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Formulation design

Make better use of experimental resources; get to market faster

KEY BENEFITS

  • Design and optimise formulated products, exploiting all available data
  • Focus experiment and maximise value from results, saving months of work
  • Find novel solutions to market, regulatory, and environmental challenges

RELATED TOPICS

  • Materials overview
  • Plastics and elastomers
  • Design of experiments
  • Process optimisation and control

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.

View recorded case study webinar:

Alchemite™ helps guide testing and find optimal formulations

Case studies and publications

Formulation design at Domino Printing Sciences

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.

“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

READ CASE STUDY

White paper: Machine learning for adaptive experimental design

Identifying the optimal composition and processing parameters to achieve commercial performance goals as quickly as possible is the key objective of formulation design projects. Machine learning identifies improved formulations up to 10 times quicker than traditional approaches, by focusing experimental effort directly on formulations that will lead to successful products in as few experimental cycles as possible.

DOWNLOAD WHITE PAPER

Alchemite for Formulations

Alchemite is ideal for quick response to formulation or reformulation challenges.

  • Gap-fill and validate sparse, noisy data from suppliers, experiment, simulation, and production
  • Auto-generate models that identify key ingredient-process-property relationships
  • Quantify uncertainty to support a rational business case for key decisions
  • Design experimental programs to support formulation or re-formulation of products with the fewest experiments
  • Identify new or improved formulations; 0ptimise process parameters to improve quality and performance
  • Capture knowledge of formulation recipes as models for sharing and re-use
FIND OUT MORE
Alchemite Analytics analysis of data

We are have a limited number of consultation sessions available
– sign up now to find how Alchemite can help you exploit your data

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Company number : 10591395 | Vat number: 267525774
Address: Eagle Labs, 28 Chesterton Road, Cambridge, United Kingdom, CB4 3AZ
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