Dermatology & Cosmetics

An active either changes skin biology or it does not, and a claims file has to show which. GenXMap turns 2D or 3D skin model and microbiome data into the statistical evidence a claim rests on, with methods documented clearly enough to be independently reproduced.

The Claims Substantiation Package

Built for the moment a claim has to hold up: GenXMap uses multiomics and extracellular vesicle profiling to establish whether an active changes skin biology, which biological processes are affected, how these changes connect across molecular layers, and whether the effect is reproducible across donors.

• Multiomics profilingintegrating transcriptomics, proteomics, metabolomics and microbiome data to capture the biological response at multiple levels
• Extracellular vesicle / exosome profilingcharacterising vesicle-associated molecular signals to investigate changes in intercellular communication and skin signalling
• Differential analysistreated versus untreated skin, with effect sizes and statistical significance clearly reported
• Pathway and mechanism analysistranslating molecular changes into coherent biological processes rather than isolated gene, protein or metabolite lists
• Cross-omics integrationconnecting genes, proteins, metabolites, microbial profiles and extracellular vesicle signals to build converging evidence for an active’s biological effect
• Donor variability tested explicitlydistinguishing a reproducible active effect from inter-donor variation
• Iteration comparisondifferentiating formulations through their integrated biological signatures, beyond what can be captured by a single endpoint

The work starts before the bench: how many donors and biological replicates are needed before an effect can be distinguished from donor variability at all — a question that has to be settled before sampling, not after.

The result is more than a dataset or a list of differentially expressed genes. It is a reproducible, multi-layer biological evidence package connecting an active to measurable changes in skin biology, the pathways involved, intercellular signalling, and the consistency of those effects across donors.

The questions we take on

• Does an active measurably change skin biology — and what is the magnitude of that effect?
• What biological processes does it affect, and do transcriptomic, proteomic and metabolomic signals converge on the same response?
• Does the response extend beyond the skin itself — through the microbiome or extracellular vesicle signalling — when these layers are relevant to the claim?
• Is the biological effect reproducible across donors, or driven by individual donor variability?
• Can we distinguish a meaningful biological response from technical or biological noise?
• Do formulation iterations produce genuinely different biological signatures, and can those differences be linked to the active or formulation change?
• Can the observed molecular changes be connected into a coherent biological story strong enough to support a claim?

What the report contains

Methods with exact tool versions, parameters and thresholds. QC and cohort-level figures. Statistical results. An interpretation written against the biological question you started from.

Built to be audited or reproduced by a third party.

When the active works through extracellular vesicles

Some dermo-cosmetic actives do not act through a single intracellular pathway. They may alter cell-to-cell communication, leaving a biological signature not only in the cells themselves, but also in the extracellular vesicles they release.

Capturing that response requires more than measuring the cellular transcriptome. The vesicles need to be isolated, characterised, quantified and their molecular cargo analysed — creating an additional biological layer that can be integrated with the response of the cells that produced them.

The Exosome Characterization Platform

GenXMap combines omics-based cargo analysis with specialised extracellular-vesicle characterisation capabilities developed with the Faculté de Pharmacie de Marseille. This enables vesicle populations to be characterised through their size, concentration and relevant markers, while their molecular cargo can be profiled and interpreted alongside cellular transcriptomic and multiomics data.

The result is a two-sided view of cell communication: what changes inside the cells, and what those cells communicate to their environment.

By integrating extracellular-vesicle data with transcriptomics, proteomics, metabolomics and, where relevant, microbiome profiling, GenXMap can determine whether an active produces a coherent, reproducible biological response across multiple levels of skin biology.

For claims involving cell communication, this provides a stronger evidence chain than measuring a single intracellular endpoint alone.

From Data to Biological Evidence

The laboratory work behind these analyses runs on OMICS4, GenXMap’s platform site, with sample requirements, logistics and turnaround defined for each study.

But the analysis does not have to start in our laboratory.

We also work with data generated elsewhere. Existing transcriptomics, proteomics, metabolomics, microbiome or extracellular-vesicle datasets, from an earlier study, an internal R&D programme or another provider, can be analysed and integrated on their own terms.

What determines the analysis is the biological question, the study design and the metadata available, not who generated the data or where the sequencing was performed.

Where multiple omics layers are available, we integrate them to identify converging biological signals, distinguish robust effects from technical or donor variability, and build a coherent evidence package around the claim.

The data may come from different platforms, providers or experiments. The biological question remains the starting point.

Explore the platforms on OMICS4