Synthetic route based on methamphetamine impurity index analysis and method for evaluating mutual relevance of methamphetamine impurity index analysis

Abstract

The invention discloses a synthetic route based on methamphetamine impurity index analysis and a method for evaluating mutual relevance of methamphetamine impurity indexes, which is characterized by comprising the following steps of: enriching MA low-content impurities by adopting a microcirculation solid-phase microextraction technology, and analyzing 22 characteristic target substances in illegal MA products by utilizing ultra-high performance liquid chromatography-tandem mass spectrometry. And deducing a synthetic route by taking an alkaloid peak area as a related calculation data variable. By analyzing the synthetic route and the correlation, the current MA selling network / source and MA manufacturing process can be identified and fed back to an investigation department in time. Therefore, targeted reference is provided for formulating policies for fighting against MA crimes, and technical support is also provided for construction of political and law intelligence and criminal technology innovation systems.

Description

Technical Field

[0001] The present invention relates to a synthesis route based on methamphetamine impurity index analysis and a method for evaluating their mutual correlation, and belongs to the field of dangerous goods inspection. Background Art

[0002] Against the backdrop of the globalization of dangerous goods, the production and trafficking of these substances are becoming increasingly prominent, and drug abuse is becoming a growing problem. Methamphetamine (MA), a highly addictive and difficult-to-quit substance, appears as a crystalline white substance. It is a laboratory-produced drug and has become one of the world's most harmful drugs. MA can be manufactured using simple materials that can be purchased in most pharmacies and synthesized at home. In recent years, Mexican dangerous goods cartels have produced large quantities of very pure MA. In recent years, driven by lucrative market demands and ongoing high-pressure crackdowns, MA synthesis methods have evolved. MA can be synthesized through a variety of pathways, each yielding a unique profile of organic impurities, which is significantly influenced by the precursors and chemicals used, as well as the equipment and various stages of synthesis. Therefore, impurity analysis can provide information that helps to identify the relationship between dangerous goods seizures, their sources, and trafficking routes. However, due to different synthesis routes, different confounding substances were added by relevant personnel in order to make huge profits, resulting in low levels of characteristic reaction intermediates, by-products and impurities of MA in some samples, which are difficult to detect on analytical instruments. Therefore, certain pretreatment of the samples is required to meet the analysis requirements.

[0003] Currently, underground illegal laboratories use ephedrine and 1-phenyl-2-propanone as raw materials to synthesize MA. Statistical techniques such as principal component analysis (PCA) and hierarchical cluster analysis can be used to quantitatively analyze impurities in synthetic raw materials, which is very helpful in obtaining relevant synthetic information. Dayrit et al. successfully inferred the synthetic route by analyzing trace impurities in MA using gas chromatography-mass spectrometry. Segawa et al. used multivariate analysis to establish an analytical method based on spatial isomer ratios to infer the synthetic information of 44 amphetamine samples. Inferring the synthetic pattern of MA by analyzing characteristic impurity components in samples helps to determine the relationship between drug seizure volume, drug source, and trafficking route. The results of this analysis can be used to help personnel obtain intelligence to track dangerous goods trafficking organizations and their trading routes. Krawczyk and Lee et al. used Euclidean distance, Canberra distance, and Pearson correlation to analyze the peak areas of MA target compounds to identify samples with similar impurity profiles. Andersson used gas chromatography-mass spectrometry to analyze amphetamine samples to establish links between samples from the same batch of amphetamine, demonstrating that Pearson correlation is the most successful distance metric for finding related samples. Furthermore, after years of research and accumulation, the National Narcotics Laboratory of the Ministry of Public Security developed an industry standard (JD / YJY03.02-2017) for tracing the origins (i.e., the "Golden Triangle" or "Golden Crescent") and characteristics of amphetamine, playing a significant role in the nation's fight against drug abuse. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method for analyzing the synthesis route of methamphetamine based on impurity indicators and evaluating their mutual correlation, which provides a targeted reference for formulating policies to combat crimes involving dangerous goods and also provides technical support for the construction of political and legal intelligence and criminal technology innovation systems.

[0005] The technical solution of the present invention is: a method for analyzing the synthesis route of methamphetamine based on impurity indexes and evaluating their mutual correlation, using microcirculation solid-phase microextraction technology to enrich low-content MA impurities, then using ultra-performance liquid chromatography-tandem mass spectrometry to analyze 22 characteristic target substances in illegal MA products, and using alkaloid peak area as a relevant calculation data variable to infer the synthesis route.

[0006] Microcirculation solid-phase microextraction technology was first used to enrich low-content characteristic target substances in the MA synthesis process. The processed samples were then analyzed using UPLC-MS / MS technology, and the MA synthesis route was inferred from the trace impurity components in the samples through targeted screening technology. Principal component analysis (PCoA) and Pearson correlation coefficient method were used to classify and analyze the correlation between MA and known synthesis process routes. Through analysis of synthesis routes and correlations, the current dangerous goods trafficking network / source and dangerous goods manufacturing process were identified.

[0007] The method first uses microcirculation solid-phase microextraction technology to enrich low-content characteristic target substances in the MA synthesis process: the extraction column is rinsed with acetonitrile and ethyl acetate in sequence and then sealed and stored; the methamphetamine sample is weighed, dissolved in anhydrous ethanol and ultrasonically dissolved, placed in a microcirculation headspace solid-phase enrichment device and connected to the adsorption column, using amino resin as the adsorbent, and heated and circulated at 110°C with a gas flow rate of 3-5 mL / min. The mixture is naturally cooled to room temperature, the adsorbent in the solid-phase microextraction column is removed, an internal standard solution is added, and the extract is then subjected to UPLC-MS / MS analysis.

[0008] The chromatographic conditions described: Acquity CSH TM C18 column (100 mm × 2.1 mm, 1.7 μm); column temperature, 40°C; eluents A (aqueous solution containing 0.1% formic acid and 2 mM ammonium formate) and B (acetonitrile). Injection volume was 1 μL, and the flow rate was maintained at 0.4 mL / min.

[0009] The mass spectrometry conditions are as follows: electrospray positive ion source; multiple reaction monitoring mode; capillary voltage 0.50 kV; cone voltage 20 V; desolvation temperature 500°C; desolvation rate 1000 L / hr; cone gas 150 L / hr; collision gas: argon; acquisition time 0-16.5 minutes. A total of 22 characteristic impurities were selected as analysis targets.

[0010] Also included: Synthesis route selection correlation analysis target: According to the standard methods JD / YJY03.021-2017, GA / T 2053-2023 and Locisirō, the peak areas of the nine target substances were normalized to obtain the normalized peak area Si of each target substance. Si was introduced into equations (1), (2) and (3) to calculate the N, E and R values of the samples respectively:

[0011]

[0012] Where Si is the normalized peak area of each target in the sample, N0, N i 、E0、E i , R0 and R i The values are shown in Table 3.

[0013] Select the target for correlation analysis according to the synthesis route. When the N value is the largest, select the characteristic components with sequence numbers 1, 2, 3, 4, 6, 8, 9, 10, 11, 16, 18, 19, 20, 21, and 22; when the E value is the largest, select 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 13, 16, 17, 19, and 20; when the R value is the largest, select 1, 3, 5, 6, 8, 9, 10, 12, 14, 15, 16, and 18; record the peak areas of all targets corresponding to N, E, and R, and normalize the peak areas of the targets to Si. For samples X and Y, calculate the correlation coefficient "r" between the two samples using the Pearson correlation coefficient method according to formula (4):

[0014]

[0015] S Xi and S Yi are the normalized peak areas of each target in samples X and Y, respectively; n is the number of targets corresponding to the synthetic routes (N, E, R) of the samples; if R>0.98, the correlation between samples X and Y is very strong, and there is a high possibility that the MA samples in the two cases came from the same processing batch.

[0016] Beneficial effects of the present invention: In the pre-treatment, the present application first adopts microcirculation solid phase microextraction technology to enrich the low-content characteristic target substances in the MA synthesis process. The treated samples are subjected to UPLC-MS / MS technology, and the MA synthesis route is inferred from the trace impurity components in the sample through targeted screening technology. The principal component analysis (PCoA) and Pearson correlation coefficient method are used to classify and analyze the correlation between MA and known synthesis process routes. Through the analysis of synthesis routes and correlations, the current dangerous goods trafficking network / source and dangerous goods manufacturing process can be identified and promptly fed back to the investigation department. This provides a targeted reference for the formulation of policies to combat dangerous goods crimes, and also provides technical support for the construction of political and legal intelligence and criminal technology innovation systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The principal coordinates analysis of each synthetic route was performed using the Pearson distance algorithm; (a), N; (b), E; (c), R;

[0018] Figure 2 It is the correlation discriminant diagram of the N samples of the synthetic route;

[0019] Figure 3 This is the correlation discriminant diagram of the samples of synthetic route R. DETAILED DESCRIPTION

[0020] 1.1 Reagents, samples, and instruments

[0021] Acetonitrile, methanol, formic acid, and ammonium formate (chromatographic grade, purity >99%) were purchased from Merck (Darmstadt, Germany). Quality control (QC) samples of MA and α-PVP were obtained from the National Narcotics Laboratory of the Ministry of Public Security (Beijing).

[0022] The instruments used included an UPLC-MS / MS with an electrospray ionization source (Aqcuity / Xevo TQ-S, Waters, USA); a headspace microcirculation solid-phase microextraction instrument and solid-phase microextraction columns (Jilin Xingke Limin Technology Development Co., Ltd.); an analytical balance purchased from Mettler-Toledo GmbH (XSR205DU, USA); an ultrasonic cleaner produced by Kunshan Ultrasonic Instrument Co., Ltd. (KQ-100DV, China); and a vortex meter purchased from Scientific Industries, Inc. (G560E, USA).

[0023] 1.1.1 Sample Source

[0024] MA was obtained from a dangerous goods case seized by relevant departments in Guizhou Province, totaling 169 samples. Due to the confidentiality of the case, the seized samples were individually named M1-M169.

[0025] 1.1.2 Reagent Preparation

[0026] Internal standard stock solution (1 mg / mL): Weigh 10 mg of α-PVP, dissolve it in methanol and dilute to 10 mL. Mix thoroughly to prepare an internal standard stock solution with a concentration of 1 mg / mL. Store at 0-5°C. The shelf life is 6 months.

[0027] Internal standard solution (10 ng / mL): Accurately weigh a certain amount of internal standard stock solution and dilute it to 10 ng / mL with an aqueous solution containing 0.1% formic acid and 2 mM ammonium formate. Store at 0-5°C. The shelf life is 1 month.

[0028] 1.2 Analytical methods

[0029] 1.2.1 Sample preparation

[0030] All samples were ground into powder prior to data acquisition. 5 mg of MA (with an acceptable range of 5 ± 0.2 mg) was placed in a centrifuge tube, mixed with 10 mL of internal standard solution by sonication and vortexing, and then filtered through a 0.22 μm microporous filter for UPLC-MS / MS analysis. QC and blank samples were also processed as described above. When applying the above method to blanks, it was necessary to confirm the absence of substances interfering with the analytes.

[0031] Pretreatment of low-level characteristic reaction intermediates, byproducts, and impurities: Rinse the extraction column sequentially with 3 mL of acetonitrile and 3 mL of ethyl acetate, then seal and store. Weigh (100 ± 5) mg of methamphetamine sample and dissolve it in 1 mL of anhydrous ethanol. Ultrasonicate and place it in a microcirculating headspace solid phase enrichment device connected to an adsorption column (amino resin as the adsorbent). Heat and circulate the extraction at 110°C for 30 min (gas flow rate: 3-5 mL / min). Cool naturally to room temperature. Remove the adsorbate from the solid phase microextraction column and place it in a small test tube. Add 0.5 mL of internal standard solution. The extract is then analyzed by UPLC-MS / MS.

[0032] 1.2.2 Liquid chromatography-mass spectrometry

[0033] Chromatographic conditions: Acquity CSH TM C18 column (100 mm × 2.1 mm, 1.7 μm); column temperature, 40°C; eluents A (0.1% formic acid and 2 mM ammonium formate in water) and B (acetonitrile). Injection volume was 1 μL, and the flow rate was maintained at 0.4 mL / min. The elution process is shown in Table 1.

[0034] Table 1. Gradient elution program for liquid chromatography mobile phase

[0035]

[0036] Mass spectrometry conditions: electrospray positive ion source; multiple reaction monitoring mode; capillary voltage 0.50 kV; cone voltage 20 V; desolvation temperature 500 °C; desolvation rate 1000 L / hr; cone gas 150 L / hr; collision gas: argon; acquisition time 0-16.5 minutes. A total of 22 characteristic impurities were selected as analytical targets, and the specific mass spectrometry parameters and reference retention time (t R )See Table 2.

[0037] Table 2. Formulas, QIP, CE, RAR, and t for 22 objectives R and internal standard ɑ-PVP

[0038]

[0039]

[0040] QIP, semiquantitative ion pairing; CE, collision energy; RAR, reference abundance ratio; t R : Reference retention time; “*” indicates semi-quantitative ion pair.

[0041] 1.3 Results Analysis

[0042] 1.3.1 Qualitative analysis

[0043] The chromatogram and mass spectrum of the test sample are compared with those of the QC sample. If the following two conditions are met, it can be determined that the corresponding target substance is detected: (1) The t R The relative error (RE%) is less than 2%. (2) Two parent / daughter ion pairs of the target substance are detected in the test sample (Table 2). The peak area ratios of the qualitative and semi-quantitative ion pairs in the QC sample and the RE% of the corresponding peak area ratios do not exceed the specified limits. With reference to the standard methods JD / Y JY03.021-2017 and GA / T 2053-2023, the maximum allowable relative error of the peak area ratio does not exceed the range of Table 2.

[0044] 1.3.2 Identification of sample synthesis route

[0045] The peak areas of the nine semi-quantitative ion pairs numbered 2, 3, 4, 5, 11, 13, 14, 16, and 21 in the sample to be tested were recorded. The peak area of the undetected target was set to 200. According to the standard methods JD / Y JY03.021-2017, GA / T2053-2023, and Locisirō, the peak areas of the nine target substances were normalized to obtain the normalized peak area Si for each target substance. Si was introduced into equations (1), (2), and (3) to calculate the N, E, and R values of the sample, respectively.

[0046]

[0047] Where Si is the normalized peak area of each target in the sample, N0, N i 、E0、E i , R0 and R i The values are shown in Table 3.

[0048] Table 3. Synthesis route discrimination coefficient formula

[0049]

[0050] 1.3.3 Distinguishing Correlations Between Samples

[0051] Select targets for correlation analysis based on the synthetic route. When the N value is the largest, the characteristic components are selected as 1, 2, 3, 4, 6, 8, 9, 10, 11, 16, 18, 19, 20, 21, and 22; when the E value is the largest, the components are selected as 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 13, 16, 17, 19, and 20; and when the R value is the largest, the components are selected as 1, 3, 5, 6, 8, 9, 10, 12, 14, 15, 16, and 18.

[0052] Record the peak areas of all targets corresponding to N, E, and R, and normalize the peak areas of the targets to Si. For samples X and Y, calculate the correlation coefficient "r" between the two samples using the Pearson correlation coefficient method according to formula (4):

[0053]

[0054] Here S Xi and S Yi are the normalized peak areas for each target in samples X and Y, respectively. n is the number of targets corresponding to the synthetic route (N, E, R) of the sample. If R > 0.98, there is a strong correlation between samples X and Y, and it is highly likely that the MA samples in both cases were derived from the same processing batch.

[0055] 1.4 Data Analysis

[0056] Refer to "Methamphetamine Synthesis Route and Correlation Identification between Samples" JD / Y JY03.021-2017 and GA / T2053-2023, record t R The peak areas and peaks were analyzed using PCoA and Pearson's correlation coefficient. Data were processed using Microsoft Excel 2021, and analyzed using one-way analysis of variance using IBM Statistics SPSS V27.0. The similarity of sample components was determined using PCoA using the Majorbio cloud platform (https: / / cloud.majorbio.com / page / tools / ).

[0057] Results and Discussion

[0058] 2.1 Qualitative analysis

[0059] In the qualitative analysis results of 169 MA experimental samples, there was no corresponding target peak in the blank test, which proved the effectiveness of the parallel test sample determination. R The RE% of 22 acidic / neutral targets is shown in Table S1. R The percentages were all less than 2%, including those for the QC samples, meeting the requirements. Furthermore, the peak area ratios of the two parent-daughter ion pairs of the target compound in the test samples, and the RE% of the peak area ratios of the qualitative and semi-quantitative ion pairs in the QC samples to the corresponding peak area ratios were within the range of -26.28–24.50, as shown in Table S2, which is less than the maximum allowable relative error.

[0060] 2.2 Identification of sample synthesis routes

[0061] MA has a simple structure and multiple synthetic routes. Its main raw materials include ephedrine, pseudoephedrine, and propiophenone. The Nagai method for synthesizing methamphetamine from ephedrine using direct reduction with hydroiodic acid is known as the Nagai method. The Moscow method involves the generation of hydroiodic acid from iodine and red phosphorus, followed by reduction. Due to the need for control over precursor chemicals, pharmaceutical manufacturers have developed methods ranging from one-step reduction to two-step reduction, in which ephedrine is oxidized to fluoroephedrine and then catalytically hydrogenated via hydrogen / palladium reduction, known as the Emde and Hypo methods, respectively. Under strict control of ephedrine, pharmaceutical manufacturers use acetophenone as a raw material and obtain MA via reductive amination, also known as the regeneration method. The N, E, and R values for each sample tested were calculated, as shown in Table 4-(1-6). Sixty-six samples had the highest N values, indicating that the MA was synthesized using the Nagai or Moscow methods; eleven samples had the highest E values, indicating that the MA was synthesized using the Emde or Hypo methods; and 92 samples had the highest R values, indicating that the MA was synthesized using the induction method. Using the same synthesis method and reaction conditions, the types and contents of impurities in MA synthesized at different times by the same operator vary little. The synthesis route can be inferred from the impurity composition. Anderson's research analyzed 11 MA samples and selected 22 stable impurities for synthesis route identification. Zheng claimed to have used gas chromatography-mass spectrometry and multivariate analysis to infer the process route for drug synthesis. The synthetic patterns derived from the samples seized so far can illustrate the development trends of drug production processes and provide a target reference for the control of precursor chemicals.

[0062] Table 4-1. Synthetic routes of 29 identified samples

[0063]

[0064]

[0065] Table 4-2. Synthetic routes of 28 samples identified

[0066]

[0067]

[0068] Table 4-3. Synthetic routes of 29 samples identified

[0069] name Fraction route N E R M58 0.8671 0.0706 0.0622 N M59 0.8187 0.0630 0.1182 N M60 0.7877 0.2094 0.0028 N M61 0.9556 0.0084 0.0359 N M62 0.2519 0.7244 0.0237 E M63 0.7427 -0.0420 0.2992 N M64 0.4717 0.2466 0.2817 N M65 0.7589 0.0456 0.1954 N M66 0.1310 0.7992 0.0697 E M67 0.2587 0.1928 0.5484 R M68 0.2270 0.7076 0.0653 E M69 0.2855 0.0917 0.6227 R M70 type 0.0956 0.1996 0.7048 R Type M71 0.5088 0.3676 0.1235 N M72 0.2497 0.0809 0.6693 R M73 0.1421 0.0803 0.7775 R M74 0.0932 0.8774 0.0294 E M75 0.0382 0.8827 0.0791 E M76 0.5930 0.1170 0.2899 N M77 0.3417 0.2485 0.4097 R M78 0.7474 0.1490 0.1035 N Type M79 0.6503 0.3667 -0.0171 N M80 0.1003 0.1483 0.7514 R Type M81 0.7722 0.0933 0.1344 N M82 0.4723 0.3046 0.2229 N M83 0.6201 0.1927 0.1871 N M84 0.6193 0.2189 0.1617 N M85 0.6153 0.1959 0.1887 N M86 0.4136 0.3768 0.2095 N

[0070] Table 4-4. Synthetic routes of 28 samples identified

[0071]

[0072]

[0073] Table 4-5. Synthetic routes of 29 samples identified

[0074]

[0075]

[0076] Table 4-6. Synthetic routes of 26 samples identified

[0077] name Fraction route N E R Type M144 0.2428 0.2028 0.5543 R M145 0.2532 0.1433 0.6034 R M146 0.2427 0.2017 0.5555 R M147 0.2307 0.1583 0.6109 R M148 0.2390 0.1939 0.5670 R M149 0.2379 0.2060 0.5561 R M150 0.2420 0.2014 0.5565 R M151 0.2409 0.2082 0.5509 R M152 0.2145 0.1893 0.5961 R M153 0.2755 0.1324 0.5921 R M154 0.1964 0.1969 0.6066 R M155 0.2026 0.2027 0.5947 R M156 0.1947 0.1988 0.6064 R M157 0.2530 0.1351 0.6117 R M158 0.2362 0.1975 0.5662 R M159 0.3063 0.0839 0.6097 R M160 0.2660 0.1214 0.6126 R M161 0.2698 0.1210 0.6092 R M162 0.2884 0.1128 0.5987 R M163 0.2807 0.1190 0.6002 R M164 0.2786 0.1209 0.6004 R M165 0.2922 0.1124 0.5953 R M166 0.2529 0.1333 0.6138 R M167 0.2655 0.1267 0.6077 R M168 0.2675 0.1263 0.6061 R M169 0.2875 0.1166 0.5958 R

[0078] 2.3 Main grouping of correlations by PCoA

[0079] PCoA is an unconstrained data dimensionality reduction analysis method that can be used to study the similarity or difference of sample composition. PCoA method is used to reduce the dimensionality of target impurity variables in samples with synthesis pathways N, E and R, such as Figure 1 As shown. Two principal components were extracted from the PCoA analysis, with the cumulative contributions of PC1 and PC2 ranging from 59.24% to 78.26%. The scatter plot analysis of the PCoA method concluded that MA and different production routes (N, E, and R) can be well separated, and samples from the same area on the plane are likely to have similarities. This result suggests that MA samples seized in the same area may have the same source or processing method. PCoA, similar to PCA, uses dimensionality reduction to identify potential principal components that cause overall differences. Duan used the methods and means of PCA to determine that the source or processing of dangerous goods samples seized in Dehong and Lincang may be different. However, it is also possible that samples are located in the same area of PCoA (or PCA) but are actually not related, mainly because the two data obtained through dimensionality reduction methods only partially represent the information in the data. Therefore, PCoA can be used as a preliminary estimate of sample correlation but cannot be used as a final basis for judging the correlation of MA samples.

[0080] 2.4 Correlation determination between samples

[0081] The Pearson correlation coefficient is a statistically accurate measure of the closeness of the relationship between two variables. According to Dujourdy, mathematical models of drug correlation based on Pearson and cosine function correlation were used to develop a mathematical model of drug correlation and characterize different seized samples and their synthetic routes. According to standard methods JD / Y JY03.021-2017 and GA / T 2053-2023, when the correlation coefficient R>0.98, the correlation between two samples can be considered to be extremely strong. 66 samples from the N synthetic route were screened and 17 groups of highly correlated samples were identified, each containing 2-8 MA samples, such as Figure 2As shown. There is no correlation among the 11 samples of the E synthetic route. The R synthetic route has the largest number of samples (Table 4, 96 samples), and 7 groups of highly correlated samples are selected, with each group containing 2 - 38 samples, as Figure 3 shown. This may be because the samples from this synthetic route were seized at the same location, resulting in a strong correlation among most samples, and these samples may come from the same batch processed by the same manufacturer. Andersson analyzed 11 MA samples and established the correlation among amphetamine samples from the same batch using the human correlation discrimination between samples from the same batch. This result further confirmed the reliability of the human correlation. As Figure 2 and Figure 3 shown, some samples are at the critical value of close correlation (0.96 < R < 0.98), which is due to various variables affecting the application of the Pearson distance method, and using decimal places when calculating R may also lead to small deviations in the results. Combining with actual cases, it is found that the obtained results are consistent with the actual situation, indicating that our correlation analysis method is reliable. By analyzing the characteristic impurity components of the samples, the correlation between the samples seized under different circumstances is speculated, and the synthesis mode of MA is inferred. This provides technical support for the management of synthetic raw materials and the investigation of dangerous goods cases, and is of great significance for relevant departments to combat the production and trafficking of illegal dangerous goods.

[0082] Conclusion

[0083] In this application, the microcirculation solid-phase microextraction technology is first used in the pretreatment to enrich the low-content characteristic target substances in the MA synthesis process. The processed samples are based on the target screening technology coupled with UPLC-MS / MS to target-screen the trace impurity components in the samples to achieve the inference of the drug production synthesis process route. The PCoA and Pearson correlation coefficient methods are used to classify and associate MA with the known synthesis process routes. The results show that this method can infer the synthesis method by analyzing the components in the MA samples, check the raw materials used in drug production, and determine the correlation between the seized substances of different batches without standard substances. Samples from the same source can be classified, and according to the classification and correlation, the source of the trafficking network can be checked, and the current trends in the drug manufacturing process can be studied. This will provide a targeted reference basis for the control and management of chemicals that are easy to manufacture dangerous goods, and achieve a full-chain crackdown on the source of drug-related crimes.

Claims

1. A method for analyzing a methamphetamine synthesis route and its correlation assessment based on impurity index, characterized in that: Microcirculation solid-phase microextraction technology was used to enrich low-content MA impurities, and then ultra-performance liquid chromatography-tandem mass spectrometry was used to analyze 22 characteristic target substances in illegal MA products. The synthetic route was inferred using the alkaloid peak area as the relevant calculation data variable.

2. A method for analyzing a synthetic route based on methamphetamine impurity index and its correlation assessment according to claim 1, characterized in that: Microcirculation solid-phase microextraction technology was first used to enrich low-content characteristic target substances in the MA synthesis process. The processed samples were then analyzed using UPLC-MS / MS technology, and the MA synthesis route was inferred from the trace impurity components in the samples through targeted screening technology. Principal component analysis (PCoA) and Pearson correlation coefficient method were used to classify and analyze the correlation between MA and known synthesis process routes. Through analysis of synthesis routes and correlations, the current MA selling network / source and MA manufacturing process were identified.

3. A method for analyzing a synthetic route based on methamphetamine impurity index and its correlation assessment according to claim 1, characterized in that: The method first uses microcirculation solid-phase microextraction technology to enrich low-content characteristic target substances in the MA synthesis process: the extraction column is rinsed with acetonitrile and ethyl acetate in sequence and then sealed and stored; the methamphetamine sample is weighed, dissolved in anhydrous ethanol and ultrasonically dissolved, placed in a microcirculation headspace solid-phase enrichment device and connected to the adsorption column, using amino resin as the adsorbent, and heated and circulated at 110°C with a gas flow rate of 3-5 mL / min. The mixture is naturally cooled to room temperature, the adsorbent in the solid-phase microextraction column is removed, an internal standard solution is added, and the extract is then subjected to UPLC-MS / MS analysis.

4. A method for analyzing a synthetic route based on methamphetamine impurity index and its correlation assessment according to claim 1, characterized in that: Chromatographic conditions: Acquity CSH TM C18 column (100 mm × 2.1 mm, 1.7 μm); column temperature, 40°C; eluents A (aqueous solution containing 0.1% formic acid and 2 mM ammonium formate) and B (acetonitrile). Injection volume 1 μL, flow rate maintained at 0.4 mL / min.

5. A method for analyzing a synthetic route based on methamphetamine impurity index and its correlation assessment according to claim 1, characterized in that: Mass spectrometry conditions: electrospray positive ion source; multiple reaction monitoring mode; capillary voltage 0.50 kV; cone voltage 20 V; desolvation temperature 500°C; desolvation rate 1000 L / hr; cone gas 150 L / hr; collision gas: argon; acquisition time 0-16.5 minutes. A total of 22 characteristic impurities were selected as analytical targets.

6. A method for analyzing a synthetic route based on methamphetamine impurity index and its correlation assessment according to claim 1, characterized in that: Also includes: Targets for correlation analysis of synthetic route selection: According to standard methods JD / Y JY03.021-2017, GA / T 2053-2023 and Locisirō, the peak areas of the nine target substances were normalized to obtain the normalized peak area Si of each target substance. Si was introduced into equations (1), (2) and (3) to calculate the N, E and R values of the samples respectively: Where Si is the normalized peak area of each target in the sample, N0, N i 、E0、E i , R0 and R i The values are shown in Table 3.

7. A method for analyzing a synthetic route based on methamphetamine impurity indexes and their correlation assessment according to claim 6, characterized in that: Select the target for correlation analysis according to the synthesis route. When the N value is the largest, select the characteristic components with sequence numbers 1, 2, 3, 4, 6, 8, 9, 10, 11, 16, 18, 19, 20, 21, and 22; when the E value is the largest, select 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 13, 16, 17, 19, and 20; when the R value is the largest, select 1, 3, 5, 6, 8, 9, 10, 12, 14, 15, 16, and 18. Record the peak areas of all targets corresponding to N, E, and R, and normalize the peak areas of the targets to Si. For samples X and Y, calculate the correlation coefficient "r" between the two samples using the Pearson correlation coefficient method according to formula (4): S Xi and S Yi are the normalized peak areas of each target in samples X and Y, respectively; n is the number of targets corresponding to the synthetic routes (N, E, R) of the samples; if R>0.98, the correlation between samples X and Y is very strong, and there is a high possibility that the MA samples in the two cases came from the same processing batch.

Images