1
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Kriikku P, Kalso E, Ojanperä I. Post-mortem oxycodone blood concentrations of hospitalized cancer and surgery patients compared with fatal poisonings. Int J Legal Med 2022; 136:1577-1583. [PMID: 36068331 PMCID: PMC9576662 DOI: 10.1007/s00414-022-02890-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 08/31/2022] [Indexed: 11/27/2022]
Abstract
Oxycodone is a strong opioid drug commonly used to treat acute, cancer, and chronic non-malignant pain. In this study, all oxycodone-related medico-legal cases where death had occurred in a hospital or nursing home in Finland were investigated to determine the range of post-mortem (PM) oxycodone blood concentrations in a therapeutic setting. All toxicology cases in which oxycodone was detected in PM femoral blood during the 4-year period of 2016–2019 in Finland were retrieved from the national PM toxicology database. In this material, the 365 deceased hospital patient cases that met the study inclusion criteria were divided into four groups according to the cause and manner of death. The reference group of 121 fatal oxycodone poisoning cases comprised two groups: those with verified associated drug abuse and those without drug abuse. The median oxycodone concentration in PM blood was significantly higher in cancer patients (0.10 mg/L) than in patients with recent surgery (0.07 mg/L) or other disease (0.06 mg/L) (p < 0.05). In addition, the median oxycodone concentration was significantly lower in all hospital patient groups than in the poisoning groups, the latter displaying 0.38 mg/L (abuse) and 0.64 mg/L (no abuse) (p < 0.001). This study shows that half of the subjects in the cancer patient group had PM blood oxycodone concentrations above the typical clinical therapeutic plasma concentration range (0.005–0.10 mg/L). Appropriate medication of hospitalized surgery and cancer patients can result in concentrations of up to 0.2 and 0.6 mg/L, respectively, while higher concentrations are exceptional.
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Affiliation(s)
- Pirkko Kriikku
- Forensic Toxicology Unit, Finnish Institute for Health and Welfare (THL), Helsinki, Finland.,Department of Forensic Medicine, University of Helsinki, Helsinki, Finland
| | - Eija Kalso
- Department of Anaesthesiology, Intensive Care and Pain Medicine, Helsinki University Hospital, Helsinki, Finland.,Department of Pharmacology and SleepWell Research Programme, University of Helsinki, Helsinki, Finland
| | - Ilkka Ojanperä
- Forensic Toxicology Unit, Finnish Institute for Health and Welfare (THL), Helsinki, Finland. .,Department of Forensic Medicine, University of Helsinki, Helsinki, Finland.
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2
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Coulter C, Garnier M, Moore C. Rapid Extraction and Qualitative Screening of 30 Drugs in Oral Fluid at Concentrations Recommended for the Investigation of DUID Cases. J Anal Toxicol 2022; 46:899-904. [PMID: 35640884 DOI: 10.1093/jat/bkac031] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/04/2022] [Accepted: 05/30/2022] [Indexed: 11/12/2022] Open
Abstract
A rapid, simple extraction method followed by qualitative screening using liquid chromatography-tandem mass spectrometry (LC-MS-MS) for drugs in oral fluid is presented. The decision points were selected to be at, or lower, than those recommended as Tier I compounds by the National Safety Council's Alcohol, Drugs, and Impairment Division for toxicological investigation of driving under the influence of drugs cases (DUID) and were also at, or lower, than those recommended by Substance Abuse and Mental Health Service Administration (SAMHSA) and the Department of Transportation (DOT) for Federal workplace drug testing programs. The method included 30 drugs: delta-9-tetrahydrocannabinol (THC), amphetamine, methamphetamine, 3,4-methylenedioxymethamphetamine (MDMA), 3,4-methylenedioxyamphetamine (MDA), cocaine, benzoylecgonine, carisoprodol, meprobamate, zolpidem, alprazolam, clonazepam, 7-aminoclonazepam, diazepam, nordiazepam, lorazepam, oxazepam, temazepam, codeine, morphine, 6-acetylmorphine, buprenorphine, fentanyl, hydrocodone, hydromorphone, oxycodone, oxymorphone, methadone, tramadol, and phencyclidine. Phencyclidine was included because it is in the Federal workplace program even though it is considered a Tier II drug for DUID cases. A liquid-liquid extraction method using isopropanol, hexane, and ethyl acetate to extract drugs from the oral fluid-buffer mix collected in a Quantisal™ device, followed by LC-MS-MS screening was developed and validated according to ANSI/ASB 2019 Standard Practices for Method Validation in Forensic Toxicology. Interference studies, limit of detection, precision at the decision point, ionization suppression/enhancement and processed sample stability were determined for each drug. The method was successfully applied to proficiency specimens and routine samples received into the laboratory.
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Affiliation(s)
- Cynthia Coulter
- 9-Delta Analytical LLC, 4365 E. Lowell Street, Suite E, Ontario, CA 91761, USA
| | - Margaux Garnier
- 9-Delta Analytical LLC, 4365 E. Lowell Street, Suite E, Ontario, CA 91761, USA
| | - Christine Moore
- 9-Delta Analytical LLC, 4365 E. Lowell Street, Suite E, Ontario, CA 91761, USA
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3
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Ji B, Xue Y, Xu Y, Liu S, Gough AH, Xie XQ, Wang J. Drug-Drug Interaction Between Oxycodone and Diazepam by a Combined in Silico Pharmacokinetic and Pharmacodynamic Modeling Approach. ACS Chem Neurosci 2021; 12:1777-1790. [PMID: 33950681 PMCID: PMC8374491 DOI: 10.1021/acschemneuro.0c00810] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Opioids and benzodiazepines have complex drug-drug interactions (DDIs), which serve as an important source of adverse drug effects. In this work, we predicted the DDI between oxycodone (OXY) and diazepam (DZP) in the human body by applying in silico pharmacokinetic (PK) and pharmacodynamic (PD) modeling and simulation. First, we studied the PK interaction between OXY and DZP with a physiologically based pharmacokinetic (PBPK) model. Second, we applied molecular modeling techniques including molecular docking, molecular dynamics (MD) simulation, and the molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) free energy method to predict the PD-DDI between these two drugs. The PK interaction between OXY and DZP predicted by the PBPK model was not obvious. No significant interaction was observed between the two drugs at normal doses, though very high doses of DZP demonstrated a non-negligible inhibitory effect on OXY metabolism. On the contrary, the molecular modeling study shows that DZP has potential to compete with OXY at the same binding pocket of the active μ-opioid receptor (MOR) and κ-opioid receptor (KOR). MD simulation and MM-PBSA calculation results demonstrated that there is likely a synergetic effect between OXY and DZP binding to opioid receptors, as OXY is likely to target the active MOR while DZP selectively binds to the active KOR. Thus, pharmacokinetics contributes slightly to the DDI between OXY and DZP although an overdose of DZP has been brought to attention. Pharmacodynamics is likely to play a more important role than pharmacokinetics in revealing the mechanism of DDI between OXY and DZP.
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Affiliation(s)
- Beihong Ji
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
| | - Ying Xue
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA.,Department of Pharmacy and Therapeutics, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261
| | - Yuanyuan Xu
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
| | - Shuhan Liu
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
| | - Albert H Gough
- Computational and Systems Biology, The University of Pittsburgh, Drug Discovery Institute, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, Pennsylvania, 15260, USA
| | - Xiang Qun Xie
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA.,To whom correspondence should be addressed: Xiang-Qun Xie: Corresponding author, , School of Pharmacy, University of Pittsburgh; Junmei Wang: Corresponding author, , School of Pharmacy, University of Pittsburgh
| | - Junmei Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA.,To whom correspondence should be addressed: Xiang-Qun Xie: Corresponding author, , School of Pharmacy, University of Pittsburgh; Junmei Wang: Corresponding author, , School of Pharmacy, University of Pittsburgh
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4
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Minhas RS, Rudd DA, Al Hmoud HZ, Guinan TM, Kirkbride KP, Voelcker NH. Rapid Detection of Anabolic and Narcotic Doping Agents in Saliva and Urine By Means of Nanostructured Silicon SALDI Mass Spectrometry. ACS APPLIED MATERIALS & INTERFACES 2020; 12:31195-31204. [PMID: 32551485 DOI: 10.1021/acsami.0c07849] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Novel doping agents and doping strategies are continually entering the market, placing a burden on analytical methods to detect, adapt, and respond to subtle changes in the composition of biological samples. Therefore, there is a growing interest in rapid, adaptable, and ideally confirmatory analytical methods for the fight against doping. Nanostructured silicon (nano-Si)-based surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS) can effectively address this need, allowing fast and sensitive detection of prohibited compounds used in sport doping. Here, we demonstrate the detection of growth hormone peptides, anabolic-androgenic steroids, and narcotics at low concentrations directly from biological matrices. Molecular confirmation was performed using the fragmentation data of the structures, obtained with the tandem mass spectrometry capabilities of the SALDI instrument. The obtained data were in excellent agreement with those obtained using leading triple quadrupole liquid chromatography-mass spectrometry instruments. Furthermore, nano-Si SALDI-MS has the capacity for high-throughput analysis of hundreds of biological samples, providing opportunities for real-time MS analysis at sporting events.
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Affiliation(s)
- Rajpreet Singh Minhas
- Drug Delivery, Disposition and Dynamics, Monash University, Parkville, Victoria 3052, Australia
- Melbourne Centre for Nanofabrication, Victorian Node of the Australian National Fabrication Facility, Clayton, Victoria 3168, Australia
- Commonwealth Scientific and Industrial Research Organisation (CSIRO), Clayton, Victoria 3168, Australia
| | - David A Rudd
- Drug Delivery, Disposition and Dynamics, Monash University, Parkville, Victoria 3052, Australia
- Melbourne Centre for Nanofabrication, Victorian Node of the Australian National Fabrication Facility, Clayton, Victoria 3168, Australia
| | - Hashim Z Al Hmoud
- Drug Delivery, Disposition and Dynamics, Monash University, Parkville, Victoria 3052, Australia
- Melbourne Centre for Nanofabrication, Victorian Node of the Australian National Fabrication Facility, Clayton, Victoria 3168, Australia
| | - Taryn M Guinan
- Drug Delivery, Disposition and Dynamics, Monash University, Parkville, Victoria 3052, Australia
- Melbourne Centre for Nanofabrication, Victorian Node of the Australian National Fabrication Facility, Clayton, Victoria 3168, Australia
- Leica Microsystems, Mount Waverly, Victoria 3149, Australia
| | - K Paul Kirkbride
- School of Chemical and Physical Sciences, Flinders University, Bedford Park, Adelaide, South Australia 5001, Australia
| | - Nicolas H Voelcker
- Drug Delivery, Disposition and Dynamics, Monash University, Parkville, Victoria 3052, Australia
- Melbourne Centre for Nanofabrication, Victorian Node of the Australian National Fabrication Facility, Clayton, Victoria 3168, Australia
- Commonwealth Scientific and Industrial Research Organisation (CSIRO), Clayton, Victoria 3168, Australia
- Department of Materials Science and Engineering, Monash University, Clayton, Victoria 3800, Australia
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5
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Physiologically Based Pharmacokinetic Modeling of Oxycodone in Children to Support Pediatric Dosing Optimization. Pharm Res 2019; 36:171. [DOI: 10.1007/s11095-019-2708-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Accepted: 09/24/2019] [Indexed: 12/14/2022]
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6
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Desrosiers NA, Huestis MA. Oral Fluid Drug Testing: Analytical Approaches, Issues and Interpretation of Results. J Anal Toxicol 2019; 43:415-443. [DOI: 10.1093/jat/bkz048] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 05/12/2019] [Accepted: 05/23/2019] [Indexed: 12/19/2022] Open
Abstract
AbstractWith advances in analytical technology and new research informing result interpretation, oral fluid (OF) testing has gained acceptance over the past decades as an alternative biological matrix for detecting drugs in forensic and clinical settings. OF testing offers simple, rapid, non-invasive, observed specimen collection. This article offers a review of the scientific literature covering analytical methods and interpretation published over the past two decades for amphetamines, cannabis, cocaine, opioids, and benzodiazepines. Several analytical methods have been published for individual drug classes and, increasingly, for multiple drug classes. The method of OF collection can have a significant impact on the resultant drug concentration. Drug concentrations for amphetamines, cannabis, cocaine, opioids, and benzodiazepines are reviewed in the context of the dosing condition and the collection method. Time of last detection is evaluated against several agencies' cutoffs, including the proposed Substance Abuse and Mental Health Services Administration, European Workplace Drug Testing Society and Driving Under the Influence of Drugs, Alcohol and Medicines cutoffs. A significant correlation was frequently observed between matrices (i.e., between OF and plasma or blood concentrations); however, high intra-subject and inter-subject variability precludes prediction of blood concentrations from OF concentrations. This article will assist individuals in understanding the relative merits and limitations of various methods of OF collection, analysis and interpretation.
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Affiliation(s)
| | - Marilyn A Huestis
- Lambert Center for the Study of Medicinal Cannabis and Hemp, Institute of Emerging Health Professions, Thomas Jefferson University, Philadelphia, PA, USA
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7
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Lee D. Oral Fluid Drug Testing in Pain Management Practice: Factors to Consider Before Choosing the Alternative Biological Matrix. J Appl Lab Med 2017; 2:598-609. [DOI: 10.1373/jalm.2017.023457] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2017] [Accepted: 10/03/2017] [Indexed: 11/06/2022]
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8
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Shaparin N, Mehta N, Kunkel F, Stripp R, Borg D, Kolb E. A Novel Chronic Opioid Monitoring Tool to Assess Prescription Drug Steady State Levels in Oral Fluid. PAIN MEDICINE 2017; 18:2162-2169. [PMID: 28339737 PMCID: PMC5914322 DOI: 10.1093/pm/pnw335] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Objective Interpretation limitations of urine drug testing and the invasiveness of blood toxicology have motivated the desire for the development of simpler methods to assess biologically active drug levels on an individualized patient basis. Oral fluid is a matrix well-suited for the challenge because collections are based on simple noninvasive procedures and drug concentrations better correlate to blood drug levels as oral fluid is a filtrate of the blood. Well-established pharmacokinetic models were utilized to generate oral fluid steady state concentration ranges to assess the interpretive value of the alternative matrix to monitor steady state plasma oxycodone levels. Methods Paired oral fluid and plasma samples were collected from patients chronically prescribed oxycodone and quantitatively analyzed by liquid chromatography tandem mass spectrometry. Steady state plasma concentration ranges were calculated for each donor and converted to an equivalent range in oral fluid. Measured plasma and oral fluid oxycodone concentrations were compared with respective matrix-matched steady state ranges, using each plasma steady state classification as the control. Results A high degree of correlation was observed between matrices when classifying donors according to expected steady state oxycodone concentration. Agreement between plasma and oral fluid steady state classifications was observed in 75.6% of paired samples. This study supports novel application of basic pharmacokinetic knowledge to the pain management industry, simplifying and improving individualized drug monitoring and risk assessment through the use of oral fluid drug testing. Many benefits of established therapeutic drug monitoring in plasma can be realized in oral fluid for patients chronically prescribed oxycodone at steady state.
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Affiliation(s)
| | - Neel Mehta
- Montefiore Medical Center, Bronx, NY, USA
| | - Frank Kunkel
- Weill-Cornell Pain Medicine Center and New York Presbyterian Hospital, New York, NY, USA
| | | | - Damon Borg
- Accessible Recovery Services, Pittsburgh, PA, USA
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9
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Kwong TC, Magnani B, Moore C. Urine and oral fluid drug testing in support of pain management. Crit Rev Clin Lab Sci 2017; 54:433-445. [PMID: 28990451 DOI: 10.1080/10408363.2017.1385053] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
In recent years, the abuse of opioid drugs has resulted in greater prevalence of addiction, overdose, and deaths attributable to opioid abuse. The epidemic of opioid abuse has prompted professional and government agencies to issue practice guidelines for prescribing opioids to manage chronic pain. An important tool available to providers is the drug test for use in the initial assessment of patients for possible opioid therapy, subsequent monitoring of compliance, and documentation of suspected aberrant drug behaviors. This review discusses the issues that most affect the clinical utility of drug testing in chronic pain management with opioid therapy. It focuses on the two most commonly used specimen matrices in drug testing: urine and oral fluid. The advantages and disadvantages of urine and oral fluid in the entire testing process, from specimen collection and analytical methodologies to result interpretation are reviewed. The analytical sensitivity and specificity limitations of immunoassays used for testing are examined in detail to draw attention to how these shortcomings can affect result interpretation and influence clinical decision-making in pain management. The need for specific identification and quantitative measurement of the drugs and metabolites present to investigate suspected aberrant drug behavior or unexpected positive results is analyzed. Also presented are recent developments in optimization of test menus and testing strategies, such as the modification of the standard screen and reflexed-confirmation testing model by eliminating some of the initial immunoassay-based tests and proceeding directly to definitive testing by mass spectrometry assays.
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Affiliation(s)
- Tai C Kwong
- a Department of Pathology and Laboratory Medicine , University of Rochester Medical Center , Rochester , NY , USA
| | - Barbarajean Magnani
- b Department of Pathology and Laboratory Medicine , Tufts Medical Center , Boston , MA , USA
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10
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Cummings OT, Morris AA, Enders JR, McIntire GL. Normalizing Oral Fluid Hydrocodone Data Using Calculated Blood Volume. J Anal Toxicol 2016; 40:486-91. [DOI: 10.1093/jat/bkw057] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
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11
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Heiskanen T, Langel K, Gunnar T, Lillsunde P, Kalso EA. Opioid Concentrations in Oral Fluid and Plasma in Cancer Patients With Pain. J Pain Symptom Manage 2015; 50:524-32. [PMID: 25242020 DOI: 10.1016/j.jpainsymman.2014.09.004] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2014] [Revised: 08/30/2014] [Accepted: 09/12/2014] [Indexed: 10/24/2022]
Abstract
CONTEXT Measuring opioid concentrations in pain treatment is warranted in situations where optimal opioid analgesia is difficult to reach. OBJECTIVES To assess the usefulness of oral fluid (OFL) as an alternative to plasma in opioid concentration monitoring in cancer patients on chronic opioid therapy. METHODS We collected OFL and plasma samples from 64 cancer patients on controlled-release (CR) oral morphine, CR oral oxycodone, or transdermal (TD) fentanyl for pain. Samples were obtained on up to five separate days. RESULTS A total of 213 OFL and plasma samples were evaluable. All patients had detectable amounts of the CR or TD opioid in both plasma and OFL samples. The plasma concentrations of oxycodone and fentanyl (determination coefficient R(2) = 0.628 and 0.700, respectively), but not morphine (R(2) = 0.292), were moderately well correlated to the daily opioid doses. In contrast to morphine and fentanyl (mean OFL/plasma ratio 2.0 and 3.0, respectively), the OFL oxycodone concentrations were significantly higher than the respective plasma concentrations (mean OFL/plasma ratio 14.9). An active transporter could explain the much higher OFL vs. plasma concentrations of oxycodone compared with morphine and fentanyl. CONCLUSION OFL analysis is well suited for detecting the studied opioids. For morphine and fentanyl, an approximation of the plasma opioid concentrations is obtainable, whereas for oxycodone, the OFL/plasma concentration relationship is too variable for reliable approximation results.
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Affiliation(s)
- Tarja Heiskanen
- Pain Clinic, Department of Anesthesiology and Intensive Care Medicine, Helsinki University Central Hospital, Helsinki, Finland.
| | - Kaarina Langel
- Alcohol and Drug Analytics Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Teemu Gunnar
- Alcohol and Drug Analytics Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Pirjo Lillsunde
- Injury Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Eija A Kalso
- Pain Clinic, Department of Anesthesiology and Intensive Care Medicine, Helsinki University Central Hospital, Helsinki, Finland; Institute of Clinical Medicine, University of Helsinki, Helsinki, Finland
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12
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Cone EJ, DePriest AZ, Heltsley R, Black DL, Mitchell JM, LoDico C, Flegel R. Prescription Opioids. IV: Disposition of Hydrocodone in Oral Fluid and Blood Following Single-Dose Administration. J Anal Toxicol 2015; 39:510-8. [PMID: 25962610 DOI: 10.1093/jat/bkv050] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The Substance Abuse and Mental Health Services Administration (SAMHSA) is currently evaluating hydrocodone (HC) for inclusion in the Mandatory Guidelines for Federal Workplace Drug Testing Programs. This study evaluated the time course of HC, norhydrocodone (NHC), dihydrocodeine (DHC) and hydromorphone (HM) in paired oral fluid and whole blood specimens by liquid chromatography-tandem mass spectrometry (limit of quantitation = 1 ng/mL of oral fluid, 5 ng/mL of blood) over a 52-h period. A single dose of HC bitartrate, 20 mg, was administered to 12 subjects. Analyte prevalence was as follows: oral fluid, HC > NHC > DHC; and blood, HC > NHC. HM was not detected in any specimen. HC was frequently detected within 15 min in oral fluid and 30 min in blood. Mean oral fluid to blood (OF : BL) ratios and correlations were 3.2 for HC (r = 0.73) and 0.7 for NHC (r = 0.42). The period of detection for oral fluid exceeded blood at all evaluated thresholds. At a 1-ng/mL threshold for oral fluid, mean detection time was 30 h for HC and 18 h for NHC and DHC. This description of HC and metabolite disposition in oral fluid following single-dose administration provides valuable interpretive guidance of HC test results.
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Affiliation(s)
- Edward J Cone
- Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Anne Z DePriest
- Aegis Sciences Corporation, 515 Great Circle Road, Nashville, TN 37228, USA University of Tennessee Health Science Center, College of Pharmacy, Memphis, TN, USA
| | - Rebecca Heltsley
- Aegis Sciences Corporation, 515 Great Circle Road, Nashville, TN 37228, USA
| | - David L Black
- Aegis Sciences Corporation, 515 Great Circle Road, Nashville, TN 37228, USA Department of Pathology, Microbiology, and Immunology, Vanderbilt University, Nashville, TN, USA
| | | | - Charles LoDico
- Division of Workplace Programs, Substance Abuse and Mental Health Services Administration, Rockville, MD, USA
| | - Ron Flegel
- Division of Workplace Programs, Substance Abuse and Mental Health Services Administration, Rockville, MD, USA
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13
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Cone EJ, DePriest AZ, Heltsley R, Black DL, Mitchell JM, LoDico C, Flegel R. Prescription Opioids. III. Disposition of Oxycodone in Oral Fluid and Blood Following Controlled Single-Dose Administration. J Anal Toxicol 2015; 39:192-202. [DOI: 10.1093/jat/bku176] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
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14
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Marsousi N, Daali Y, Rudaz S, Almond L, Humphries H, Desmeules J, Samer CF. Prediction of Metabolic Interactions With Oxycodone via CYP2D6 and CYP3A Inhibition Using a Physiologically Based Pharmacokinetic Model. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2014; 3:e152. [PMID: 25518025 PMCID: PMC4288002 DOI: 10.1038/psp.2014.49] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2014] [Accepted: 09/29/2014] [Indexed: 01/01/2023]
Abstract
Evaluation of a potential risk of metabolic drug–drug interactions (DDI) is of high importance in the clinical setting. In this study, a physiologically based pharmacokinetic (PBPK) model was developed for oxycodone and its two primary metabolites, oxymorphone and noroxycodone, in order to assess different DDI scenarios using published in vitro and in vivo data. Once developed and refined, the model was able to simulate pharmacokinetics of the three compounds and the DDI extent in case of coadministration with an inhibitor, as well as the oxymorphone concentration variation between CYP2D6 extensive metabolizers (EM) and poor metabolizers (PM). The reliability of the model was tested against published clinical studies monitoring different inhibitors and dose regimens, and all predicted area under the concentration–time curve (AUC) ratios were within the twofold acceptance range. This approach represents a strategy to evaluate the impact of coadministration of different CYP inhibitors using mechanistic incorporation of drug-dependent and system-dependent available in vitro and in vivo data.
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Affiliation(s)
- N Marsousi
- 1] Department of Clinical Pharmacology and Toxicology, Geneva University Hospitals, Geneva University, Geneva, Switzerland [2] Department of Pharmaceutical Analytical Chemistry, School of Pharmaceutical Sciences, Geneva University, Geneva, Switzerland
| | - Y Daali
- 1] Department of Clinical Pharmacology and Toxicology, Geneva University Hospitals, Geneva University, Geneva, Switzerland [2] Swiss Centre for Applied Human Toxicology, Geneva, Switzerland
| | - S Rudaz
- 1] Department of Pharmaceutical Analytical Chemistry, School of Pharmaceutical Sciences, Geneva University, Geneva, Switzerland [2] Swiss Centre for Applied Human Toxicology, Geneva, Switzerland
| | - L Almond
- Simcyp Limited (a Certara Company), Blades Enterprise Centre, Sheffield, UK
| | - H Humphries
- Simcyp Limited (a Certara Company), Blades Enterprise Centre, Sheffield, UK
| | - J Desmeules
- 1] Department of Clinical Pharmacology and Toxicology, Geneva University Hospitals, Geneva University, Geneva, Switzerland [2] Swiss Centre for Applied Human Toxicology, Geneva, Switzerland
| | - C F Samer
- 1] Department of Clinical Pharmacology and Toxicology, Geneva University Hospitals, Geneva University, Geneva, Switzerland [2] Swiss Centre for Applied Human Toxicology, Geneva, Switzerland
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15
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Oral fluid for the detection of drugs of abuse using immunoassay and LC–MS/MS. Bioanalysis 2013; 5:1555-69. [DOI: 10.4155/bio.13.115] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The utility of oral fluid as a sample matrix for the analysis of drugs has been increasing in popularity over the last few years. This is largely because of collection advantages over other matrices, but also due to the rapid improvements in analytical assays including highly sensitive liquid reagent format enzyme immunoassays and LC–MS/MS. This review will highlight improvements in assay formats, sensitivity, laboratory equipment and sample processing using low sample volumes to expand drug test profiles.
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