Related Experiment Video
Updated: Jun 29, 2025
08:31
Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
Published on: December 1, 2020
5.0K
Pharmacokinetics Profiler (PhaKinPro): Model Development, Validation, and Implementation as a Web Tool for Triaging
Marielle Rath1, James Wellnitz1, Holli-Joi Martin1
1Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina 27599, United States.
Journal of Medicinal Chemistry
|April 3, 2024
Summary
Computational models predict drug properties to improve drug discovery. Developed quantitative structure-activity relationship (QSAR) models accurately assess drug candidates, aiding in the selection of promising compounds.
Area of Science:
- Computational chemistry and cheminformatics
- Drug discovery and development
- Pharmacokinetics and drug metabolism
Background:
- Accurate prediction of pharmacokinetic properties is essential for efficient drug candidate prioritization.
- High-throughput screening generates numerous drug hits requiring rapid assessment.
- Quantitative structure-activity relationship (QSAR) models offer a computational approach to predict drug behavior.
Purpose of the Study:
- To develop and validate robust binary QSAR models for predicting pharmacokinetic properties.
- To create a comprehensive database of drug compound pharmacokinetic data.
- To make these predictive models accessible for broader use in drug discovery.
Main Methods:
- Collected, curated, and integrated a database of over 10,000 unique compounds with 12 pharmacokinetic endpoints.
- Developed and validated binary quantitative structure-activity relationship (QSAR) models using the curated dataset.
- Applied the trained QSAR models to predict pharmacokinetic properties for compounds in the NCATS Inxight Drugs and DrugBank databases.
Main Results:
- All developed QSAR models demonstrated a correct classification rate above 0.60.
- Positive predictive values for the models exceeded 0.50, indicating reliable predictions.
- Successful prediction of pharmacokinetic properties for extensive drug compound libraries.
Conclusions:
- The developed QSAR models provide a valuable tool for deprioritizing drug candidates with unfavorable pharmacokinetic profiles.
- The integrated models and web portal (PhaKinPro) enhance accessibility for researchers in drug discovery.
- These computational tools can significantly accelerate the early stages of the drug development pipeline.
Related Concept Videos
01:12Analysis of Population Pharmacokinetic Data
254
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
254
01:20Pharmacokinetic Models: Overview
672
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.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
672
01:10Pharmacokinetics: Overview
6.3K
Pharmacokinetics is a scientific discipline that focuses on the journey of a drug within the body, encompassing four key stages: absorption, distribution, metabolism, and elimination. The first stage, absorption, involves the drug's transfer into the bloodstream. Several factors dictate the extent and speed of this process. For example, the liver often metabolizes oral drugs before they reach systemic circulation, leading to only partial absorption. In contrast, intravenous (IV)...
6.3K
01:22Nonlinear Pharmacokinetics: Bioavailability and Protein-Drug Binding
170
When a drug follows nonlinear pharmacokinetics, its bioavailability, the amount of the drug that reaches the systemic circulation, can change with different doses. This is due to the presence of a saturable pathway. The pathway becomes saturated as the drug concentration increases, decreasing the absorption rate. Consequently, the drug's bioavailability may be lower than expected at higher doses.
To quantify the extent of bioavailability, pharmacologists often use a parameter called .
To quantify the extent of bioavailability, pharmacologists often use a parameter called .
170
00:59Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
62
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
62
01:14Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
123
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
123