KEY BENEFITS
INDUSTRIES
- Fast-moving consumer goods
- Pharmaceuticals
- Speciality chemicals and plastics
- Paints, inks and coatings
- Foods, flavours and fragrances
Whatever your product – plastics, pharmaceuticals, paints, inks, cosmetics, foodstuffs, personal care products – formulation is difficult. You must bring together the right combination of ingredients and processing conditions to deliver a quality product, repeatably, while controlling cost and minimising environmental impact.
Alchemite applies powerful machine learning to guide your testing program and identify formulation improvements that deliver better product performance, reduce costs, and meet regulatory constraints. It gets more value from your existing data, even where that data is sparse and noisy, and helps you to find the most efficient routes to improve the quality of this data and your understanding of it.
Formulation design case study
Domino Printing Sciences applied Alchemite to help guide testing and find optimal formulations for their inks. This case study shows how to reduce time-to-market, identify new candidate formulations, and enable reformulation in response to market, environmental, or regulatory drivers.
View a recorded webinar with guest speaker, Dr Josie Harries, Ink Technology Manager at Domino.
You can also read and download a PDF summary of the Domino Printing Sciences case study.
“We were impressed with the ability of Alchemite™ to identify novel formulations quickly and accurately.This enabled us to make the most of limited lab resources and continue innovating during the COVID-19 lockdown.”
– Dr Andrew Clifton, Director of Marking Materials and Test Engineering Team at Domino
Alchemite for Formulations
Alchemite is ideal for quick response to formulation or reformulation challenges.
- Gain new insight from historical data, even if that data has significant gaps
- Enable advanced, data-driven Design of Experiments
- Guide which tests to do next
- Identify novel formulation candidates that you would not otherwise find.
