Predicting Shelf- Life
Over time, quality characteristics of a product can change, or degrade.
We can use an example from the pharma industry in which the shelf-life of tablets are predicted. This can be compared, for example, to the potency of whiskey as it matures over time. It’s possible to use several batch samples to understand which attributes have the most effect on potency (in this case, time) and predict the shelf life based on specific parameters. In the pharma industry, these predictions are required to meet stringent specifications for regulatory compliance and must be precisely accurate.
Benefits for the company
Understanding the parameters that may affect a product’s shelf life – in time to make adjustments to counteract them – can save food and beverage industry manufacturers a lot of time and money, as well as prevent product waste.
Type of expertise/ AI domain
Internal data required
API degradation, potency data