The applied predictive formulation science, Hydrophilic Lipophilic Difference – Net Average Curvature (HLD-NAC) is very powerful to find matching ingredients, resulting in improved stability and efficacy of end-products. Although it has been applied for many years, there is still a limited use in formulation developments and ingredients thereof. The equation requires practical parameters of surfactants and oils. Once generated, compatible combinations can be predicted to develop and optimize specific formulations. The ingredient parameters generated via the model are predictive and sustainable: you can use them over and over, allowing you to move away from trial-and-error and use digitalization in product developments. This is a very efficient way to enhance the properties in addition to reducing the complexity, time and cost of developing formulations or ingredients. When combined with High Throughput (HT) screening for automated, parallel and small-scale preparation of samples and end-products, further efficiencies can be achieved. The HLD-NAC approach and the required ingredient parameters will be explained via practical applications to showcase how it can lead to efficient developments of a broad range of products. The use of HT screening will be explained as well and why this is needed to fill up the ingredient database of our HLD-NAC app. This app can be used as the first stage of experimentation by formulating emulsions digitally, followed by a drastically streamlined amount of practical lab work needed, compared to trial-and-error. This digital HLD-NAC approach will be demonstrated, to show how this can boost efficient emulsion and ingredient developments.
