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Related Concept Videos

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Drug transporters are critical in drug absorption, distribution, and excretion processes. They should be included in physiological-based pharmacokinetic (PBPK) models, which help predict human drug disposition. However, predicting this is challenging during drug development, especially when liver transport is involved. However, with a realistic representation of body transport processes, an accurate model may be possible.
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Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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Pharmacokinetic Models: Overview01:20

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Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
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Related Experiment Video

Updated: Aug 20, 2025

Combining Fluidic Devices with Microscopy and Flow Cytometry to Study Microbial Transport in Porous Media Across Spatial Scales
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Unravelling microbial efflux through mathematical modelling.

Sara Jabbari1

  • 1School of Mathematics and Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK.

Microbiology (Reading, England)
|November 21, 2022
PubMed
Summary

Mathematical modelling aids understanding of microbial efflux, the process microbes use to expel harmful substances. This approach is key for tackling antimicrobial resistance and advancing synthetic biology.

Keywords:
efflux pumpsinterdisciplinarymathematical modellingmultidisciplinary

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Area of Science:

  • Life Sciences
  • Microbiology
  • Computational Biology

Background:

  • Microbial efflux is a critical process for microbial survival and adaptation.
  • Understanding efflux mechanisms is vital for combating antimicrobial resistance.
  • Efflux plays a role in synthetic biology applications.

Approach:

  • This review examines the application of mathematical modelling in studying microbial efflux.
  • It highlights the interdisciplinary nature of this approach, integrating computational and experimental methods.
  • The review synthesizes current knowledge on how modelling advances efflux research.

Key Points:

  • Mathematical models provide predictive power for microbial efflux dynamics.
  • Modelling has significantly enhanced the understanding of efflux pumps and their role in resistance.
  • Applications extend to designing novel antimicrobial strategies and synthetic biological systems.

Conclusions:

  • Mathematical modelling is an indispensable tool for dissecting complex biological systems like microbial efflux.
  • Further collaborations between modellers and experimentalists are encouraged to accelerate discoveries.
  • This interdisciplinary synergy will drive innovation in both fundamental microbiology and applied synthetic biology.