AI Cosmetic Effect Prediction With Virtual Formulation Testing

Solution Overview

Problem

The cosmetics industry faces time-consuming and resource-intensive traditional methods for developing and testing new cosmetic ingredients and formulations, which often fail to accurately predict performance across diverse consumer groups.

Innovation Solution

Utilizing machine learning and artificial intelligence to predict cosmetic effects of ingredients through virtual testing, simulating effects on virtual models, and generating formulations, reducing the need for extensive physical testing.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional laboratory testing and human trials are used to evaluate cosmetic ingredients, then the reliability of efficacy evaluation is improved, but the time required and resources consumed increase significantly

Engineering Contradiction:

Improveefficacy evaluation accuracyVSAvoiddevelopment time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent creates virtual copies of human skin and hair models that replicate physical characteristics, allowing unlimited virtual testing without the time and ethical constraints of real human trials. These digital twins can be repeatedly tested with different cosmetic formulations simultaneously, accelerating development while maintaining evaluation reliability through standardized virtual assessment protocols.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent replaces physical laboratory testing mechanisms with computational modeling and machine learning algorithms. The system uses AI to predict cosmetic efficacy by analyzing interactions between ingredients and virtual skin/hair models, substituting manual laboratory procedures with automated digital simulations that reduce testing time while maintaining scientific validity.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If traditional human trials are conducted to test cosmetic products, then the reliability of results is improved, but the cost and time investment increase

Engineering Contradiction:

Improveproduct performance predictionVSAvoidresource consumption

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The patent creates virtual copies of human skin and hair models that replicate physical characteristics, allowing unlimited virtual testing without the time and ethical constraints of real human trials. These digital twins can be repeatedly tested with different cosmetic formulations simultaneously, accelerating development while maintaining evaluation reliability through standardized virtual assessment protocols.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent changes the fundamental parameters of testing from physical to digital domains. By transforming real-world cosmetic testing into virtual simulations with adjustable parameters (skin type, age, environment, formulation concentration), the system maintains predictive reliability while dramatically reducing resource consumption through infinite replicability and parallel processing.

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If extensive physical testing is performed to evaluate cosmetic ingredients, then the accuracy of efficacy assessment is improved, but the speed of development decreases

Engineering Contradiction:

Improvecosmetic effect measurementVSAvoiddevelopment speed

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent replaces physical laboratory testing mechanisms with computational modeling and machine learning algorithms. The system uses AI to predict cosmetic efficacy by analyzing interactions between ingredients and virtual skin/hair models, substituting manual laboratory procedures with automated digital simulations that reduce testing time while maintainingscientific validity.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent enables continuous, uninterrupted virtual testing that can run simultaneously without the logistical constraints of physical laboratories. Multiple formulations can be tested on diverse virtual models concurrently, and the system continuously learns from new data to improve prediction accuracy, maintaining both measurement precision and rapid development throughput.

Inventive Principle:

Principle #20Continuity of useful action

Data Source

PatentUS20260041221A1Method for predicting cosmetic effects of ingredients using machine learning

Publication Date: 2026.02.12 ELC MANAGEMENT LLC

AI summary

The present disclosure provides a method for predicting cosmetic effects of ingredients using machine learning. A computing device trains a machine learning model using properties of ingredients having known cosmetic effects as predictor feature values and the known cosmetic effects as target feature values. The computing device obtains a set of properties for a new ingredient and applies them to the trained machine learning model to predict cosmetic effects of the new ingredient. Additionally, the computing device generates a formulation for a new beauty product with the new ingredient using a generative AI model trained on existing beauty product formulations. A virtual cosmetic testing system simulates the predicted cosmetic effects on a virtual person over time. The virtual cosmetic testing system presents a display of the virtual person's face and runs a simulation depicting changes to the virtual person's face as the new ingredient is applied.