Integration with Experimental Testing
Integration with Experimental Testing bridges computational modeling with real laboratory data to create a unified, accurate, and highly predictive understanding of material and biological performance. By combining simulations (mechanical, thermal, molecular, genomic, statistical, or AI-driven) with empirical results from microscopy, spectroscopy, mechanical testing, chemical analysis, or biological assays, this approach ensures that models reflect real-world conditions and experiments are designed more efficiently.
This integrated framework strengthens decision-making, reduces experimental burden, accelerates development timelines, and provides high-confidence insights suitable for research, product development, and regulatory submissions.
Materials Metric brings together computational analytics and ISO 9001:2015, aligned laboratory testing to deliver a complete, validated scientific picture.
Integration Enhances Research & Development
1. Model Validation & Refinement
Validate computational models using real experimental measurements
Adjust parameters to improve accuracy and reduce uncertainty
Strengthen predictive power for materials, devices, and biological systems
2. Experiment Design Guided by Simulation
Use modeling to identify the optimal test conditions
Reduce unnecessary experiments and increase efficiency
Prioritize high-impact tests based on predictive outputs
3. Multi-Modal Data Fusion
Combine imaging (SEM/TEM/CLSM), spectroscopy (FTIR, Raman, NMR), mechanical curves, thermal data, and biological assays
Build an integrated dataset for deeper interpretation
Create correlations between structure, composition, and performance
4. Mechanistic Insight & Hypothesis Development
Reveal underlying causes of failure, degradation, or biological response
Predict long-term behavior and validate mechanisms experimentally
Enable targeted material modifications supported by evidence
5. Streamlined Regulatory & Technical Documentation
Use combined computational + experimental datasets for submission packages
Provide quantitative evidence for device performance, safety, and risk mitigation
Support GLP/ISO-aligned reporting for preclinical and material validation
Applications We Support
Materials Science & Engineering
Validating stress–strain predictions with mechanical testing
Confirming molecular modeling results with spectroscopy or thermal data
Linking microstructure (SEM/TEM) to mechanical or thermal behavior
Medical Devices & Biomaterials
Pairing simulation-based wear/fatigue predictions with bench studies
Validating cell adhesion, protein adsorption, and tissue-interface models
Correlating surface modeling results with in-vitro performance
Pharmaceutical & Formulation Science
Using dissolution or stability simulations to design focused experiments
Confirming impurity or degradation predictions with chromatographic testing
Linking molecular docking outputs to in-vitro activity
Antimicrobial & Biofilm Analysis
Predicting antimicrobial resistance trends and validating them in vitro
Using AI-based biofilm models to guide CLSM/SEM imaging and quantification
Computational Biology & Toxicology
Testing QSP or PK/PD predictions with experimental bioassays
Confirming genomic or molecular docking predictions with wet-lab data
Integration Workflow at Materials Metric
1. Pre-Study Assessment
Define computational models and experimental objectives
Identify datasets required for validation or hypothesis testing
2. Computational Simulation
Run mechanical, thermal, chemical, molecular, or AI-driven models
Predict outcomes, highlight variables, and narrow the testing focus
3. Experimental Execution
Perform microscopy, spectroscopy, mechanical testing, thermal analysis, or biological assays
Generate high-quality empirical data
Follow ISO 9001:2015–aligned procedures throughout
4. Data Fusion & Comparative Analysis
Compare empirical results with simulation predictions
Apply statistical and quantitative metrics to evaluate agreement
Identify discrepancies and adjust models as needed
5. Reporting & Translational Insights
Provide unified computational + experimental reports
Deliver design recommendations and next-step strategies
Prepare optional regulatory-supporting documentation
Why Choose Materials Metric
Materials Metric is uniquely positioned as both a computational modeling provider and a multi-disciplinary analytical testing CRO, allowing us to seamlessly connect simulations with laboratory data.
We offer:
ISO 9001:2015–certified quality systems ensuring scientific rigor
Access to advanced experimental platforms (SEM/TEM/AFM, FTIR, NMR, HPLC/GC-MS, DSC/TGA, mechanical testing, biofilm imaging, biocompatibility assays)
State-of-the-art computational tools (FEM, molecular modeling, AI/ML, QSP, PK/PD)
Cross-disciplinary expertise spanning materials science, biomedical engineering, analytical chemistry, microbiology, and pharmacometrics
Regulatory-ready documentation for medical device, pharmaceutical, and materials submissions
Collaborative, end-to-end R&D support from model creation to experimental interpretation
This integrated approach enables faster development, higher accuracy, reduced costs, and greater confidence in scientific and engineering decisions