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<p>Cannabis legalization has created regulated markets requiring residual pesticide testing to protect public health. Regulatory programs establish action limits governing product release and enforcement, necessitating accurate quantification in analytically challenging matrices. Compliance is further complicated by the need to quantify dozens of compounds with widely varying physicochemical properties, often requiring multiple assays per product. Validated multiplex methods in representative matrices are therefore critical for defensible quantification at regulatory thresholds. We developed and validated a multiplex liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous quantification of 64 pesticides in cannabis-derived hemp oil, employing external calibration with 58 stable isotope-labeled internal standards (SIL-IS) and 4 surrogate internal standards (IS) across 8.4 units of LogP. Validation followed Clinical &amp; Laboratory Standards Institute (CLSI) guidelines (C62-A, EP05-A3, EP29-A) and Food and Drug Administration (FDA) guidance. All 64 pesticides demonstrated linear calibration (R<sup>2</sup> ≥ 0.995), with accuracy of 80.0–120.0% (mean recovery = 101.9%) and precision of ≤ 15% coefficient of variation (%CV, mean %CV = 2.7%). Analytical measurement ranges extended to 20,000 parts per billion (ppb) for 62 components. Expanded measurement uncertainty ranged from ±2.3% to ±14.6% and remained ≤15% at 100&#xa0;ppb for 57 of 64 pesticides. Systematic benchmarking of surrogate IS suitability across all analyte-IS pairings showed that performance correlated with chromatographic and physicochemical similarity, enabling identification of optimal surrogates and analytes requiring matched SIL-IS. This study illustrates an isotope-dilution approach for multiplexed pesticide quantification with structured uncertainty characterization to support accurate and defensible regulatory determinations at regulatory thresholds for cannabis.</p> Graphical abstract <p></p>

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Enhanced quantification of 64 pesticides in cannabis-derived oil by isotope-dilution LC-MRM-MS at regulatory decision thresholds

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月18日

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  • Raymond T. Suhandynata,
  • Jiaxi Cai,
  • Benjamin J. Spiegel,
  • Thomas D. Marcotte,
  • Igor Grant,
  • Robert L. Fitzgerald,
  • Jeremiah D. Momper

摘要

Cannabis legalization has created regulated markets requiring residual pesticide testing to protect public health. Regulatory programs establish action limits governing product release and enforcement, necessitating accurate quantification in analytically challenging matrices. Compliance is further complicated by the need to quantify dozens of compounds with widely varying physicochemical properties, often requiring multiple assays per product. Validated multiplex methods in representative matrices are therefore critical for defensible quantification at regulatory thresholds. We developed and validated a multiplex liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous quantification of 64 pesticides in cannabis-derived hemp oil, employing external calibration with 58 stable isotope-labeled internal standards (SIL-IS) and 4 surrogate internal standards (IS) across 8.4 units of LogP. Validation followed Clinical & Laboratory Standards Institute (CLSI) guidelines (C62-A, EP05-A3, EP29-A) and Food and Drug Administration (FDA) guidance. All 64 pesticides demonstrated linear calibration (R2 ≥ 0.995), with accuracy of 80.0–120.0% (mean recovery = 101.9%) and precision of ≤ 15% coefficient of variation (%CV, mean %CV = 2.7%). Analytical measurement ranges extended to 20,000 parts per billion (ppb) for 62 components. Expanded measurement uncertainty ranged from ±2.3% to ±14.6% and remained ≤15% at 100 ppb for 57 of 64 pesticides. Systematic benchmarking of surrogate IS suitability across all analyte-IS pairings showed that performance correlated with chromatographic and physicochemical similarity, enabling identification of optimal surrogates and analytes requiring matched SIL-IS. This study illustrates an isotope-dilution approach for multiplexed pesticide quantification with structured uncertainty characterization to support accurate and defensible regulatory determinations at regulatory thresholds for cannabis.

Graphical abstract