Recreate healthy human physiology or complex human disorders in the lab
PhysioMimix Organ-on-a-chip models (or microphysiological systems) are comprised of human cells and tissues whose phenotypes and functions reliably mimic those in vivo.
By recreating human physiology in the lab, these models can be used for a myriad of contexts of use to further our understanding of disease mechanisms, uncover potential therapeutic targets, and assist with the safe and efficacious development of potential therapeutics.
Below are examples of the human-relevant purposes for which we have characterized our Organ-on-a-chip models.
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Building better data packages: The role of MPS in modern efficacy, toxicity and ADME workflows
Disease modeling
Studying disease models provides insight into disease cause and progression. They help to identify potential therapeutic approaches and are used to assess drug efficacy. Our models functionally mimic the organ and give a realistic expression of the disease phenotype to ensure more clinically translatable data.
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Safety toxicology
Predictive safety toxicology models that closely mimic in vivo function can more accurately predict drug safety and accelerate drug development by avoiding unexpected adverse effects in human trials.
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ADME
Determining the ADME properties of compounds is essential for lead optimization and candidate selection in early drug discovery. Single- and multi-organ models closely predict human in vivo pharmacokinetics for more informed decision-making.
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Customer adapted applications
Discover how researchers worldwide are leveraging PhysioMimix’s adaptable platform to advance safety toxicology, disease modeling, and ADME studies across diverse organ systems.
Safety Toxicology
Charles River
Genotoxicity
Pharmaron
Gastrointestinal toxicity
Pharmaron
Pulmonary toxicity
Texax A&M
Nephrotoxicity
Disease modeling
University of Sydney
COPD
University of Pittsburgh
Oncology
Imperial college
Hepatitis B
MIT
IBD
NOVO
MASLD/Insulin resistance
Melomanes
CAR T-cell therapy
ADME
Amgen
DDI
Roche
Quantitative drug metabolism