26 AI
Relationship) modeling is a computational technique that predicts molecular activity based on chemical structure. By analyzing molecular fingerprints, MeNow’s proprietary QSAR system can forecast biological effects, assess potential toxicity (such as carcinogenic, mutagenic, ecological and respiratory risks), and optimize molecule selection with an accuracy exceeding 95%. Additionally, MeNow has built an advanced, virtual model of human skin powered by Deep Bayesian Networks. This model was developed using large language models (LLMs) that scanned vast scientific literature and was further refined by integrating thousands of human skin transcriptomic samples. As a result, this AI-driven skin model
provides an unprecedented ability to simulate molecular interactions in human skin, predict efficacy, and ensure safety in a biologically relevant context.
The science of synergy: How AI is transforming ingredient combinations Synergy is a phenomenon where the combined effect of two ingredients exceeds the sum of their individual effects, enabling more potent formulations with lower concentrations of active ingredients. This concept is particularly valuable in cosmetics, where synergistic combinations can enhance efficacy, reduce irritation, and improve stability. However, identifying these synergies using traditional methods is time- consuming, expensive, and often left to chance, as the number of possible ingredient interactions is vast. MeNow is the first company to develop an
AI-driven equivalent of the isobole method, a pharmacological technique traditionally used to quantify the interaction between two active compounds.7 The classical isobole method is used to
determine whether two compounds interact synergistically or antagonistically. It involves plotting dose-response curves for each compound individually and then analyzing their combined effect to see if the interaction enhances or reduces efficacy. Traditionally, this requires extensive laboratory testing, precise concentration
+500k Compounds
300 Compounds
270 Compounds
7 Compounds
Figure 2: MeNow’s patented AI technology for the discovery of new natural bioactives, has discovered seven new compounds for the activation of SIRT1
gradients, and in-depth statistical modeling, making it impractical for large-scale screening in the cosmetics industry. MeNow’s AI system overcomes these challenges by automatically predicting synergistic interactions at scale, analyzing thousands of molecular structures, biological pathways, and ingredient compatibilities to identify optimal combinations (Figure 3A). This breakthrough allows for the efficient
discovery of powerful ingredient pairings, not only between single molecules but also within complex botanical extracts, opening the door to the next generation of optimized,
A In vitro Isobole Method
AI Predictions of Synergistic Effects In silico Adaptation
B Retinol AI Synergy Computation Additive Effect only Additive Effect only Synergy Lab Results Contributor 2 EC50
Predicted Activity contributor 2
ECM preservation Anti-ageing
Figure 3: Synergistic effect of bioactives. A: An illustration of the in vitro traditional Isobole technique, and the AI in silico adaptation. B: A synergy prediction for the combination of a pernolipid found in Phaeolepiota aurea and retinol, revealing a 24% synergy for extracellular matrix (ECM) preservation, and 32% for anti-ageing effect
PERSONAL CARE June 2025
www.personalcaremagazine.com Synergy 24% Synergy 32%
high-performance, and sustainable skin care formulations. This synergistic prediction technology opens new possibilities for developing next-generation skin care formulations that are not only highly effective but also more sustainable and resource- efficient.
Scanning nature AI is not only revolutionizing synergy detection but also reshaping the way natural bioactives are discovered. By automatically scanning scientific literature, molecular databases, and analytical outputs from techniques
■ Additive Effect ■ synergistic effect
Contributor 1 EC50
Predicted Activity contributor 1
Efficacy Prediction
Pernolipid
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