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Related Concept Videos

Feedback control systems01:26

Feedback control systems

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Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
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Effects of feedback01:24

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Feedback in control systems plays a critical role in shaping various operational parameters, extending beyond simple error reduction to influence stability, bandwidth, gain, impedance, and sensitivity. Understanding these effects requires examining a basic feedback system characterized by defined input, output, error, and feedback signals.
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Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
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Animal organs and organ systems constantly adjust to internal and external changes through a process called homeostasis ("steady state"). Examples of these changes include regulation of the level of glucose or calcium in the blood or internal responses to external temperatures. Homeostasis requires  maintaining an internal dynamic equilibrium:
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Desensitization and Tachyphylaxis01:20

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Tachyphylaxis is described as a rapid decrease in response to a drug after repeated or continuous administration of the same drug dose. It is a phenomenon where the body becomes less responsive to a particular substance or intervention over time, requiring higher doses or stronger interventions to achieve the same effect. It results from adaptive changes in the body's receptors, signaling pathways, or physiological processes that occur in response to prolonged exposure to a stimulus.
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The Two-State Receptor Model01:29

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The two-state receptor model explains a drug's interaction with receptors, such as G protein-coupled receptors and ligand-gated ion channels, to induce or inhibit a biological response. When no natural ligands are present, a receptor exists in an equilibrium of inactive (Ri) and active (Ra) conformations. The inactive form does not produce a response, while the active form generates a basal effect known as constitutive activity.
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A nonlinear feedback model capturing different patterns of tolerance and rebound.

Johan Gabrielsson1, Lambertus A Peletier

  • 1Discovery DMPK, HA232, AstraZeneca R&D Mölndahl, S-43183 Mölndahl, Sweden. Johan.Gabrielsson@AstraZeneca.com

European Journal of Pharmaceutical Sciences : Official Journal of the European Federation for Pharmaceutical Sciences
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Summary

This study analyzes turnover feedback models for characterizing biological responses. The models predict distinct overshoots and rebounds based on production or loss term alterations, aiding drug discovery.

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Area of Science:

  • Pharmacology
  • Systems Biology
  • Mathematical Modeling

Background:

  • Turnover feedback models are crucial for understanding biological system dynamics.
  • Characterizing response onset, intensity, and duration is vital for drug discovery.
  • Existing models offer flexibility but require deeper mechanistic and empirical analysis.

Purpose of the Study:

  • To dissect a class of flexible turnover feedback models.
  • To analyze model behavior mathematically and through simulations.
  • To provide recommendations for experimental design and model building in drug discovery.

Main Methods:

  • Mathematical and analytical dissection of turnover feedback models.
  • Simulations with varied parameter settings and dosing regimens.
  • Analysis of model extensions including transduction and nonlinear phenomena.

Main Results:

  • Demonstrated distinct model behaviors (overshoot, rebound) based on specific perturbations (production/loss term stimulation/inhibition).
  • Anchored model predictions in three distinct experimental datasets.
  • Highlighted intrinsic model behaviors and drew general conclusions applicable to feedback systems.

Conclusions:

  • Turnover feedback models provide a robust framework for understanding biological responses.
  • Model simulations reveal predictable patterns crucial for drug development.
  • The study offers insights into experimental design and model building for optimizing drug discovery efforts.