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Related Concept Videos

Bioequivalence: Overview01:16

Bioequivalence: Overview

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Pharmaceutical equivalents, by definition, are drug products with the same active ingredient in the same quantities, encapsulated in identical dosage forms, and intended for the same administration routes. These pharmaceutical equivalents are deemed bioequivalent if the bioavailability of the active entity in the drug preparations is similar. Moreover, pharmaceutical equivalents demonstrating bioequivalence are also regarded as therapeutically equivalent. This means that when used as directed,...
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This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
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Related Experiment Video

Updated: Aug 3, 2025

Evaluation of Blood Lactate and Plasma Insulin During High-intensity Exercise by Antecubital Vein Catheterization
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Evaluation of Blood Lactate and Plasma Insulin During High-intensity Exercise by Antecubital Vein Catheterization

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Non-Invasive Multiparametric Approach To Determine Sweat-Blood Lactate Bioequivalence.

Genis Rabost-Garcia1,2, Valeria Colmena2, Javier Aguilar-Torán2,3

  • 1Department of Mechanical Engineering (DEM), Universitat Politècnica de Catalunya-BarcelonaTech (UPC), 08222 Terrassa, Spain.

ACS Sensors
|April 8, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to accurately predict blood lactate levels using non-invasive wearable sensors measuring sweat lactate, sweat rate, and heart rate. This innovation offers real-time, continuous monitoring for sports and health applications.

Keywords:
lactate monitoringmachine learningmultiparametricsportsweat analysiswearable sensors

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Area of Science:

  • Biomedical Engineering
  • Sports Science
  • Wearable Technology

Background:

  • Wearable systems for sweat monitoring often lack reliable correlation with blood values.
  • Lactate is a key biomarker in sports and health, but its sweat-blood bioequivalence is complex.
  • Existing methods for lactate monitoring can be invasive or lack continuous real-time data.

Purpose of the Study:

  • To develop a multiparametric methodology for predicting blood lactate from non-invasive wearable sensors.
  • To establish a reliable and accurate method for continuous, real-time lactate monitoring.
  • To overcome the limitations of current sweat-based biomarkers for lactate.

Main Methods:

  • A study involving over 30 volunteers in collaboration with sports institutions.
  • Utilized independent non-invasive sensors to measure sweat lactate, sweat rate, and heart rate.
  • Employed a neural network algorithm to predict blood lactate values using sensor data and subject metadata.

Main Results:

  • The developed methodology accurately predicted blood lactate absolute values.
  • The system achieved a low accumulated error of only 0.3 mM compared to portable blood lactate meters.
  • Demonstrated the feasibility of predicting blood lactate from sweat and physiological data.

Conclusions:

  • The proposed multiparametric approach offers a reliable and accurate method for non-invasive blood lactate monitoring.
  • This integrated platform for sweat monitoring has significant potential for real-time, continuous application in sports and health.
  • The methodology enhances the utility of sweat biomarkers by overcoming bioequivalence challenges.