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Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

232
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...
232
The Carbon Cycle01:14

The Carbon Cycle

43.1K
Carbon is the basis of all organic matter on Earth, and is recycled through the ecosystem in two primary processes: one in which carbon is exchanged among living organisms, and one in which carbon is cycled over long periods of time through fossilized organic remains, weathering of rocks, and volcanic activity. Human activities, including increased agricultural practices and the burning of fossil fuels, has greatly affected the balance of the natural carbon cycle.
43.1K
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

1.8K
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...
1.8K
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

301
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
301
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

221
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...
221
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

218
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
218

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Related Experiment Video

Updated: Jan 6, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
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In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox

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A Large Language Model-based Framework to Retrieve Life Cycle Inventory and Environmental Impact Data from Scientific

Avan Kumar1, Farshid Nazemi2, Hariprasad Kodamana3,4,5

  • 1School of Sustainability, Arizona State University, Tempe, Arizona 85288, United States.

Environmental Science & Technology
|October 16, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces Sustain-LLaMA, a retrained large language model (LLM) to automate life cycle inventory (LCI) data retrieval for environmental impact assessments. This tool enhances accuracy and efficiency in sustainability research.

Keywords:
environmental impact datalarge language modellife cycle inventory dataliterature miningmethanol synthesisplastic packaging EoL treatment

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Area of Science:

  • Environmental Science
  • Computer Science
  • Chemical Engineering

Background:

  • Life Cycle Assessment (LCA) relies on accurate Life Cycle Inventory (LCI) data.
  • Obtaining LCI data is resource-intensive, involving literature reviews and costly databases.
  • This hinders transparent and efficient environmental impact analysis.

Purpose of the Study:

  • To develop a systematic framework using a retrained large language model (LLM) to automate LCI data retrieval.
  • To assist LCA practitioners in accessing LCI data and environmental impact information from scientific literature.
  • To improve the scalability and precision of environmental impact assessments.

Main Methods:

  • A three-stage framework: document classification, LLaMA-2-7B pretraining, and Q&A model fine-tuning.
  • The resulting LLM, Sustain-LLaMA, was applied to methanol production and plastic packaging end-of-life treatment.
  • Retrieval Augmented Generation (RAG) was employed for data extraction.

Main Results:

  • High accuracies for classification models (0.850 methanol, 0.952 plastic packaging).
  • Q&A models achieved competitive F1 scores (0.823 methanol, 0.855 plastic).
  • Sustain-LLaMA demonstrated comparable or superior performance to existing models and databases.

Conclusions:

  • The proposed framework effectively automates LCI data retrieval, enhancing LCA efficiency.
  • Sustain-LLaMA offers a scalable and precise tool for sustainability research.
  • This approach supports the chemical and plastic industries in their pursuit of sustainability.