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A Metabolomics and Big Data Approach to Cannabis Authenticity (Authentomics)

With the increasing accessibility of cannabis (Cannabis sativa L., also known as marijuana and hemp), its products are being developed as extracts for both recreational and therapeutic use. This has led to increased scrutiny by regulatory bodies, who aim to understand and regulate the complex chemis...

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Autores principales: Jadhav, Pramodkumar D., Shim, Youn Young, Paek, Ock Jin, Jeon, Jung-Tae, Park, Hyun-Je, Park, Ilbum, Park, Eui-Seong, Kim, Young Jun, Reaney, Martin J. T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10179091/
https://www.ncbi.nlm.nih.gov/pubmed/37175910
http://dx.doi.org/10.3390/ijms24098202
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author Jadhav, Pramodkumar D.
Shim, Youn Young
Paek, Ock Jin
Jeon, Jung-Tae
Park, Hyun-Je
Park, Ilbum
Park, Eui-Seong
Kim, Young Jun
Reaney, Martin J. T.
author_facet Jadhav, Pramodkumar D.
Shim, Youn Young
Paek, Ock Jin
Jeon, Jung-Tae
Park, Hyun-Je
Park, Ilbum
Park, Eui-Seong
Kim, Young Jun
Reaney, Martin J. T.
author_sort Jadhav, Pramodkumar D.
collection PubMed
description With the increasing accessibility of cannabis (Cannabis sativa L., also known as marijuana and hemp), its products are being developed as extracts for both recreational and therapeutic use. This has led to increased scrutiny by regulatory bodies, who aim to understand and regulate the complex chemistry of these products to ensure their safety and efficacy. Regulators use targeted analyses to track the concentration of key bioactive metabolites and potentially harmful contaminants, such as metals and other impurities. However, the metabolic complexity of cannabis metabolic pathways requires a more comprehensive approach. A non-targeted metabolomic analysis of cannabis products is necessary to generate data that can be used to determine their authenticity and efficacy. An authentomics approach, which involves combining the non-targeted analysis of new samples with big data comparisons to authenticated historic datasets, provides a robust method for verifying the quality of cannabis products. To meet International Organization for Standardization (ISO) standards, it is necessary to implement the authentomics platform technology and build an integrated database of cannabis analytical results. This study is the first to review the topic of the authentomics of cannabis and its potential to meet ISO standards.
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spelling pubmed-101790912023-05-13 A Metabolomics and Big Data Approach to Cannabis Authenticity (Authentomics) Jadhav, Pramodkumar D. Shim, Youn Young Paek, Ock Jin Jeon, Jung-Tae Park, Hyun-Je Park, Ilbum Park, Eui-Seong Kim, Young Jun Reaney, Martin J. T. Int J Mol Sci Review With the increasing accessibility of cannabis (Cannabis sativa L., also known as marijuana and hemp), its products are being developed as extracts for both recreational and therapeutic use. This has led to increased scrutiny by regulatory bodies, who aim to understand and regulate the complex chemistry of these products to ensure their safety and efficacy. Regulators use targeted analyses to track the concentration of key bioactive metabolites and potentially harmful contaminants, such as metals and other impurities. However, the metabolic complexity of cannabis metabolic pathways requires a more comprehensive approach. A non-targeted metabolomic analysis of cannabis products is necessary to generate data that can be used to determine their authenticity and efficacy. An authentomics approach, which involves combining the non-targeted analysis of new samples with big data comparisons to authenticated historic datasets, provides a robust method for verifying the quality of cannabis products. To meet International Organization for Standardization (ISO) standards, it is necessary to implement the authentomics platform technology and build an integrated database of cannabis analytical results. This study is the first to review the topic of the authentomics of cannabis and its potential to meet ISO standards. MDPI 2023-05-03 /pmc/articles/PMC10179091/ /pubmed/37175910 http://dx.doi.org/10.3390/ijms24098202 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Jadhav, Pramodkumar D.
Shim, Youn Young
Paek, Ock Jin
Jeon, Jung-Tae
Park, Hyun-Je
Park, Ilbum
Park, Eui-Seong
Kim, Young Jun
Reaney, Martin J. T.
A Metabolomics and Big Data Approach to Cannabis Authenticity (Authentomics)
title A Metabolomics and Big Data Approach to Cannabis Authenticity (Authentomics)
title_full A Metabolomics and Big Data Approach to Cannabis Authenticity (Authentomics)
title_fullStr A Metabolomics and Big Data Approach to Cannabis Authenticity (Authentomics)
title_full_unstemmed A Metabolomics and Big Data Approach to Cannabis Authenticity (Authentomics)
title_short A Metabolomics and Big Data Approach to Cannabis Authenticity (Authentomics)
title_sort metabolomics and big data approach to cannabis authenticity (authentomics)
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10179091/
https://www.ncbi.nlm.nih.gov/pubmed/37175910
http://dx.doi.org/10.3390/ijms24098202
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