The problem of different cannabis laboratories obtaining different results on the same samples, inter-laboratory variation, has been studied extensively. One of the causes of the problem is different laboratories prepare their samples differently. Another issue is how varying amounts of moisture in plant material can impact potency measurements. Ideas on how to improve the situation are given.
3. Extraction Solvent
Standardizing the solvent used to extract samples is a no-brainer. Chemistry 101 tells us that the same solutes dissolve in different solvents at different rates and in different amounts. I have seen methanol, ethanol, isopropanol, and chlorinated solvents used to extract cannabis samples. These extracts will vary in composition when applied to the same sample because of the variation in properties of these solvents. The industry needs to standardize this.
4. Varying Amounts
I have seen different laboratories use anywhere from 1–5 g of sample in an extraction. I have also seen variable amounts of extraction solvent used, from a few to many milliliters. Of course this affects the composition of the analytes extracted from a material. The more sample used, the more will be extracted. The more solvent perhaps the more efficient the extraction, but the analyte concentrations will vary with the amount of solvent used.
5. Mixing and Vortexing
Once the sample and extraction solvent are in intimate contact in a sample vial, they must be stirred up and mixed together via some mechanism. I have seen people shake vials, use vortexers, shakers, mixers, and other contraptions. The variables here are the size and shape of the container, the amount of sample and solvent, and the time and manner of mixing. The amount of time spent and the manner in which mixing occurs will affect the efficiency of the analyte extraction.
When extracting plant material, it must be filtered before proceeding with analyzing the extraction obtained from the sample. Depending upon how the solution is filtered analytes may be left behind on the filtration medium. This can be confirmed by filtering an extract, and then passing pure solvent through the filtration medium and analyzing it for the analytes. When filtering the extract is often open to the environment. Different amounts of solvent may evaporate from different samples during filtration, further adding concentration variation to the results.
For chromatographic analyses some samples may be too concentrated to be analyzed and need to be diluted before analysis. This is particularly true of samples high in cannabinoids, such as extracts and distillates. At times dilution factors of 100 or more may be needed. This means that volume measurement error of less than a drop can have a huge impact on results. Laboratories vary in how they dilute and how much they dilute contributing to the inter-laboratory variation problem.
8. Variation in Extraction Efficiency and Not Extracting to Exhaustion
For any extraction technique to be accurate it should pull out all of the analytes in a sample not just a fraction. Even if your extraction technique gets reproducible numbers, it will not compare to other laboratories who may pull out more or less of an analyte from the same sample because of variations in extraction efficiency. This variation is caused by the variables discussed above. The solution to this problem is for all laboratories to extract to exhaustion to make sure all the analyte is extracted from all samples. This means performing studies by extracting the same samples over and over again and measuring analyte concentrations until they reach zero. Then, a method needs to be developed for all samples to insure all analytes are extracted all the time. If all laboratories extracted to exhaustion they would each pull the same amount of analytes from the same samples, and much of the inter-laboratory variation problem would go away.
9. Human Error
As we have seen, the extraction methods for preparing samples for chromatography involve a significant amount of manual sample preparation. Being who we are, human beings are bound to make mistakes when preparing samples, which contributes to the inter-laboratory variation problem. The solution to this problem is better training, or use of analytical methods that require less manual sample preparation (13).
- B.C. Smith, Cannabis Science and Technology 2(2), 12–17 (2019).
- B.C. Smith, Cannabis Science and Technology 2(3), 10–14 (2019).
- M.O. Bonn-Miller, M.J.E. Loflin, B.F. Thomas, J.P. Marcu, T. Hyke, and R. Vandrey, JAMA, J. Am. Med. Assoc. 318, 1708 (2017).
- B. Young, The Seattle Times, January 5, 2016. https://www.seattletimes.com/seattle-news/marijuana/some-pot-labs-in-state-failed-no-pot-at-all-says-scientist/.
- L. Wagner, M. Bott, M. Villarreal, and M. Horn, NBC Bay Area, November 16, 2017, https://www.nbcbayarea.com/investigations/Industry-Insiders-Warn-of-Fraud-at-Marijuana-Testing-Labs-458125743.html?_osource=SocialFlowFB_BAYBrand.
- B.C. Smith, P. Lessard, and R. Pearson, Cannabis Science and Technology 2(1), 48–53 (2019).
- California Bureau of Cannabis Control Regulations, Section 5719.
- 115th United States Congress, Senate Bill S.2667, ”Hemp Farming Act of 2018.”
- B.C. Smith, Cannabis Science and Technology 1(4), 12–16 (2018).
- M. Giese, M. Lewis, L. Giese, and K. Smith, J. AOAC Int. 98(6), 1503–1522 (2015).
- B. Smith, M. Giese, and M. Lewis, unpublished results.
- B.C. Smith, Cannabis Science and Technology 2(6), 28–33 (2019).
About the Columnist
Brian C. Smith, PhD, is Founder, CEO, and Chief Technical Officer of Big Sur Scientific in Capitola, California. Dr. Smith has more than 40 years of experience as an industrial analytical chemist having worked for such companies as Xeros, IBM, Waters Associates, and Princeton Instruments. For 20 years he ran Spectros Associates, an analytical chemistry training and consulting firm where he improved their chemical analyses. Dr. Smith has written three books on infrared spectroscopy, and earned a PhD in physical chemistry from Dartmouth College.
How to Cite this Article
B.C. Smith, Cannabis Science and Technology 3(2), 10–15 (2020).