Ageless Beauty · Genes & Aesthetics

Reshaping the Science of Beauty with Computation

Health and longevity are the foundation; beauty is the growth engine. Transforming A/T/C/G into commercial-grade aesthetic insights--the same WGS data supports both health and beauty.

Beauty Seekers

Understand how genes affect your beauty--which aesthetic procedures suit you best

Aesthetic Clinics / Brands

Evaluate gene-level precision aesthetics and anti-aging peptide screening capabilities

Investors / Peers

Assess differentiated technical strength and Chinese population data assets

Four Steps to Your Genetic Beauty Profile

01

Obtain Genetic Data

Partner sequencing institutions collect and submit samples. Already have a VCF file? Upload directly, start at zero cost. The same data supports both health-longevity and beauty interpretation.

02

AI Three-Pipeline Parallel Computing

Pipeline A: PRSice-2 + PGS Catalog for aesthetic target risk scoring. Pipeline B: Protenix V2 + FoldX + ProteinMPNN for molecular-level screening. Pipeline C: QIIME2 + ANNOVAR for microbiota-gene cross-mining.

03

Receive Genetic Beauty Profile (GBP)

A report you can understand--"Your collagen retention ranks in the 80th percentile, recommend Thermage." "MC1R variant, high pigmentation risk from IPL, consider picosecond lasers instead." Actionable beauty recommendations.

04

Lifelong Tracking & Annual Re-analysis

Track epigenetic clock every 6 months. Annual re-analysis--new databases + new models + new targets. Quantified anti-aging results: biological age changes, collagen indicator changes.

Verifiable Engineering Foundation

Not a vision on a slide--but proven, validated, deliverable engineering capability

MetricValueNote
Structure Prediction AccuracypLDDT 95.4Pipeline B: Protenix V2 triple-engine cross-validation
Molecular Docking AccuracyΔΔG ~1.1 kcal/molPipeline B: FoldX literature benchmark
Immunogenicity Pre-screeningAUROC 0.7547Pipeline B: MHCflurry TESLA benchmark
PRS Computing EnginePRSice-2 ✅Pipeline A: deployed and verified
PGS Catalog Weights4,000+ publishedPipeline A: includes aesthetic target weights
Chinese Population CalibrationGVM+NyuWa+WBBCPipeline A: triple-database cross-calibration
Localized Models38 SOTAAll tools locally deployed, data never leaves
HLA TypingDual-tool crossPipeline C: OptiType+Polysolver verified

Honest Boundaries

What we can and cannot do--clear boundaries build trustworthy reliability

What We Can Do

  • Compute polygenic risk scores (PRS) for aesthetic targets based on GWAS data
  • Protein 3D structure prediction + molecular docking + peptide design (Pipeline B all tools 100% deployed)
  • 16S/ITS skin microbiome analysis + host gene cross-mining (Pipeline C designed, pending deployment)
  • Chinese population calibration (GVM + NyuWa + WBBC)
  • B2B2C model--serving as the computing backbone for aesthetic/anti-aging institutions

What We Don't Do

  • No clinical skin diagnosis--GBP is risk assessment, not dermatological diagnosis
  • No skincare product recommendations--we output causal maps, not product ads
  • No sequencing--we do computational analysis, samples are provided by partners
  • No "gene editing for beauty"--gene editing is for genetic disease treatment
  • Targets with insufficient East Asian coverage are flagged "needs validation"

Technical Strength & Capabilities

Three layers of differentiation: model precision -> pipeline synergy -> data accumulation

Layer 1

Model Precision

38 SOTA models + multi-model cross-validation

Protenix V2 + ESMFold + Boltz-2 triple-engine structure prediction, Genos + AlphaGenome + Evo2 triple-model VUS scoring. No single-model user can match our cross-validation precision. All tools locally deployed, data never leaves the country.

Layer 2

Pipeline Synergy

Three-pipeline cross-validation

PRS pipeline (risk quantification) + protein pipeline (molecular screening) + microbiome pipeline (microbiota-gene cross-analysis). Single pipelines can be copied, but three-pipeline cross-validation creates differentiation. Same data yields three insights at near-zero marginal cost.

Layer 3

Data Accumulation

Chinese population aesthetic PRS calibration data

Every GBP report accumulates Chinese population gene-aesthetic phenotype association data. This data fuels continuous model optimization, taking years to build from scratch. Health-longevity engine data assets can be directly transferred, not starting from zero.

Glossary

PRSPolygenic Risk Score--combining small effects across multiple genetic loci to quantify overall genetic risk for a phenotype
GBPGenetic Beauty Profile--a personalized "gene -> beauty" digital archive based on genomic data
MMPMatrix Metalloproteinase--enzyme family that degrades collagen, core driver of skin aging
MC1RMelanocortin 1 Receptor--regulates melanin synthesis, variants cause photosensitivity and pigmentation risk
FLGFilaggrin--key skin barrier protein, mutations lead to barrier fragility
SirtuinSirtuin--deacetylase family regulating aging, metabolism, and inflammation as core targets

Start Building Your Genetic Beauty Profile

The same WGS data supports both health-longevity and beauty interpretation.

Health and longevity are the foundation; beauty is the growth engine

DiVo Gen²AI · Genomics + Protein Engineering AI Computing Services