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From The Society of Cosmetic Scientists

Prove it! Decoding Cosmetic Claim Substantiation – Zoom Webinar

In the dynamic world of cosmetics, product claims play a pivotal role in influencing consumer choices.

However, ensuring that these claims are regulatory complaint, truthful, evidence-backed, and aligned with consumer expectations is paramount for building trust and fostering brand loyalty.

This event brings together leading industry experts to delve into the intricacies of substantiating cosmetic claims, exploring a comprehensive range of approaches, including clinical research, instrumental tests, and consumer user trials.

Join us as we unravel the complexities of claims substantiation and empower you to make the choices that enhance the credibility and effectiveness of your cosmetic products.

If you are unable to make the event in person, a Zoom link will be available so that you can still join us.

Key Takeaways:

  • Gain insights into the regulatory landscape governing cosmetic claims substantiation.
  • Discover the latest advancements in instrumental tests and their application in substantiating claims.
  • Explore the role of consumer research in validating product efficacy and consumer perception.
  • Uncover the intricacies of clinical studies.
  • Gain a deeper understanding of consumer behaviour and how it influences claim substantiation strategies.


There will be live presentations and round table discussions with the experts.

Lunch will be provided from 12 noon with the presentations starting at 1.00pm – finish 4.00pm. There will also be a break for afternoon tea.


Paul Cornwell PhD (Director, Business Development – TRI Princeton)

Latest Developments in Instrumental Cosmetic Product Evaluation and claim Support Testing Methods


To develop innovative products and make stronger claims, you always need to use high quality measurement techniques and testing protocols.  As the famous saying goes “If you can’t measure it, you cannot improve it” (Lord Kelvin, 1824-1907).

This presentation will describe the range of measurement techniques available for claims testing on hair, skin, nails and lips, and how different classes of tests give different levels of claim support.  It will also provide best practice advice on experimental design for claims testing, including mastering the art of translating of consumer terms into scientific language.

The presentation will conclude with descriptions of the latest developments in instrumental testing at TRI.  This will include new claims protocols for textured hair products, new and advanced spectroscopy methods for the measurement of the skin penetration of cosmetic actives, new techniques for testing lipsticks and new techniques for looking at the health of our nails.


Dr Paul Cornwell is the Business Development Director for TRI Princeton.  His role is to provide technical support for TRI clients around the world, to manage TRI’s on-line activities, and to organise educational courses and scientific events.

Paul has many years of experience working in the cosmetics industry working in various leadership roles in Unilever R&D and PZ Cussons.  He is a qualified pharmacist and experienced cosmetic scientist with extensive knowledge of hair and skin science, and product evaluation.

Paul is member of the Royal Pharmaceutical Society (of Great Britain), and the Society of Cosmetic Scientists.


Pauline Foster BSc MPhil (Managing Director, Foster and Brown Research Ltd

Implicit association testing: this is an alternative method of market research which measures implicit associations or subconscious, “gut feelings” towards brands and products which we know primarily drive consumer behaviour. These neuromarketing methods can gain superior, more accurate research insights into what consumers really want as opposed to what they say they want and allow us to dig much deeper into consumer behaviour.

We have an app – Mind-Choice which Pauline would like attendees to download on their phones beforehand if possible.

This will allow them to experience & create their own implicit experiments. The data is not collected or saved anywhere.