Precision Targeted Metabolomics with Defined Quantification Rigor
Price
Academic
Starting at $126 per sample for 20 samples or more, with pricing varying based on metabolite coverage and quantification requirements. Add $400 extra per channel for analyzing 19 samples or less. Plus $200 flat fee for sample handling per project.
Industry
Add 30% university overhead charge to the above price.
Instrument
UHPLC-HRMS
Description
Overview
The FOCUS Metabolite Assay Platform is a flexible, targeted metabolomics solution designed for hypothesis-driven studies, biomarker validation, and accurate quantification of selected metabolites.
FOCUS complements TMIC’s existing global metabolomics platform:
- HP-CIL LC–MS → high-coverage discovery metabolomics
- Global Lipidomics → comprehensive lipid profiling
- FOCUS → targeted analysis and quantification of specific metabolites
Together, these platforms provide a complete workflow from discovery to validation.
When to Use FOCUS
FOCUS is ideal when:
- Accurate quantification of specific metabolites is required
- Biomarkers identified from discovery studies need validation
- Customized metabolite panels are needed
- Mechanistic or pathway-focused studies are being conducted
- Quantification needs to align with study goals and budget
Quantification Options
FOCUS offers three levels of quantification, allowing users to balance accuracy, coverage, and cost.
1). Absolute Quantification (Clinical-Grade)
- One-to-one isotope-labeled standards for each metabolite
- Standards spiked into individual samples prior to extraction
- Corrects for extraction efficiency, matrix effects, and ion suppression
- Suitable for:
- Clinical research
- Cross-study comparisons
- Reference range determination
2). Semi-Quantitative Analysis
- Estimated concentrations using external standards (isotope or non-isotope)
- A small number of internal standards used to monitor instrument performance
- No sample-specific spiking
- Suitable for:
- Comparative studies with approximate concentration values
- Relative quantification within a study
3). Relative Quantification
- Based on signal intensities
- Optional normalization using internal standards
- Suitable for:
- Comparative studies with signal intensities
- Relative quantification within a study
FOCUS Assay Menu
FOCUS assays are modular and customizable, with each assay built around a core panel that can be expanded to meet specific needs. The following assays are currently available, with additional panels under development—please check back regularly for updates.
1) FOCUS IMA (Ionic Metabolite Assay)
- Central carbon metabolism (glycolysis, TCA cycle, PPP)
- Energy and redox metabolism (ATP/ADP/AMP, NAD⁺/NADH, NADP⁺/NADPH)
- Highly polar and ionic metabolites
- Includes phosphorylated metabolites, nucleotides/nucleosides, amino acids, and organic acids
2) FOCUS GMA (Gut Metabolism Assay)
- Short-chain (C2–C6) and medium-chain fatty acids
- Primary, secondary, conjugated, and unconjugated bile acids
- Microbiome-derived metabolites
- Host–microbiome interactions, gut health, and inflammation
3) FOCUS Acyl-CoA Assay
- Coenzyme A thioesters (short- to long-chain acyl-CoAs)
- Key intermediates in central carbon and lipid metabolism
- Provides insight into metabolic flux and pathway activity
4) FOCUS Acylcarnitine Assay
- Short-, medium-, and long-chain acylcarnitines
- Indicators of mitochondrial function and fatty acid oxidation
- Widely used markers for metabolic and mitochondrial disorders
5) FOCUS Target Metabolite Assay (TMA)
- Fully customizable targeted panel
- Any metabolites of interest (subject to feasibility)
- Ideal for:
- Hypothesis-driven research
- Biomarker verification and validation
- High-rigor quantification of selected metabolites
Integration with TMIC Platforms
FOCUS is designed to integrate seamlessly within TMIC’s Global Metabolomics framework:
Discovery → Validation Workflow
-
- HP-CIL LC–MS for broad metabolome coverage
- Lipidomics for comprehensive lipid profiling
- FOCUS assays for targeted quantification
This integrated approach enables:
- High-confidence biomarker discovery
- Robust validation and interpretation
- Efficient study design
Statistical Analysis
- Basic statistical analysis is included.
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