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Record W2800043206 · doi:10.1016/j.jpba.2018.04.016

Efficiency of extraction and conversion of pseudoephedrine to methamphetamine from tamper-resistant and non-tamper-resistant formulations

2018· article· en· W2800043206 on OpenAlexfundno aff
Brandon C. Presley, Bob Bianchi, John R. Coleman, Fran Diamond, Gerry McNally

Bibliographic record

VenueJournal of Pharmaceutical and Biomedical Analysis · 2018
Typearticle
Languageen
FieldChemistry
TopicAnalytical Methods in Pharmaceuticals
Canadian institutionsnot available
FundersJohnson and JohnsonAssociation of Canadian Universities for Research in Astronomy
KeywordsPseudoephedrineChemistryEphedrineNasal decongestantChromatographyExtraction (chemistry)Particle sizePharmacology

Abstract

fetched live from OpenAlex

Clandestine chemists have demonstrated an ability to convert commercially available pseudoephedrine formulations to methamphetamine. Some of these formulations have properties that manufacturers claim limit or block the extraction of pseudoephedrine and its direct conversion to methamphetamine. In this study, 3 commercially available pseudoephedrine formulations were evaluated for ease of extraction and conversion to methamphetamine using a common chemistry technique called the one-pot method that is frequently employed by clandestine chemists. Two marketed pseudoephedrine formulations with claimed tamper-resistant properties – Zephrex-D® and Nexafed® – were compared to Sunmark®, a comparator formulation of pseudoephedrine without tamper-resistant properties. Particle size reduction was conducted using 8 readily available tools; solubility was assessed using 2 common aqueous solutions and various reaction conditions (e.g., temperature, stirring); extractability was evaluated using 8 common organic solvents. The one-pot (single vessel) method commonly used in clandestine processes was employed; chemicals and equipment were purchased locally on the open market. Quantities and addition times of the chemicals used to carry out the procedure and the duration of the reaction were varied to determine the effect on methamphetamine yield. The procedure was appropriately scaled and conducted in a controlled environment to reduce risk and maximize yields. Pseudoephedrine and methamphetamine were quantified using liquid chromatography-tandem mass spectrometry (LC–MS/MS). Standard quantitative procedures were used to determine the quantities of pseudoephedrine and methamphetamine recovered and produced, respectively. Particle size reduction resulted in some loss of material of each pseudoephedrine formulation; Zephrex-D tablets were broken down to a coarse material; Nexafed and Sunmark tablets were reduced to a fine powder. The solubility rates of intact and ground tablets varied by product; Zephrex-D was most resistant to solubilizing while Nexafed and Sunmark were comparable and dissolved completely, demonstrating no solubility-resistant properties. Conditions of the one-pot method were modified throughout the studies to increase methamphetamine yield. Using optimal parameters identified in these studies and allowing the reaction to proceed for 90 min, average percent conversions were similar for the 3 formulations: 43.3% for Zephrex-D, 46.4% for Nexafed, and 48.6% for Sunmark. The greatest conversion occurred with a 150 min reaction time and resulted in 44.8%–48.4% conversion of Zephrex-D, 54.1%–66.4% conversion of Nexafed, and 58.6%–71.8% conversion of Sunmark. This series of methodological evaluations demonstrated that clandestine chemists can readily produce similar yields of methamphetamine using pseudoephedrine products with and without claimed tamper-resistant technology.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.383
Teacher spread0.353 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2018
Admission routes1
Has abstractyes

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