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Deception is a pervasive aspect of human communication. Empirical studies have shown that most individuals engage in some form of deceit on a daily basis, with approximately 20% of social exchanges involving deceptive elements. Lying follows a developmental trajectory, peaking during adolescence and declining with age, possibly due to the maturation of cognitive control and social accountability.Cognitive and Social Factors in Deception DetectionDespite its prevalence, accurately detecting...
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Updated: Jun 17, 2026

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime
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Blood Never Lies: The PopPK-Based Lie Detector.

Sahira Chaiben1, Peggy Gandia2,3, Béatrice Duly-Bouhanick4

  • 1INTHERES, Université de Toulouse, INRAE, ENVT, Toulouse, France.

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A novel bi-analyte population pharmacokinetic approach using parent drugs and metabolites improves detection of non-adherence in unsupervised oral therapies. This method enhances accuracy over single-analyte models for better patient adherence assessment.

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Area of Science:

  • Pharmacokinetics
  • Drug Metabolism
  • Population Modeling

Background:

  • Accurate drug adherence assessment is crucial for unsupervised oral therapies.
  • Conventional adherence monitoring tools often lack objectivity and miss non-adherence.
  • Population pharmacokinetic (PopPK) modeling offers improved objectivity but may miss hidden non-adherence with single analytes.

Purpose of the Study:

  • To develop and validate a bi-analyte PopPK approach for enhanced detection of drug non-adherence.
  • To utilize both parent drug and metabolite concentrations to reconstruct patient dosing histories.
  • To improve the accuracy of adherence assessment in long-term oral therapies.

Main Methods:

  • Identified spironolactone and canrenone as suitable candidates due to distinct pharmacokinetic profiles.
  • Simulated virtual patients under various adherence scenarios.
  • Employed a modified Metropolis-Hastings algorithm to jointly estimate pharmacokinetic parameters and dosing patterns from simulated concentrations.
  • Derived posterior adherence probability and evaluated diagnostic performance using receiver operating characteristic analysis.

Main Results:

  • The bi-analyte approach demonstrated superior non-adherence detection compared to single-analyte methods, especially for recent missed doses.
  • Trough concentrations proved more effective than peak concentrations for adherence detection, particularly when patients did not overcompensate.
  • The method successfully inferred probabilities of daily tablet intake.

Conclusions:

  • The probabilistic bi-analyte PopPK approach significantly enhances non-adherence detection.
  • This method is adaptable to other drugs with distinct metabolite profiles and low model variability.
  • Improved adherence monitoring can lead to better therapeutic outcomes in long-term oral treatments.