Cross-reactivity studies and predictive modeling of "Bath Salts" and other amphetamine-type stimulants with amphetamine screening immunoassays

Clin Toxicol (Phila). 2013 Feb;51(2):83-91. doi: 10.3109/15563650.2013.768344.

Abstract

Introduction: The increasing abuse of amphetamine-like compounds presents a challenge for clinicians and clinical laboratories. Although these compounds may be identified by mass spectrometry-based assays, most clinical laboratories use amphetamine immunoassays that have unknown cross-reactivity with novel amphetamine-like drugs. To date, there has been a little systematic study of amphetamine immunoassay cross-reactivity with structurally diverse amphetamine-like drugs or of computational tools to predict cross-reactivity.

Methods: Cross-reactivities of 42 amphetamines and amphetamine-like drugs with three amphetamines screening immunoassays (AxSYM(®) Amphetamine/Methamphetamine II, CEDIA(®) amphetamine/Ecstasy, and EMIT(®) II Plus Amphetamines) were determined. Two- and three-dimensional molecular similarity and modeling approaches were evaluated for the ability to predict cross-reactivity using receiver-operator characteristic curve analysis.

Results: Overall, 34%-46% of the drugs tested positive on the immunoassay screens using a concentration of 20,000 ng/mL. The three immunoassays showed differential detection of the various classes of amphetamine-like drugs. Only the CEDIA assay detected piperazines well, while only the EMIT assay cross-reacted with the 2C class. All three immunoassays detected 4-substituted amphetamines. For the AxSYM and EMIT assays, two-dimensional molecular similarity methods that combined similarity to amphetamine/methamphetamine and 3,4-methylenedioxymethampetamine most accurately predicted cross-reactivity. For the CEDIA assay, three-dimensional pharmacophore methods performed best in predicting cross-reactivity. Using the best performing models, cross-reactivities of an additional 261 amphetamine-like compounds were predicted.

Conclusions: Existing amphetamines immunoassays unevenly detect amphetamine-like drugs, particularly in the 2C, piperazine, and β-keto classes. Computational similarity methods perform well in predicting cross-reactivity and can help prioritize testing of additional compounds in the future.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Amphetamines / analysis*
  • Amphetamines / immunology
  • Antibody Specificity
  • Area Under Curve
  • Central Nervous System Stimulants / analysis*
  • Central Nervous System Stimulants / immunology
  • Cross Reactions
  • Crystallography, X-Ray
  • Illicit Drugs
  • Immunoassay / methods*
  • Models, Chemical
  • Models, Molecular
  • Molecular Conformation
  • Predictive Value of Tests
  • ROC Curve
  • Substance Abuse Detection

Substances

  • Amphetamines
  • Central Nervous System Stimulants
  • Illicit Drugs