imports from other systems, like a traditional IRT/RTSM, we can unify clinical supply data, we reduce the fragmentation of knowledge and errors that can occur when information is spread across multiple offline spreadsheets.

A great observability platform should also be looked for problems across organizations. A forecast, traditionally, is done on a per study basis. Bluefin’s ability to reconcile demand forecasts on a portfolio level means it can more holistically look at depot inventory on a basis of shortage risk for studies using a pooled supply. It provides tools for the user to adjust lot allocations and affect how a particular product is used across a portfolio.

You can see why “forecasting” isn’t the full way to describe what we’re working on. A forecast is a fantastic feature of our product, with forecasts calculated in just seconds and a flexible reporting platform to slice and dice however you see fit. But it is a feature of Bluefin’s platform. Without study data to derive insights from, it exists in a vacuum, and conclusions may not be fully informed.