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Related Concept Videos

Clearance Models: Physiological Models01:09

Clearance Models: Physiological Models

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Drug clearance is a critical pharmacokinetic process involving the irreversible removal of drugs from the body through various organs over a specified time period. Physiological models are indispensable in determining organ-specific clearance, defined by the proportion of the drug eliminated per unit of time from the organ's blood volume.
The organ's clearance rate depends on the blood flow to the organ and the extraction ratio (E). The extraction ratio describes the organ's...
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Model Approaches for Pharmacokinetic Data: Physiological Models01:15

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Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
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Small population sizes put a species at extreme risk of extinction due to a lack of variation, and a consequent decrease in adaptability. This weakens the chances of survival under pressures such as climate change, competition from other species, or new diseases. Large populations are more likely to survive pressures such as these, as such populations are more likely to harbor individuals that have genetic variants that are adaptive under new stresses. Small populations are much less...
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A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.
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Population Growth00:57

Population Growth

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Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.
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A Robust Simulator for Physiologically Structured Population Models.

Michiel Van Dyck, Xavier Woot de Trixhe, An Vermeulen

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |July 12, 2018
    PubMed
    Summary

    A new framework enables efficient simulation of physiologically structured population (PSP) models on high-performance computing (HPC) infrastructure. This approach significantly accelerates the modeling of cell populations and organ interactions.

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    Area of Science:

    • Computational Biology
    • Systems Biology
    • Biophysics

    Background:

    • Physiologically Structured Population (PSP) models are crucial for understanding biological systems.
    • Simulating large-scale PSP models on existing infrastructure is computationally intensive.
    • Efficient simulation frameworks are needed to advance organ-level and whole-body modeling.

    Purpose of the Study:

    • To develop a novel framework for simulating PSP models on high-performance computing (HPC) infrastructure.
    • To significantly reduce simulation time for large-scale cellular and organ interactions.
    • To validate the accuracy and efficiency of the developed simulation framework.

    Main Methods:

    • Developed a PSP modeling framework optimized for HPC clusters.
    • Implemented parallel processing exploiting cellular redundancy for speed-up.
    • Utilized an unconditionally stable partial differential equation solver for large time steps.
    • Mathematically derived the simulator for maximal stability.

    Main Results:

    • Achieved multiple orders of magnitude reduction in simulation time.
    • Enabled efficient simulation of billions of cells based on a single-cell model.
    • Demonstrated fast simulation of interactions between organs and other body parts.
    • Validated simulation results, measuring speed and accuracy.

    Conclusions:

    • The developed PSP simulation framework offers unprecedented efficiency for large-scale biological modeling.
    • HPC infrastructure combined with optimized algorithms drastically accelerates PSP simulations.
    • This framework facilitates advanced research in organ-level and whole-body physiological modeling.