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Related Concept Videos

Noncompartmental Analysis: Mean Residence Time01:05

Noncompartmental Analysis: Mean Residence Time

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According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean of a probability density function distribution. It provides valuable insights into drug disposition in the body.
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...
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Noncompartmental Analysis: Mean Transit, Absorption and Dissolution Time01:02

Noncompartmental Analysis: Mean Transit, Absorption and Dissolution Time

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When drugs are administered extravascularly, a comprehensive evaluation through noncompartmental analysis becomes imperative. This analytical approach considers various parameters that play a crucial role in understanding the pharmacokinetics of these drugs.
One of the key parameters is the mean transit time (MTT), which refers to the total duration required for drug molecules to transit through the body. MTT is determined by calculating the ratio of the area under the moment curve to the area...
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Drug Accumulation During Multiple Dosing: Repetitive IV Injections01:21

Drug Accumulation During Multiple Dosing: Repetitive IV Injections

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Calculating drug dosage and accumulation in multiple-dose regimens is crucial for achieving therapeutic efficacy while avoiding toxicity. This involves determining the plasma drug concentrations over time to optimize dosing schedules. The principle of superposition is fundamental in this process, allowing for the prediction of drug concentration in plasma following multiple doses based on single-dose data.The principle of superposition asserts that the plasma concentration-time curves from...
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Dosage Regimens: Partial Pharmacokinetic Parameters01:01

Dosage Regimens: Partial Pharmacokinetic Parameters

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It is not uncommon for complete drug pharmacokinetic profiles to remain elusive in pharmacokinetics. This necessitates certain educated assumptions by pharmacokineticists to determine appropriate dosage regimens without comprehensive pharmacokinetic data from animal or human studies. One prevalent assumption is setting the bioavailability factor, denoted as F, to 1 or 100%. This assumption caters to the scenario where a drug doesn't achieve full systemic absorption, resulting in the patient...
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Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance01:07

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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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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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Updated: Jan 9, 2026

An Intestine/Liver Microphysiological System for Drug Pharmacokinetic and Toxicological Assessment
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Toward Automated Physics-Based Absolute Drug Residence Time Predictions.

Zachary Smith1, Davide Branduardi2, Dmitry Lupyan3

  • 1Schrödinger, New York, 1540 Broadway, 24th Floor, New York, New York 10036, United States.

Journal of Chemical Information and Modeling
|December 9, 2025
PubMed
Summary
This summary is machine-generated.

Calculating drug residence time is crucial for drug discovery. A new computational method combining Random Acceleration Molecular Dynamics and Infrequent Metadynamics accurately predicts drug-target residence times, aiding ligand optimization.

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Area of Science:

  • Computational chemistry and molecular dynamics
  • Drug discovery and medicinal chemistry

Background:

  • Drug residence time (τ) is a critical parameter in ligand optimization, influencing compound profiles beyond binding affinity.
  • Accurate prediction of residence time is essential for efficient small molecule drug discovery programs.

Purpose of the Study:

  • To introduce a novel computational protocol for calculating absolute drug residence times.
  • To provide a method balancing accuracy, throughput, and ease of use for drug discovery.

Main Methods:

  • A two-phase enhanced sampling approach: Random Acceleration Molecular Dynamics (RAMD) for pathway harvesting and Infrequent Metadynamics (iMetaD) for residence time estimation.
  • Protocol applied to 29 drug-target complexes across five diverse targets without manual parameter tuning.

Main Results:

  • The combined RAMD and iMetaD protocol achieved good accuracy in predicting residence times.
  • Quantitative metrics showed strong correlation with experimental values (RMSE of 1.22 and R² of 0.80 in log₁₀(τ)).

Conclusions:

  • This computational scheme offers a robust and accurate method for determining drug residence times.
  • The protocol is suitable for small molecule drug discovery, enhancing ligand optimization strategies.