In this white paper, we review the current approaches used to guide experimental design and present why machine learning poses a significant improvement. Intellegens is using Alchemite™ to accurately map the formulation landscape, improve understanding of specific properties and suggest the most important experiments to be carried out.
Design of experiments is used to guide experimentation and find the best combination of parameters in the fewest number of steps. The advent of machine learning approaches has enabled innovative companies to augment their design of experiments with a more guided approach to not only find the ‘answer’ the quickest but also identify experiments to best improve the underlying model. This leads to a continual cycle of improved operational performance. Here we highlight the traditional approaches to experimental design and how Intellegens is using machine learning to disrupt this methodology. Our approach results in significant savings in cost and time in the product development lifecycle.