Case Studies
Real-world impact through advanced metabolic profiling
Our analytical workflows transform complex samples into actionable insights. From optimizing drug delivery to mapping microbiome-informed treatments, we partner with researchers to solve critical challenges in biotechnology and medicine.
Research question: How does the choice of microfluidic device material (PDMS vs COC) affect the sorption and washout behavior of small lipophilic pharmaceutical compounds?
Sample type: Solutions of pharmaceutically relevant small molecules incubated in microfluidic organ-on-chip devices
Methods: Custom method development
Key findings:
Lipophilic compounds exhibited significantly higher sorption to PDMS compared to COC, reducing their detectable concentrations after incubation.
COC allowed faster desorption and washout than PDMS, indicating less distortion of pharmacokinetic profiles in chip devices.
Molecular properties like lipophilicity (logP) strongly influenced sorption behavior.
Research question: What are the molecular mechanisms behind the cytotoxic effects of physically crosslinked hyaluronic acid/ε-poly-l-lysine hydrogels on cells, particularly with respect to metabolism?
Sample type: cells
Methods: TARGET, LIPID, Isotope tracing
Key findings:
HA/PLL hydrogel exposure significantly disturbs glutamate metabolism, indicating metabolic stress.
Metabolic disruptions correlate with cytoskeletal collapse and reduced cell viability, underscoring biocompatibility challenges for this hydrogel formulation.
The study highlights the importance of metabolite-level analysis in material biocompatibility assessments.
Research question: Can gut microbiome-derived metabolites in purine and amino acid metabolism predict the efficacy of metformin therapy in newly diagnosed type 2 diabetes (T2D) patients?
Sample type: Feces
Key findings:
Specific gut microbiome encoded purine and amino acid metabolic pathways strongly associate with differential metformin response.
Certain metabolite signatures may serve as early predictive biomarkers for optimal therapeutic outcomes with metformin.
This finding supports microbiome-informed stratification in T2D treatment.
Research question: How is systemic amino acid metabolism altered in patients hospitalized with severe COVID-19, and what are the implications for disease severity?
Sample type: Plasma
Methods: AMINO
Key findings:
Severe COVID-19 patients exhibited distinct alterations in amino acid metabolism compared with healthy or less severe cases.
The metabolic shifts include disruptions in tryptophan pathways and other amino acid networks linked to immune response.
These metabolic signatures correlated with clinical severity markers, pointing toward potential diagnostic and prognostic utilities.
Research question: Can gut microbiome-derived metabolites in purine and amino acid metabolism predict the efficacy of metformin therapy in newly diagnosed type 2 diabetes (T2D) patients?
Sample type: Feces
Key findings:
Specific gut microbiome encoded purine and amino acid metabolic pathways strongly associate with differential metformin response.
Certain metabolite signatures may serve as early predictive biomarkers for optimal therapeutic outcomes with metformin.
This finding supports microbiome-informed stratification in T2D treatment.
Research question: How is systemic amino acid metabolism altered in patients hospitalized with severe COVID-19, and what are the implications for disease severity?
Sample type: Plasma
Methods: AMINO
Key findings:
Severe COVID-19 patients exhibited distinct alterations in amino acid metabolism compared with healthy or less severe cases.
The metabolic shifts include disruptions in tryptophan pathways and other amino acid networks linked to immune response.
These metabolic signatures correlated with clinical severity markers, pointing toward potential diagnostic and prognostic utilities.
Research question: How does the choice of microfluidic device material (PDMS vs COC) affect the sorption and washout behavior of small lipophilic pharmaceutical compounds?
Sample type: Solutions of pharmaceutically relevant small molecules incubated in microfluidic organ-on-chip devices
Methods: Custom method development
Key findings:
Lipophilic compounds exhibited significantly higher sorption to PDMS compared to COC, reducing their detectable concentrations after incubation.
COC allowed faster desorption and washout than PDMS, indicating less distortion of pharmacokinetic profiles in chip devices.
Molecular properties like lipophilicity (logP) strongly influenced sorption behavior.
Research question: What are the molecular mechanisms behind the cytotoxic effects of physically crosslinked hyaluronic acid/ε-poly-l-lysine hydrogels on cells, particularly with respect to metabolism?
Sample type: cells
Methods: TARGET, LIPID, Isotope tracing
Key findings:
HA/PLL hydrogel exposure significantly disturbs glutamate metabolism, indicating metabolic stress.
Metabolic disruptions correlate with cytoskeletal collapse and reduced cell viability, underscoring biocompatibility challenges for this hydrogel formulation.
The study highlights the importance of metabolite-level analysis in material biocompatibility assessments.