Technical and Evidence-Based Foundation

MetaGuard's

MetaGuard's

Model Source and Validation

Model Source and Validation

Every MetaGuard score—biological age and health risk—is built on high-dimensional metabolomics data × large-scale medical data × published biological mechanisms. This page is curated for professionals interested in technology, research, and clinical translation.

Every MetaGuard score—biological age and health risk—is built on high-dimensional metabolomics data × large-scale medical data × published biological mechanisms. This page is curated for professionals interested in technology, research, and clinical translation.

60M+

Number of medical records

2,000+

Metabolic Markers / Session

10yr+

Practical Model Operation

6

Health Risk Model

Silicon Valley Technology DNA

MetaGuard's

MetaGuard's

Core Technology Partner

Core Technology Partner

MetaGuard's technical foundation comes from deep collaboration among three world-class institutions from the San Francisco Bay Area: mProbe Inc. provides the clinical mass spectrometry platform, Stanford University provides AI models and academic validation, and HBI Solutions provides risk assessment and clinical translation capabilities.

MetaGuard's technical foundation comes from deep collaboration among three world-class institutions from the San Francisco Bay Area: mProbe Inc. provides the clinical mass spectrometry platform, Stanford University provides AI models and academic validation, and HBI Solutions provides risk assessment and clinical translation capabilities.

🏛️

3 Top Institutions

🌉

Silicon Valley · San Francisco Bay Area

🔬

Clinical + Academic + Industry

San Francisco Bay Area · Silicon Valley

A world-class center for technological and biomedical innovation

mProbe Inc.

Silicon Valley, United States

Clinical Mass Spectrometry Testing

"The world’s leading clinical-grade metabolomics platform"

CAP/CLIA Certified Laboratory

1,000+ Metabolite Tests

Clinical-Grade Data Quality

CAP/CLIA dual certification

50,000+ Samples

1,000+ Metabolites

Visit Official Website

Stanford University

Silicon Valley, United States

AI Model and Academic Foundation

"World-leading Multi-omics and Precision Medicine Research Center"

Published in 100+ top-tier journals

AI-Powered Predictive Model

Scientific Validation and Endorsement

Stanford Medicine

AI-Driven Research

100+ Top Research Publications

Visit Official Website

HBI Solutions

Silicon Valley, United States

Risk Assessment and Clinical Applications

"Expert in Large-Scale Medical Data and AI Risk Assessment"

60 million clinical data records

700+ AI Assessment Models

Multi-System Risk Stratification

60 million data records

700+ AI Models

Multisystem assessment

Visit Official Website

Partnership Declaration

These three institutions are the strong backbone behind Homnia’s technology: mProbe Inc. and HBI Solutions are not only core shareholders, but also deeply involved in technology development; Stanford University provides the academic research foundation and support for scientific validation. Through this exclusive scientific collaboration system, Homnia brings world-class metabolomics analysis, AI-powered health risk models, and clinical mass spectrometry capabilities into everyday health decision-making for individuals and clinics.

這三個機構是 Homnia 技術的重要後盾：mProbe Inc. 與 HBI Solutions 不僅是核心股東，也深度參與技術開發；史丹佛大學則提供學術研究基礎與科學驗證支持。

透過這套專屬的科學合作體系，Homnia 將世界級的代謝體分析、AI 健康風險模型與臨床質譜能力，真正導入個人與診所的日常健康決策中。

These three institutions are the strong backbone behind Homnia’s technology: mProbe Inc. and HBI Solutions are not only core shareholders, but also deeply involved in technology development; Stanford University provides the academic research foundation and support for scientific validation. Through this exclusive scientific collaboration system, Homnia brings world-class metabolomics analysis, AI-powered health risk models, and clinical mass spectrometry capabilities into everyday health decision-making for individuals and clinics.

mProbe Inc.

Silicon Valley, United States

Clinical Mass Spectrometry Testing

"The world’s leading clinical-grade metabolomics platform"

CAP/CLIA Certified Laboratory

1,000+ Metabolite Tests

Clinical-Grade Data Quality

CAP/CLIA dual certification

50,000+ Samples

1,000+ Metabolites

Visit Official Website

Stanford University

Silicon Valley, United States

AI Model and Academic Foundation

"World-leading Multi-omics and Precision Medicine Research Center"

Published in 100+ top-tier journals

AI-powered predictive model

Scientific Validation and Endorsement

Stanford Medicine

AI-Driven Research

100+ Top Research Publications

Visit Official Website

HBI Solutions

Silicon Valley, United States

Risk Assessment and Clinical Applications

"Expert in Large-Scale Medical Data and AI Risk Assessment"

60 million clinical data records

700+ AI Assessment Models

Multi-System Risk Stratification

60 million data records

700+ AI Models

Multisystem assessment

Visit Official Website

01 · Data Sources and Baseline Construction

Large-scale medical data

Large-scale medical data

As the Training Foundation

As the Training Foundation

Model credibility comes from the scale and diversity of the training data. MetaGuard’s data foundation includes electronic medical records, laboratory data, diagnostic codes, and long-term follow-up records, and uses an Asian adult metabolic baseline as the population reference panel for risk stratification.

Consultation:

  • Lifestyle

  • - Habits

  • - Health Status

    • - Strategy

60M+

Medical and Population Database

Over 60 million medical records, including electronic health records, laboratory data, diagnosis codes, and long-term follow-up records, are used to train and evaluate health risk models.

Metabolomic Baseline

Full metabolic profiling of tens of thousands of Asian adults

Used as a population reference panel for biological age and health risk scores, to calculate relative risk percentiles and age differences.

Multi-omics data dimensions

Metabolomics, as the intersection of clinical and biological dimensions, integrates proteomics and peptidomics to form a comprehensive multi-omics data cube.

Metabolomics, as the intersection of clinical and biological dimensions, integrates proteomics and peptidomics to form a comprehensive multi-omics data cube.

mProbe Personalized Fingerprint

Personalized metabolic fingerprint map—each node represents a metabolite, and the colors reflect relative concentration deviations.

Personalized metabolic fingerprint map—each node represents a metabolite, and the colors reflect relative concentration deviations.

01.2 · Full-Spectrum Metabolomics Data

LC-MS/MS Technology Platform

LC-MS/MS

Technology platform

Single analysis, 2,000+ metabolic markers

Single Analysis of 2,000+ Metabolic Biomarkers

Using LC-MS/MS as the core technology platform, combined with internal standards and QC strategies to minimize batch effects and instrument drift, ensuring high reproducibility and comparability across analyses.

Using LC-MS/MS as the core technology platform, combined with internal standards and QC strategies to minimize batch effects and instrument drift, ensuring high reproducibility and comparability across analyses.

Actual equipment and instruments

LC-MS/MS Mass Spectrometer Used by MetaGuard

This is the LC-MS/MS mass spectrometer that MetaGuard actually uses for comprehensive metabolomics profiling. Liquid chromatography (LC) separates metabolites in complex biological samples according to their polarity and hydrophobicity, while tandem mass spectrometry (MS/MS) provides precise mass detection and fragmentation-based identification for each metabolite, ensuring highly sensitive and highly specific measurement of more than 2,000 metabolites.

2,000+

Metabolites / Times

CAP / CLIA

Dual Laboratory Certification

< 1 mL

Blood requirements

10yr+

Continuous stable operation

MS Acquisition — 3D Signal Profile

LC-MS/MS 3D mass spectrum signal diagram: X-axis represents retention time, Y-axis represents m/z (mass-to-charge ratio), Z-axis represents signal intensity. Peaks correspond to specific metabolites, with purple/orange markers indicating key identification peaks.

LC-MS/MS 3D 質譜訊號圖：X 軸為保留時間，Y 軸為 m/z 質荷比，Z 軸為

訊號強度。高峰對應特定代謝物，紫色／橘色標記為關鍵識別峰。

Longitudinal Signal Stability · Time Series

Longitudinal measurement stability curves reflect the signal consistency of QC samples across multiple batches, verifying that batch effects have been effectively controlled.

縱向量測穩定性曲線，反映 QC 樣本於多批次分析中的訊號一致性，並驗證批

次效應已有效控制。

Metabolite Categories Covered

01

central carbon metabolism

Glycolysis, TCA Cycle, Pentose Phosphate Pathway

02

Amino acid metabolism

Glycine/Serine/Threonine, Branched-Chain Amino Acids

03

Lipid metabolism

Fatty acids, phospholipids, and acylcarnitines

04

Oxidative Stress & Inflammation

Metabolites such as methylglyoxal and lactic acid

Laboratory Accreditation

CAP Certified / CAP Certified

CLIA Certified

Our partner laboratories are dual certified by CAP and CLIA, ensuring that every analysis meets medical-grade quality standards.

合作實驗室通過 CAP 與 CLIA 雙重認證，

確保每次分析符合醫療級品質標準。

Individual Metabolite MS Spectra & Longitudinal Tracking

Panel A — Individual mass spectra of the nine metabolites

LC-MS/MS mass spectra of DHEAS, Prolylleucine, 3-(4-Hydroxyphenyl)lactate, Citrulline, Citrate, Kynumine, Gulonate, Ornithine, Phenylalanine, and other metabolites. Each figure displays the m/z characteristic peaks of the test sample (blue line) and reference sample (red line) to ensure accuracy in metabolite identification.

Panel B & C — Feature Importance Ranking and Longitudinal Tracking

Panel B shows the ranking of feature importance (importance score) for each metabolite in the biological age model, highlighting which metabolites contribute most to the prediction results. Panel C shows the longitudinal change curves of these metabolite values with chronological age (40–90 years), reflecting their biological relationship with aging.

Actual equipment and instruments

MetaGuard 使用的

LC-MS/MS 質譜儀

This is the LC-MS/MS mass spectrometer that MetaGuard actually uses for comprehensive metabolomics profiling. Liquid chromatography (LC) separates metabolites in complex biological samples according to their polarity and hydrophobicity, while tandem mass spectrometry (MS/MS) provides precise mass detection and fragmentation-based identification for each metabolite, ensuring highly sensitive and highly specific measurement of more than 2,000 metabolites.

2,000+

Metabolites / Times

< 1 mL

Blood requirements

CAP / CLIA

Dual Laboratory Certification

10yr+

Continuous stable operation

02 · Biological Age Model and Aging Rate

Regression / Ensemble

Regression / Ensemble

Predicted "Metabolic Phenotypic Age"

Predicted "Metabolic Phenotypic Age"

Using "healthy population + multi-disease groups" as training samples, applying regression/ensemble models to predict the age corresponding to the metabolic phenotype. The model outputs three core indicators and has been externally validated.

Using "healthy population + multi-disease groups" as training samples, applying regression/ensemble models to predict the age corresponding to the metabolic phenotype. The model outputs three core indicators and has been externally validated.

1

Inner Age

Predicted Biological Age — the age corresponding to metabolic features

2

Age Gap ΔAge

ΔAge = Biological Age − Chronological Age, a positive value indicates accelerated aging

3

Aging Rate Indicator

Estimates the rate of change over time based on longitudinal data, reflecting the dynamic trajectory of aging

Report Presentation Strategy

Communicate externally using a "percentile rank" and "age difference" approach to avoid misinterpreting the estimated age as a diagnostic result. The model has been running continuously for over 10 years and has accumulated a large amount of real-world application data.

Model Architecture Diagram

Multi-layer neural network architecture: taking 2,000+ metabolic features as input, extracting features through hidden layers, and outputting a predicted biological age.

Model Output Example

Chronological Age

45

Inner Age

38

ΔAge

-7

Aging Rate Index

0.84×

Percentile rank: Top 12% (slower-aging group)

03 · Health Risk Model

From Metabolic Fingerprints to the Six Major Body Systems

From Metabolic Fingerprints to the Six Major Body Systems

Six Independent AI Models

Six Independent AI Models

MetaGuard independently trains dedicated models for each body system — not a universal model; each model extracts metabolic precursor signals unique to its system.

MetaGuard independently trains dedicated models for each body system — not a universal model; each model extracts metabolic precursor signals unique to its system.

Process Overview (Simplified Description)

🔍

Feature Extraction

Select metabolite combinations significantly associated with the target disease from the full metabolome, and map them to KEGG/Reactome metabolic pathways through pathway enrichment analysis.

Select metabolite combinations significantly associated with the target disease from the full metabolome, and map them to KEGG/Reactome metabolic pathways through pathway enrichment analysis.

⚙️

Feature engineering

Normalize, batch correct, and handle missing values for metabolites. Build pathway-level features (aggregate score of metabolite expression within specific pathways).

Normalize, batch correct, and handle missing values for metabolites. Build pathway-level features (aggregate score of metabolite expression within specific pathways).

🤖

Model Training and Validation

Using gradient boosting, random forest, or deep learning variants to achieve optimal balance between AUC, calibration, and interpretability. Split data into training, validation, and test sets, and perform external validation across different populations.

Using gradient boosting, random forest, or deep learning variants to achieve optimal balance between AUC, calibration, and interpretability. Split data into training, validation, and test sets, and perform external validation across different populations.

📊

Risk Score Output

Output a relative risk score from 0 to 100, and define low, medium, and high risk ranges based on population distribution. Example: Alzheimer's disease: 0–7.3 low risk, 7.3–35.8 medium risk, 35.8–100 high risk.

Output a relative risk score from 0 to 100, and define low, medium, and high risk ranges based on population distribution. Example: Alzheimer's disease: 0–7.3 low risk, 7.3–35.8 medium risk, 35.8–100 high risk.

Metabolic Pathways — Disease Association Map

Sankey diagram showing the cross-relationships between metabolic pathways and multiple diseases

mProbe Molecular Taxonomy

Normal → Transitional → Disease Stage Metabolome Cluster Heatmap

X-axis: Different population clusters (Healthy A, Sub-healthy B, Transitional C, Disease D). Y-axis: Disease-related metabolic pathways. Color: Blue = low expression, Yellow/Red = high expression, clearly showing metabolic change trajectories during disease progression.

X-axis: Different population clusters (Healthy A, Sub-healthy B, Transitional C, Disease D). Y-axis: Disease-related metabolic pathways. Color: Blue = low expression, Yellow/Red = high expression, clearly showing metabolic change trajectories during disease progression.

Current Coverage: 6 Major Health Conditions

Each disease has its own model, training data, and validation results.

Alzheimer's disease

Low risk

0–7.3

Moderate risk

7.3–35.8

High risk

35.8–100

Stroke

Low risk

0–10.2

Moderate risk

10.2–40.1

High risk

40.1–100

Acute myocardial infarction

Low risk

0–8.5

Moderate risk

8.5–38.2

High risk

38.2–100

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)

Low risk

0–12.0

Moderate risk

12.0–44.5

High risk

44.5–100

Type 2 diabetes

Low risk

0–9.1

Moderate risk

9.1–36.7

High risk

36.7–100

Chronic kidney disease

Low risk

0–11.3

Moderate risk

11.3–42.0

High risk

42.0–100

Alzheimer's disease

Low risk

0–7.3

Moderate risk

7.3–35.8

High risk

35.8–100

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)

Low risk

0–12.0

Moderate risk

12.0–44.5

High risk

44.5–100

Stroke

Low risk

0–10.2

Moderate risk

10.2–40.1

High risk

40.1–100

Type 2 diabetes

Low risk

0–9.1

Moderate risk

9.1–36.7

High risk

36.7–100

Acute myocardial infarction

Low risk

0–8.5

Moderate risk

8.5–38.2

High risk

38.2–100

Chronic kidney disease

Low risk

0–11.3

Moderate risk

11.3–42.0

High risk

42.0–100

04 · In-Depth Case Analysis: Type 2 Diabetes

From metabolic pathways to

Specific metabolites

Using type 2 diabetes as an example, demonstrate a complete technical and explanatory chain: from relevant metabolic pathways → key metabolites → directionality and literature support → specific actionable recommendations.

Demonstrating the Complete Technical and Interpretation Chain using Type 2 Diabetes: From Relevant Metabolic Pathways → Key Metabolites → Directionality & Literature Support → Specific Actionable Recommendations.

Using type 2 diabetes as an example, demonstrate a complete technical and explanatory chain: from relevant metabolic pathways → key metabolites → directionality and literature support → specific actionable recommendations.

Metabolite Interaction Network Diagram

Network diagram showing the connections among metabolic pathway nodes related to type 2 diabetes—red nodes indicate key metabolites that are consistently upregulated in high-risk populations, and the edges represent metabolic reactions or enzyme-catalyzed relationships.

Upgraded to high risk

General Node

protective

Citrate Cycle (TCA)

At the core of mitochondrial energy metabolism, reduced TCA cycle flux in diabetic patients leads to the accumulation of lactate and pyruvate.

Pentose & Glucuronate Conversion

Abnormal activity in the pentose phosphate pathway may affect NADPH production and the capacity for oxidative stress regulation.

Amino Sugar Metabolism

Overactivation of the hexosamine pathway is an important mechanism of insulin resistance and is strongly associated with a variety of diabetes complications.

Citrate Cycle (TCA)

At the core of mitochondrial energy metabolism, reduced TCA cycle flux in diabetic patients leads to the accumulation of lactate and pyruvate.

Amino Sugar Metabolism

Overactivation of the hexosamine pathway is an important mechanism of insulin resistance and is strongly associated with a variety of diabetes complications.

Pentose & Glucuronate Conversion

Abnormal activity in the pentose phosphate pathway may affect NADPH production and the capacity for oxidative stress regulation.

Related Metabolic Pathways (Excerpt)

1

Amino sugar and nucleotide sugar metabolism

2

Glycolysis / Gluconeogenesis

3

HIF-1 signaling pathway

4

Pentose phosphate pathway

5

Glycine, serine and threonine metabolism

6

Propanoate metabolism

The aforementioned pathways exhibit high biological relevance to glucose metabolism, insulin sensitivity, oxidative stress, and microvascular complications.

Using pyruvate as an example: Practical recommendations

✓

Avoid high-glycemic-index foods to reduce the metabolic burden on glucose metabolism.

✓

Increase aerobic exercise to improve mitochondrial function and glucose metabolism efficiency.

✓

Supplementing specific B vitamins helps promote the flow of glycolytic products into the TCA cycle.

All recommendations are supported by biological mechanisms and scientific literature, with full citations included in the report.

Key Metabolites and Directionality

Percentage variance in concentration compared to general population baseline.

Pyruvate

+1%

Positive correlation

During the glucose tolerance test, the rise in levels is delayed and remains elevated, reflecting decreased pancreatic islet function.

Lactate

+25%

Positive correlation

Abnormal glucose metabolism is strongly associated with insulin resistance.

Methylglyoxal

+18%

Positive correlation

Glycation stress marker, accelerating microvascular damage

beta-D-Glucose

+12%

Positive correlation

Directly reflects the extent of blood glucose metabolism imbalance.

Supporting Evidence

Report citation note: In patients with diabetes, during the glucose tolerance test, pyruvate levels rise later and remain elevated, reflecting abnormalities in glucose metabolism and impaired insulin action, and may be associated with reduced islet function.

Report citation note: In patients with diabetes, during the glucose tolerance test, pyruvate levels rise later and remain elevated, reflecting abnormalities in glucose metabolism and impaired insulin action, and may be associated with reduced islet function.

Metabolite Interaction Network Diagram

Network diagram showing the connections among metabolic pathway nodes related to type 2 diabetes—red nodes indicate key metabolites that are consistently upregulated in high-risk populations, and the edges represent metabolic reactions or enzyme-catalyzed relationships.

Upgraded to high risk

General Node

protective

Citrate Cycle (TCA)

At the core of mitochondrial energy metabolism, reduced TCA cycle flux in diabetic patients leads to the accumulation of lactate and pyruvate.

Pentose & Glucuronate Conversion

Abnormal activity in the pentose phosphate pathway may affect NADPH production and the capacity for oxidative stress regulation.

Amino Sugar Metabolism

Overactivation of the hexosamine pathway is an important mechanism of insulin resistance and is strongly associated with a variety of diabetes complications.

05 · References and Academic Foundation

Technical white paper and complete references

Technical White Paper & Complete References

MetaGuard 報告的「附錄 4：參考文獻」收錄了多篇已發表文獻。

以下為主要涵蓋的領域：

MetaGuard 報告的「附錄 4：參考文獻」收錄了多篇已發表文獻。

以下為主要涵蓋的領域：

1

Biological Age and Multi-omics/Metabolomics Correlation Analysis

Biological Age and Multi-omics/Metabolomics Correlation Analysis

2

Metabolomic signatures of diseases such as Alzheimer's disease, stroke, myocardial infarction, diabetes, fatty liver disease, and kidney disease

Metabolomic signatures of diseases such as Alzheimer's disease, stroke, myocardial infarction, diabetes, fatty liver disease, and kidney disease

3

Mechanistic studies of metabolic pathways (glycolysis, the pentose phosphate pathway, amino sugar metabolism, etc.) and disease risk

Mechanistic studies of metabolic pathways (glycolysis, the pentose phosphate pathway, amino sugar metabolism, etc.) and disease risk

4

The application of metabolomics as an early predictive tool for chronic diseases in practical healthcare systems

The application of metabolomics as an early predictive tool for chronic diseases in practical healthcare systems

📄

Request the technical white paper and full references

Complete technical white paper, model validation report, and full reference list, provided for use by physicians, researchers, and when discussing potential collaborations with institutions.

Complete technical white paper, model validation report, and full reference list, provided for use by physicians, researchers, and when discussing potential collaborations with institutions.

Contact us to request

Contact us to request

Contact us to request

Institutional Partnership Inquiries

Institutional Partnership Inquiries

Your rate of aging determines your next ten years.

It's time to see clearly.

Book now

Email Contact

contact@homnia.life

Official Line

Join now

Download Product Brochure

Join now

Homnia Inc.

Homnia Inc.

TAX ID：60587851

•

Taiwan

contact@homnia.life

@homnia

Product & Services

Discover | Testing & Assessment

Discover｜MetaGuard

Discover | CTC Circulating Tumor Cells

Discover | CEDS Early Detection

Nuture | Health & Wellness

Accompany | Partnership & Tracking

Homnian

Good Fortune People | Community & Membership

Partners

Collector | Sample collecting Partner

Distributors｜Channels and Distribution Partners

Supplier | Product and Service Partner

Investor | Investment and Strategic Partners

Institutional Plans

For Business | ESG company health program

Education | Institutional Health & Wellness Programs

Healthcare | Clinical Collaboration for Medical Institutions

Goverment | Goverment public health program

Homnia Values

About us

News Center

Career center

Investor Relations

Resources and Support

Technical and Evidence-Based Foundation

Specimen Collection Cooperation Guide

Privacy Policy

Terms of Service

© 2026 Homnia Inc. All right reserved

Homnia Inc.

Homnia Inc.

TAX ID：60587851

•

Taiwan

contact@homnia.life

@homnia

Product & Services

Discover | Testing & Assessment

Discover｜MetaGuard

Discover | CTC Circulating Tumor Cells

Discover | CEDS Early Detection

Nuture | Health & Wellness

Accompany | Partnership & Tracking

Homnian

Good Fortune People | Community & Membership

Partners

Collector | Sample collecting Partner

Distributors｜Channels and Distribution Partners

Supplier | Product and Service Partner

Investor | Investment and Strategic Partners

Institutional Plans

For Business | ESG company health program

Education | Institutional Health & Wellness Programs

Healthcare | Clinical Collaboration for Medical Institutions

Goverment | Goverment public health program

Homnia Values

About us

News Center

Career center

Investor Relations

Resources and Support

Technical and Evidence-Based Foundation

Specimen Collection Cooperation Guide

Privacy Policy

Terms of Service

© 2026 Homnia Inc. All right reserved

Homnia Inc.

Homnia Inc.

TAX ID：60587851

•

Taiwan

contact@homnia.life

@homnia

Product & Services

Discover | Testing & Assessment

Discover｜MetaGuard

Discover | CTC Circulating Tumor Cells

Discover | CEDS Early Detection

Nuture | Health & Wellness

Accompany | Partnership & Tracking

Homnian

Good Fortune People | Community & Membership

Partners

Collector | Sample collecting Partner

Distributors｜Channels and Distribution Partners

Supplier | Product and Service Partner

Investor | Investment and Strategic Partners

Institutional Plans

For Business | ESG company health program

Education | Institutional Health & Wellness Programs

Healthcare | Clinical Collaboration for Medical Institutions

Goverment | Goverment public health program

Homnia Values

About us

News Center

Career center

Investor Relations

Resources and Support

Technical and Evidence-Based Foundation

Specimen Collection Cooperation Guide

Privacy Policy

Terms of Service

© 2026 Homnia Inc. All right reserved

Your rate of aging determines your next ten years.

It's time to see clearly.

Book now

Email Contact

contact@homnia.life

Official Line

Join now

Download Product Brochure

Join now

你的老化速度，

決定你未來十年。

It's time to see clearly.

Book a test now

Email Contact

contact@homnia.life

Official Line

Join now

Download Product Brochure

Join now