Article In Press : Article / Volume 4, Issue 1

Detection Of Fentanyl And Its Analogues Using Portable Raman Spectroscopy In The Monitoring Of Fraudulent Activities

Duban Mauricio Muñoz ReyesJorge Humberto Restrepo Zapata*

Universidad Santiagode Cali, Valledel Cauca. Colombia

Correspondng Author:

Jorge Humberto Restrepo Zapata, Universidad Santiagode Cali, Valledel Cauca. Colombia

Citation:

Duban Mauricio Muñoz Reyes, Jorge Humberto Restrepo Zapata. (2025). Detection Of Fentanyl And Its Analogues Using Portable Raman Spectroscopy In The Monitoring Of Fraudulent Activities "Systematic Review. Pharmacy and Drug Development. 4(1). DOI:10.58489/2836-2322/037

Copyright:

© 2025 Jorge Humberto Restrepo Zapata, this is an open-access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

  • Received Date: 25-01-2025   
  • Accepted Date: 01-02-2025   
  • Published Date: 06-02-2025
Abstract Keywords:

Analogues, Rapid Detection, Portable Raman Spectroscopy, Fentanyl and Fraudulent Sale.

Abstract

Among the controlled medications we have Fentanyl and its analogues, it is an extremely powerful synthetic opioid medication, even up to 50 times stronger than Heroin and 100 times stronger than morphine. In medicine, it is used to treat very intense pain, such as in cancer patients, especially after surgery. However, its high potency makes it a very dangerous substance if used for recreational purposes or if mixed with other drugs. Portable Raman spectroscopy is an invaluable tool that allows for the rapid and accurate detection of fentanyl and its analogues and for other types of dangerous and controlled substances, improving the safety and effectiveness of the study. In this study, the literature covering recent years (2017-2024) about the Portable Raman Spectroscopy application will be systematically reviewed, an extensive review will be made, thoroughly analyzing its advantages in the detection of Fentanyl and its analogues in the monitoring of fraudulent activities. demonstrating the speed of this instrument in detection, which is done in seconds. It is a non-destructive method since it does not damage the sample and allows for on-site analysis; which, due to its versatility, allows analyzing solids, liquids and powders. It allows rapid detection which is based on modified straight line local screening (LSLS) where principal component analysis (PCA) is developed as a type of fingerprint where it quickly distinguishes counterfeit medicines from authentic ones.

HIGHLIGHTS

  • An advantage of Handheld Raman Spectroscopy is its excellent sensitivity for detecting fentanyl and fentanyl analogues and its great potential for screening and detecting drug mixtures.
  • Suspicious drug samples can be analyzed quickly and safely using benchtop instruments such as inexpensive portable Raman spectrometers, which many forensic labs and police departments already have on-site. (Dogruer et al., 2024, p. 2)
  • Raman spectroscopy has great potential for the analysis of fentanyl and its analogues. These spectroscopic techniques make it possible to differentiate between different fentanyl analogues, including positional isomers.
  • Portable Raman spectroscopy compared to other methods of detection of controlled drugs, especially with fentanyl, is the due speed that the identification is carried out in seconds. It is a non-destructive method as it does not damage the sample and the Portable Raman Spectroscopy equipment allows for on-site analysis. (Kline ND, Guicheteau JA).

Introduction

Falsified controlled medicines pose a significant and growing threat to public health globally, affecting both individuals and health systems in general. These products, designed to mimic legitimate drugs, are often manufactured under unsanitary conditions and without meeting required regulatory standards. According to Vera, 2019, counterfeit medicines can affect both branded and generic products, and can be products made with the wrong or correct ingredients, and can even be replaced by toxic substances, with active ingredients in insufficient or no quantities, or with falsified packaging. In this way, the quality of falsified medicines can be evidenced in products when they do not contain the active ingredients indicated on their labelling or these are different. Likewise, as mentioned by the National Institute on Drug Abuse (NIDA), 2021, they state that fentanyl, a synthetic opioid with a potency 50 times greater than heroin and 100 times higher than morphine, stands out as a critical problem. These products mimic legitimate, regulated medications, such as opioid painkillers or tranquilizers, but may contain dangerous ingredients. Medication errors are the most frequent and preventable source of harm to patients. They can manifest themselves at different points in the health care process, from prescription to administration of the drug (Tariq et al. 2024).

The presence and distribution of substandard medicines and counterfeit pharmaceuticals have shown a considerable increase in domestic markets, becoming a public health problem that requires urgent attention. This phenomenon can be explained according to Worku et al. 2024, the circulation of substandard and falsified pharmaceutical products in national markets has increased, which has generated great concern, which directly affects local health systems, compromising the effectiveness of medical treatments and endangering patient safety. As a result, there is a loss of trust in the institutions responsible for ensuring the quality and safety of medicines, which further aggravates the situation. 

 The identification of falsified medicines has traditionally been a challenge in the field of pharmacovigilance and pharmaceutical quality control. Conventional analytical methods, such as Portable Raman Spectroscopy, High Performance Liquid Chromatography (HPLC), and Near-Infrared (NIR) spectroscopy, have been widely used for this purpose due to their ability to offer accurate and detailed analyses of the active substances and excipients present in medicines. The portable Raman spectral technique and the NIRS technique showed potential to detect hundreds of drugs with insufficient concentration and could therefore be used together to identify inferior drugs (Wilson, 2017).

However, these sophisticated methods have important limitations that affect their applicability in contexts where broader and more accessible surveillance is required. Among the main barriers are the high costs associated with specialized equipment and maintenance.

According to Rodionova et al. 2019, adequate and accurate equipment to identify all types of falsified controlled medicine are high-cost and time-consuming methods, so it is essential to have trained and specialized personnel in specific places and of great scientific recognition that endorses technical support.

In this context, the need to develop faster, cheaper and more accessible approaches that can complement or replace traditional techniques, especially in emergency surveillance scenarios, has been highlighted. This presents an opportunity to explore emerging technologies that can contribute to more efficient detection of counterfeit medicines, thereby improving the safety and quality of pharmaceutical products worldwide. For this reason, Portable Raman spectroscopy was used before the other methods of detection of controlled drugs, especially with fentanyl, since it is faster because the identification is made in seconds. It is a non-destructive method as it does not damage the sample and performs on-site analysis. According to Crocombe et al. 2023, the need to detect fentanyl and its analogues in the field is an important capability to help prevent unintentional exposure or overdose of these substances, which can lead to death. One of the most effective methods for fraudulent detection of fentanyl and its analogues is handheld Raman spectroscopy.

Methodology

A systematic review was carried out following the methodological guidelines proposed by the Joanna Briggs Institute (JBI), which are concerning, robust and exhaustive, in order to guarantee an effective, transparent and pertinent process in the detection of controlled drug such as fentanyl, to prevent fraudulent sale, using the portable Raman spectroscopy method. To this end, a prism diagram is designed for the choice of studies. The JBI has developed a number of methodologies and methods for evidence synthesis to support healthcare decision-making for various types of reviews (Aromataris, 2020).

Definition of the eligibility criteria for the selection of studies

Inclusion criteria: Any type of research that integrates search completion strategies, functionality, and performance of the portable Raman spectral technique for the detection of the drug fentanyl and its analogues, published in English, that are fully available, published from 2017 to 2024.

Present the search strategies used: keywords, age of studies, type of studies, language, if they answer the research question.

Describe the databases consulted, for example: Science Direct, Scopus, Redalyc, Ebsco, Scielo, Google Scholar, etc., as well as the total number of articles found.

Specify the characteristics of the inclusion and exclusion criteria: year of age, language, quality of article, country and others that you consider to be relevant to the objective of your review.

Describe the method of data extraction from the selected studies.

They can be supported by the PRISMA methodology (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and/or other available methodologies that denote a rigorous and methodical process in the development of the research.

Exclusion criteria: This review will exclude individual case study approaches with no special relevance, editorial opinions or reviews without original data, low-quality studies based on predefined risk of bias assessment tools, research that does not address the research question or departs from defined PICO parameters, and duplicate publications.

Identification of sources of information

The search for evidence was reviewed between August and November 2024, in the bibliographic databases: PubMed, Taylor & Francis, Science Direct, Scielo and NIH.

Bias control 

To control biases in the study of fentanyl detection by portable Raman spectroscopy, various strategies will be used to improve the internal validity of the results. Selection bias will be reduced through the application of specific inclusion and exclusion criteria, ensuring the homogeneity of the selected studies and the relevance of their methodologies. Also, information bias will be controlled through the use of reliable and standardized data sources, with rigorous collection parameters that minimize errors due to variability in recording methods.

Table 1. PICO Strategy of the General Question (Own elaboration)

Component

Description 

 

Population

Drug fentanyl and its analogues.

 

Intervention

Performance of the portable Raman spectroscopy technique for the detection of fentanyl and analogues in the monitoring of fraudulent activities.

 

Comparison

Other analytical techniques that can be used for the detection of Fentanyl and its analogues such as Infrared NIR spectroscopy and HPLC high-performance liquid chromatography.

Outcomes

(results)

Findings in the detection of fentanyl and its analogues, evidencing their ability to identify these compounds accurately and quickly in the monitoring of fraudulent activities.

Figure 1. Diagram for the selection of studies (Prisma) (Aromataris, 2020)

Selection of sources of evidence

In the selection of the sources of evidence, a prism diagram was developed (see figure 1) with the purpose of systematically selecting the eligibility of the reviewed articles.

Establishing the search strategy 

The PICO strategy corresponds to a tool to structure the research question and define the elements that guide the search for evidence in the systematic review. According to MarshallWebb et al. 2018, a systematic review may pose the following precise question based on the PICO (population, intervention, comparator, and outcome) elements of its inclusion criteria. In this case, it applies to the research question: How does the Portable Raman spectroscopy technique contribute to the detection of the drug fentanyl and its analogues in the monitoring of fraudulent activities?

Development And Discussion

Development And Discussion

The main findings and contributions regarding the detection of fentanyl and its analogues by Portable Raman spectroscopy in the monitoring of fraudulent activities, consisted of identifying what was proposed by Crocombe, et al., (2023) "the need to detect fentanyl and its analogues in the field is an important capability to help prevent accidental exposure or overdose of these substances, that can result in death." (p.1).

"Doctors and patients can unintentionally make medication errors that lead to harm; however, patients may also intentionally use medications in ways that are not recommended." (Budnitz et al., 2021)

Raman spectroscopy has great potential for the analysis of fentanyl and its analogues. These spectroscopic techniques make it possible to differentiate between different fentanyl analogues, including positional isomers.

"Suspicious drug samples can be analyzed quickly and safely using benchtop instruments or inexpensive portable Raman spectrometers, which many forensic labs and police departments already have on-site. The advantage of the technique is its excellent sensitivity for detecting fentanyl and fentanyl analogues and its great potential for screening and detection of drug mixtures" (Dogruer et al., 2024, p. 2)

Drugs with fraudulent labels such as fentanyl and its analogues are distributed to various health care providers, raising serious concerns about the safety of the pharmaceutical supply chain and potential harm to patients who rely on authentic drugs to treat life-threatening diseases. In this way, Ali et al (2023) state: "The integrity of disease surveillance faces challenges due to the presence of false records. The distortion of accurate epidemiological data makes it difficult for health authorities to assess the real prevalence of diseases." (p. 4)

"As defined by the World Health Organization (WHO), a falsified drug is one that is deliberately and fraudulently mislabeled with respect to its identity and/or origin. Counterfeit products can include products with the right ingredients or with the wrong ingredients, no active ingredients, insufficient active ingredient, or false packaging. (Chen et al., 2020, p. 3)

For this reason, to maximize sensitivity and specificity in the identification of fentanyl compounds and their analogues, it can be evidenced in what is proposed by Gozdzialski et al., (2022) the use of fentanyl and fentanyl compounds yielded a sensitivity of 60% and a specificity of 86%, which reinforces the accuracy of the method under controlled conditions." (p 2)

"Recently, special attention is being paid to portable NIR and Raman devices.

In fact, in addition to their miniaturization, these devices can integrate intelligent decision-making algorithms and built-in spectral libraries. Clearly, they can offer significant advantages over conventional analytical chemistry methods in drug detection. According to him (Ciza et al, 2019, p. 4)

While Raman spectroscopy is an effective tool for detecting illicit drugs, the weak intensity of Raman scattering can make it difficult to distinguish trace materials.

The current lack of testing and monitoring represents a significant vulnerability, and new methods are required to enable risk-based post-market surveillance. Due to the high variability of counterfeits, no single analytical method can identify all falsified medicines, which complicates the development of uniform guidelines on detection methods. In this way, the comparison of the functionality of the portable Raman spectroscopy technique with other techniques such as high-performance liquid chromatography (HPLC) and near-infrared spectroscopy (NIR), in parameters of precision, accuracy, repeatability and reproducibility, for the detection of the drug fentanyl and its analogues, affirms itHart et al., (2021) "Analytical methods for all available drugs are described in pharmacopoeias, which often involve techniques such as high-performance liquid chromatography (HPLC) or near-infrared spectroscopy (NIR), . These methods typically provide high sensitivity and selectivity, but require high-quality instruments, solvents, and expertise. This is hardly achievable for low- and middle-income countries (where the problem of FS drugs seems to be the greatest." (p. 2)

This systematic review addresses the problem, since as Lee et al., (2023) state "The prevalence of falsified medicines seems to be increasing and has not been slowed down by close cooperation between pharmaceutical companies, governments or international organizations interested in trade, health, customs and excise and counterfeiting." (p. 1).

That is why, "in 2012, WHO launched its Global Surveillance and Monitoring System (GSMS) for substandard and falsified medicines, with the aim of improving the quality of reporting, the use of data to inform the market and the development of regulatory capacity." (Mahmoudi et al., 2024, p. 2)

Fentanyl and its analogues have been at the center of the opioid epidemic. A major element in the opioid crisis is the growing number of clandestine fentanyl labs being reported by law enforcement agencies. This in turn generates what was demonstrated by Montastruc et al., (2021) "Several studies have underlined the importance of adverse drug reactions (ADRs) in terms of public health. According to the main studies carried out in the late 90s and the early years of the twenty-first century, it is reported that ADRs are the most common cause of hospital admission and the fourth or sixth leading cause of death" (p. 1).

"The main causes of the prevalence of falsified and substandard medicines are the absence of surveillance and control by government authorities; a lack of awareness of the dangers of fake and fraudulent medicines, especially on the part of pharmacists and patients; the online sale of counterfeit medicines; and the economic and political situation of the country." (Mozayad, et al., 2024, p. 2)

The risks posed by fentanyl and its analogues extend beyond health outcomes.

"Poor quality medicines generate higher costs for patients and the health system. Some of these costs, such as resources wasted on ineffective therapies and treating additional complications, are borne primarily by consumers and healthcare facilities. Others, such as the decline in economic productivity resulting from prolonged illness, reduced sales and tax revenues, and the costs of anti-counterfeiting initiatives

are assumed by governments, companies, the pharmaceutical industry, donors and society as a whole." (Ozawa et al., 2018, p. 2)

This approach can be strengthened by employing standardized terminology to prioritize the monitoring of suspected poor-quality drugs that are frequently reported for risk-based sampling and testing within the supply chain. This is stated by Toroitich et al., (2024) "Poor quality, substandard quality and falsified medicines pose a significant threat to public health, particularly in low- and middle-income countries." (p.1).

Likewise, in order to quantify active pharmaceutical ingredients (APIs) and formulation accuracy within authentic, counterfeit, and substandard simulated drugs, one can infer what Wang et al., (2019) indicates: "Portable, non-destructive detection devices can assist regulatory authorities in their defense against the spread of SF drugs. Vibrational spectroscopy is an ideal candidate because of its ease and sampling rate." (p. 1)

Finally, the portable Raman spectral technique for monitoring fraudulent activities of the drug fentanyl and its analogues, was shown to detect counterfeit products as long as a consistent spectrum of the assured quality is available.

According to (Wilson, 2017, p. 5) the portable Raman spectral technique and the NIRS technique showed potential to detect hundreds of drugs with insufficient concentration and could therefore be used together to identify drugs of inferior quality.

Conclusions

Data extraction

For data extraction, followed by specific and organized criteria. First, the eligibility criteria were defined, such as the range of years, language and publication status, justifying each one based on the objectives of the review. The sources of information used were also detailed, including databases, search periods and date of the last search, as well as the complete search strategy, keywords and limits applied. The evidence selection process was described in terms of screening and eligibility, and the method of data extraction will be documented, using independent confirmation to reduce biases. The variables of interest were defined, the assumptions made where it will be explained if a critical assessment of the studies will be carried out, indicating the evaluation methods. Finally, the methods of synthesis of results were described to summarize and present the findings in a coherent and objective manner. Standardized data extraction tools promote the extraction of similar data across all included studies and are required for JBI systematic reviews. The protocol details what data the reviewers plan to extract from the included studies and the data extraction tool must be attached to the protocol (Aromataris, 2020).

Artificial Intelligence Usage Statement

The authors declare that they have not used artificial intelligence (AI) tools in the creation of this article

Conflict of Interest

The authors declare that they have no conflict of interest

“this research has been funded by dirección General de Investigaciones of Universidad Santiago de Cali under call No. 01-2025”

https://www.mediresonline.org/journals/pharmacy-and-drug-development

https://www.mediresonline.org/journals/pharmacy-and-drug-development/article/detection-of-fentanyl-and-its-analogues-using-portable-raman-spectroscopy-in-the-monitoring-of-fraudulent-activities-systematic-review

References

  1. Ali, V. E., Asika, M. O., Elebesunu, E. E., Agbo, C., & Antwi, M. H. (2024). Cognizance and mitigation of falsified immunization documentation: Analyzing the consequences for public health in Nigeria, with a focus on counterfeited COVID‐19 vaccination cards: A case report. Health Science Reports, 7(2), e1885.
  2. Arjun, E., Chhabra, P., & Singh, P. (2024). Forensic Aspects of Mass Spectroscopy and Isotope Ratio Mass Spectroscopy. Advances in Analytical Techniques for Forensic Investigation, 149-187.
  3. Aromataris, E., & Munn, Z. (Eds.). (2020). JBI manual for evidence synthesis. Jbi.
  4. Awotunde, O., Roseboom, N., Cai, J., Hayes, K., Rajane, R., Chen, R., ... & Lieberman, M. (2022). Discrimination of substandard and falsified formulations from genuine pharmaceuticals using NIR spectra and machine learning. Analytical Chemistry, 94(37), 12586-12594.
  5. Budnitz, D. S., Shehab, N., Lovegrove, M. C., Geller, A. I., Lind, J. N., & Pollock, D. A. (2021). US emergency department visits attributed to medication harms, 2017-2019. Jama, 326(13), 1299-1309.
  6. Chen, H., Lin, Z., & Tan, C. (2018). Nondestructive discrimination of pharmaceutical preparations using near-infrared spectroscopy and partial least-squares discriminant analysis. Analytical Letters, 51(4), 564-574.
  7. Chen, H., Lin, Z., & Tan, C. (2020). Application of near-infrared spectroscopy and class-modeling to antibiotic authentication. Analytical biochemistry, 590, 113514.
  8. Ciza, P. H., Sacre, P. Y., Waffo, C., Coïc, L., Avohou, H., Mbinze, J. K., ... & Ziemons, E. (2019). Comparing the qualitative performances of handheld NIR and Raman spectrophotometers for the detection of falsified pharmaceutical products. Talanta, 202, 469-478.
  9. Clarke, R., Bharucha, T., Arman, B. Y., Gangadharan, B., Gomez Fernandez, L., Mosca, S., ... & McCullagh, J. S. (2024). Using matrix assisted laser desorption ionisation mass spectrometry combined with machine learning for vaccine authenticity screening. npj Vaccines, 9(1), 155.
  10. Crocombe, R. A., Giuntini, G., Schiering, D. W., Profeta, L. T., Hargreaves, M. D., Leary, P. E., ... & Chmura, J. W. (2023). Field‐portable detection of fentanyl and its analogs: A review. Journal of forensic sciences, 68(5), 1570-1600.
  11. Cronin, M. A., & George, E. (2023). The why and how of the integrative review. Organizational Research Methods, 26(1), 168-192.
  12. Cui, P., Zhao, J., Liu, M., Qi, M., Wang, Q., Li, Z., ... & Li, G. (2021). Non-invasive detection of medicines and edible products by direct measurement through vials using near-infrared spectroscopy: A review. Infrared Physics & Technology, 115, 103687.
  13. Erkok, S. D., Gallois, R., Leegwater, L., Gonzalez, P. C., van Asten, A., & McCord, B. (2024). Combining Surface-Enhanced Raman Spectroscopy (SERS) and Paper Spray Mass Spectrometry (PS-MS) for Illicit Drug Detection. Talanta, 126414.
  14. Duan, D., Long, C., & Zhang, H. (2024). An authentic assessment method for cordyceps sinensis. Journal of Pharmaceutical and Biomedical Analysis, 239, 115879.
  15. Feeney, A. J., Goad, J. A., & Flaherty, G. T. (2024). Global Perspective of the Risks of Falsified and Counterfeit Medicines: A Critical Review of the Literature. Travel Medicine and Infectious Disease, 102758.
  16. Gozdzialski, L., Rowley, A., Borden, S. A., Saatchi, A., Gill, C. G., Wallace, B., & Hore, D. K. (2022). Rapid and accurate etizolam detection using surface-enhanced Raman spectroscopy for community drug checking. International Journal of Drug Policy, 102, 103611.
  17. Guillemain, A., Dégardin, K., & Roggo, Y. (2017). Performance of NIR handheld spectrometers for the detection of counterfeit tablets. Talanta, 165, 632-640.
  18. Haddad, A., Comanescu, M. A., Green, O., Kubic, T. A., & Lombardi, J. R. (2018). Detection and quantitation of trace fentanyl in heroin by surface-enhanced Raman spectroscopy. Analytical Chemistry, 90(21), 12678-12685.
  19. Bakker, I. M., Ohana, D., & Venhuis, B. J. (2021). Current challenges in the detection and analysis of falsified medicines. Journal of Pharmaceutical and Biomedical Analysis, 197, 113948.
  20. Hattori, Y., Seko, Y., Peerapattana, J., Otsuka, K., Sakamoto, T., & Otsuka, M. (2018). Rapid identification of oral solid dosage forms of counterfeit pharmaceuticals by discrimination using near-infrared spectroscopy. Bio-Medical Materials and Engineering, 29(1), 1-14.
  21. Velásquez, D. G. D. L. S., Patiño, A. R., Jaime, B. P. V., Arturo, L., & Sandoval, V. Publicación.
  22. Kimani, M. M., Kern, S., Lanzarotta, A., Thatcher, M., Lorenz, L. M., Smith, S. W., ... & Wetherby Jr, A. E. (2023). Rapid screening of 2‐benzylbenzimidazole nitazene analogs in suspect counterfeit tablets using Raman, SERS, DART‐TD‐MS, and FT‐IR. Drug Testing and Analysis, 15(5), 539-550.
  23. Lee, J., Park, S., & Kim, M. (2023). The global threat of counterfeit pharmaceuticals: A systematic review. Journal of Pharmaceutical Sciences, 112(3), 567-582.
  24. Liu, P., Wang, J., Li, Q., Gao, J., Tan, X., & Bian, X. (2019). Rapid identification and quantification of Panax notoginseng with its adulterants by near infrared spectroscopy combined with chemometrics. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 206, 23-30.
  25. Ma, Q., Li, T., Liu, Y., Chai, J., Xu, Z., Liu, A., ... & Gao, L. (2024). Experimental study on the detection of Gastrodia elata by enzymatic recombinase amplification and immunochromatography. Analytical Biochemistry, 694, 115618-115618.
  26. Mahmoudi Meymand, F., Takian, A., & Jaafaripooyan, E. (2024). The challenges associated with the prevention of smuggling and counterfeiting health goods in Iran. BMC Public Health, 24(1), 1564.
  27. Marshall-Webb, M., Peters, M. D., Bright, T., & Watson, D. I. (2018). Effectiveness of Nissen fundoplication versus anterior and posterior partial fundoplications for treatment of gastro-esophageal reflux disease: a systematic review protocol. JBI Evidence Synthesis, 16(5), 1095-1102.
  28. Masterson, A. N., Hati, S., Ren, G., Liyanage, T., Manicke, N. E., Goodpaster, J. V., & Sardar, R. (2021). Enhancing nonfouling and sensitivity of surface-enhanced Raman scattering substrates for potent drug analysis in blood plasma via fabrication of a flexible plasmonic patch. Analytical Chemistry, 93(4), 2578-2588.
  29. Minh, D. T. C., Nhu, N. T. Q., Lan, D. T. N., Anh, N. T. K., & Ha, P. T. T. (2024). HPTLC sequentially coupled to UV and SERS: A cost-effective tool for confirmative identification and quantitation of sildenafil in falsified herbal products. Journal of Pharmaceutical and Biomedical Analysis, 251, 116392.
  30. Mirsafavi, R., Moskovits, M., & Meinhart, C. (2020). Detection and classification of fentanyl and its precursors by surface-enhanced Raman spectroscopy. Analyst, 145(9), 3440-3446
  31. Mishra, R., Ramesh, D., Mohammad, N., & Mondal, B. (2024). Blockchain enabled secure pharmaceutical supply chain framework with traceability: An efficient searchable pharmachain approach. Cluster Computing, 27(10), 13621-13641.
  32. Montastruc, J. L., Lafaurie, M., de Canecaude, C., Durrieu, G., Sommet, A., Montastruc, F., & Bagheri, H. (2021). Fatal adverse drug reactions: A worldwide perspective in the World Health Organization pharmacovigilance database. British journal of clinical pharmacology, 87(11), 4334-4340.
  33. Mozayad, A. N., Fouad, M. A., & Elkady, E. F. (2024). Utilizing experimental design and desirability function in optimizing RP-HPLC method for simultaneous determination of some skeletal muscle relaxants and analgesics. Scientific Reports, 14(1), 10360
  34. Laing, S. K., Bessias, S., Ozawa, S., Herrington, J. E., Haynie, D. G., Evans, D. R., & Yemeke, T. T. (2018). Prevalence of Substandard and Falsified Essential Medicines. JAMA Network Open, 1, e181685.
  35. Palamar, J. J., Fitzgerald, N. D., Goldberger, B. A., & Cottler, L. B. (2024). Monitoring illicit pentobarbital availability in the United States: A National Drug Early Warning System briefing. Drug and Alcohol Dependence, 263, 112402.
  36. Authority, P. S. (2022). December 2022-Printed Issue. PATIENT SAFETY, 4(4)
  37. Qin, Y., Yin, S., Chen, M., Yao, W., & He, Y. (2023). Surface-enhanced Raman spectroscopy for detection of fentanyl and its analogs by using Ag-Au nanoparticles. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 285, 121923.
  38. Qin, Y., Yin, S., Chen, M., Yao, W., & He, Y. (2023). Surface-enhanced Raman spectroscopy for detection of fentanyl and its analogs by using Ag-Au nanoparticles. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 285, 121923.
  39. Rahman, M. S., Yoshida, N., Tsuboi, H., Tomizu, N., Endo, J., Miyu, O., ... & Kimura, K. (2018). The health consequences of falsified medicines‐a study of the published literature. Tropical Medicine & International Health, 23(12), 1294-1303.
  40. Rodionova, O. Y., Balyklova, K. S., Titova, A. V., & Pomerantsev, A. L. (2018). Application of NIR spectroscopy and chemometrics for revealing of the ‘high quality fakes’ among the medicines. Forensic Chemistry, 8, 82-89.
  41. Said, M. M., Gibbons, S., Moffat, A., & Zloh, M. (2019). Use of near infrared spectroscopy and spectral databases to assess the quality of pharmaceutical products and aid characterization of unknown components. Journal of Near Infrared Spectroscopy, 27(5), 379-390.
  42. Salami, R. K., de Almeida, S. V., Gheorghe, A., Njenga, S., Silva, W., & Hauck, K. (2023). Health, economic, and social impacts of substandard and falsified medicines in low-and middle-income countries: a systematic review of methodological approaches. The American Journal of Tropical Medicine and Hygiene, 109(2), 228.
  43. Schram, J., Parrilla, M., Sleegers, N., Slosse, A., Van Durme, F., van Nuijs, A. L., & De Wael, K. (2024). Electrochemical classification of benzodiazepines: A comprehensive approach combining insights from voltammetry and liquid chromatography− mass spectrometry. Talanta, 279, 126623.
  44. Siddaway, A. P., Wood, A. M., & Hedges, L. V. (2019). How to do a systematic review: a best practice guide for conducting and reporting narrative reviews, meta-analyses, and meta-syntheses. Annual review of psychology, 70(1), 747-770.
  45. Lavallais, K. L. (2024). Factors Affecting the Quality of Reporting Dispensing Errors Among Pharmacists (Doctoral dissertation, Walden University).
  46. Toroitich, A. M., Armitage, R., & Tanna, S. (2024). Suspected poor-quality medicines in Kenya: a retrospective descriptive study of medicine quality-related complaints reports in Kenya’s pharmacovigilance database. BMC Public Health, 24(1), 2561.
  47. Usman, A. G., Ghali, U. M., & Selin, I. Ş. I. K. (2020). Applications of miniaturized and portable near infrared (NIR), Fourier transform infrared (FT-IR) and Raman spectrometers for the inspection and control of pharmaceutical products. Journal of Faculty of Pharmacy of Ankara University, 44(1), 188-203.
  48. Vera Carrasco, Oscar. (2019). COUNTERFEIT MEDICINES: AN EXTREMELY SERIOUS RISK TO PUBLIC HEALTH. Revista Médica La Paz, 25(1), 94- 102. Recovered in 23 of November of 2024,
  49. rui Wang, X., ting Zhang, J., guang Jing, W., hua Li, M., han Guo, X., long Cheng, X., & Wei, F. (2024). Digital identification and adulteration analysis of Pulsatilla Radix and Pulsatilla Cernua based on “digital identity” and UHPLC-QTOF-MSE. Journal of Chromatography B, 1244, 124257.
  50. Wang, W., Keller, M. D., Baughman, T., & Wilson, B. K. (2020). Evaluating low-cost optical spectrometers for the detection of simulated substandard and falsified medicines. Applied spectroscopy, 74(3), 323-333.
  51. Wang, X. R., Zhang, J. T., He, F., Fu, R., Jing, W. G., Guo, X., ... & Wei, F. (2024). Identification Analysis of Angelicae sinensis radix and Angelicae pubescentis radix Based on Quantized “Digital Identity” and UHPLC-QTOF-MSE Analysis. Journal of the American Society for Mass Spectrometry, 35(9), 2222-2229.
  52. Weiss, A. J., Freeman, W. J., Heslin, K. C., & Barrett, M. L. (2018). Adverse drug events in US hospitals, 2010 versus 2014. HCUP statistical brief, 234.
  53. Wilcox, P. G., Emmons, E. D., Pardoe, I. J., Kline, N. D., & Guicheteau, J. A. (2023). Quantitative Raman cross-sections and band assignments for fentanyl and fentanyl analogs. Applied Spectroscopy, 77(5), 439-448.
  54. Wilson, B. K., Kaur, H., Allan, E. L., Lozama, A., & Bell, D. (2017). A new handheld device for the detection of falsified medicines: demonstration on falsified artemisinin-based therapies from the field. The American journal of tropical medicine and hygiene, 96(5), 1117.
  55. Worku, M. C., Mitku, M. L., Ayenew, W., Limenh, L. W., Ergena, A. E., Geremew, D. T., ... & Anagaw, Y. K. (2024). Assessment of knowledge, attitude, and practice on substandard and counterfeit pharmaceutical products among pharmacy professionals in Gondar City, North-West Ethiopia. Currents in Pharmacy Teaching and Learning, 16(10), 102140.

Become an Editorial Board Member

Become a Reviewer

What our clients say

MEDIRES PUBLISHING

At our organization, we prioritize excellence in supporting the endeavors of researchers and practitioners alike. With a commitment to inclusivity and diversity, our journals eagerly accept various article types, including but not limited to Research Papers, Review Articles, Short Communications, Case Reports, Mini-Reviews, Opinions, and Letters to the Editor.

This approach ensures a rich tapestry of scholarly contributions, fostering an environment ripe for intellectual exchange and advancement."

Contact Info

MEDIRES PUBLISHING LLC,
447 Broadway, 2nd Floor, Suite #1734,
New York, 10013, United States.
Phone: +1-(302)-231-2656
Email: info@mediresonline.org