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extractiongraphic

The Four Pillars of Cannabis Processing

By Christian Sweeney
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extractiongraphic

Cannabis extraction has been used as a broad term for what can best be described as cannabis processing. A well-thought-out cannabis process goes far beyond just extraction, largely overlapping with cultivation on the front-end and product development on the back-end1. With this in mind, four pillars emerge as crucial capabilities for developing a cannabis process: Cultivation, Extraction, Analytics and Biochemistry.

The purpose and value of each pillar on their own is clear, but it is only when combined that each pillar can be optimized to provide their full capacities in a well-designed process. As such, it is best to define the goals of each pillar alone, and then explain how they synergize with each other.

At the intersection of each pillar, specific technology platforms exist that can effectively drive an innovation and discovery cycle towards the development of ideal products.Cultivation is the foundation of any horticultural process, including cannabis production. Whether the goal be to convert pigments, flavors or bioactive compounds into a usable form, a natural process should only utilize what is provided by the raw material, in this case cannabis flower. That means cultivation offers a molecular feedstock for our process, and depending on our end goals there are many requirements we may consider. These requirements start as simply as mass yield. Various metrics that can be used here include mass yield per square foot or per light. Taken further, this yield may be expressed based not only on mass, but the cannabinoid content of the plants grown. This could give rise to a metric like CBD or THC yield per square foot and may be more representative of a successful grow. Furthermore, as scientists work to learn more about how individual cannabinoids and their combinations interact with the human body, cultivators will prioritize identifying cultivars that provide unique ratios of cannabinoids and other bioactive compounds consistently. Research into the synergistic effect of terpenes with cannabinoids suggests that terpene content should be another goal of cultivation2. Finally, and most importantly, it is crucial that cultivation provide clean and safe materials downstream. This means cannabis flower free of pesticides, microbial growth, heavy metals and other contaminants.

Extraction is best described as the conversion of target molecules in cannabis raw material to a usable form. Which molecules those are depends on the goals of your product. This ranges from an extract containing only a pure, isolated cannabinoid like CBD, to an extract containing more than 100 cannabinoids and terpenes in a predictable ratio. There are countless approaches to take in terms of equipment and process optimization in this space so it is paramount to identify which is the best fit for the end-product1. While each extraction process has unique pros and cons, the tunability of supercritical carbon dioxide provides a flexibility in extraction capabilities unlike any other method. This allows the operator to use a single extractor to create extracts that meet the needs of various product applications.

Analytics provide a feedback loop at every stage of cannabis production. Analytics may include gas chromatography methods for terpene content3 or liquid chromatography methods for cannabinoids 3, 4, 5. Analytical methods should be specific, precise and accurate. In an ideal world, they can identify the compounds and their concentrations in a cannabis product. Analytics are a pillar of their own due simply to the efforts required to ensure the quality and reliability of results provided as well as ongoing optimization of methods to provide more sensitive and useful results. That said, analytics are only truly harnessed when paired with the other three pillars.

extractiongraphic
Figure 1: When harnessed together the pillars of cannabis processing provide platforms of research and investigation that drive the development of world class products.

Biochemistry can be split into two primary focuses. Plant biochemistry focuses back towards cultivation and enables a cannabis scientist to understand the complicated pathways that give rise to unique ratios of bioactive molecules in the plant. Human biochemistry centers on how those bioactive molecules interact with the human endocannabinoid system, as well as how different routes of administration may affect the pharmacokinetic delivery of those active molecules.

Each of the pillars require technical expertise and resources to build, but once established they can be a source of constant innovation. Fig. 1 above shows how each of these pillars are connected. At the intersection of each pillar, specific technology platforms exist that can effectively drive an innovation and discovery cycle towards the development of ideal products.

For example, at the intersection of analytics and cultivation I can develop raw material specifications. This sorely needed quality measure could ensure consistencies in things like cannabinoid content and terpene profiles, more critically they can ensure that the raw material to be processed is free of contamination. Additionally, analytics can provide feedback as I adjust variables in my extraction process resulting in optimized methods. Without analytics I am forced to use very rudimentary methods, such as mass yield, to monitor my process. Mass alone tells me how much crude oil is extracted, but says nothing about the purity or efficiency of my extraction process. By applying plant biochemistry to my cultivation through the use of analytics I could start hunting for specific phenotypes within cultivars that provide elevated levels of specific cannabinoids like CBC or THCV. Taken further, technologies like tissue culturing could rapidly iterate this hunting process6. Certainly, one of the most compelling aspects of cannabinoid therapeutics is the ability to harness the unique polypharmacology of various cannabis cultivars where multiple bioactive compounds are acting on multiple targets7. To eschew the more traditional “silver bullet” pharmaceutical approach a firm understanding of both human and plant biochemistry tied directly to well characterized and consistently processed extracts is required. When all of these pillars are joined effectively we can fully characterize our unique cannabis raw material with targeted cannabinoid and terpene ratios, optimize an extraction process to ensure no loss of desirable bioactive compounds, compare our extracted product back to its source and ensure we are delivering a safe, consistent, “nature identical” extract to use in products with predictable efficacies.

Using these tools, we can confidently set about the task of processing safe, reliable and well characterized cannabis extracts for the development of world class products.


[1] Sweeney, C. “Goal-Oriented Extraction Processes.” Cannabis Science and Technology, vol 1, 2018, pp 54-57.

[2] Russo, E. B. “Taming THC: potential cannabis synergy and phytocannabinoid-terpenoid entourage effects.” British Journal of Pharmacology, vol. 163, no. 7, 2011, pp. 1344–1364.

[3] Giese, Matthew W., et al. “Method for the Analysis of Cannabinoids and Terpenes in Cannabis.” Journal of AOAC International, vol. 98, no. 6, 2015, pp. 1503–1522.

[4] Gul W., et al. “Determination of 11 Cannabinoids in Biomass and Extracts of Different Varieties of Cannabis Using high-Performance Liquid Chromatography.” Journal of AOAC International, vol. 98, 2015, pp. 1523-1528.

[5] Mudge, E. M., et al. “Leaner and Greener Analysis of Cannabinoids.” Analytical and Bioanalytical Chemistry, vol. 409, 2017, pp. 3153-3163.

[6] Biros, A. G., Jones, H. “Applications for Tissue Culture in Cannabis Growing: Part 1.” Cannabis Industry Journal, 13 Apr. 2017, www.cannabisindustryjournal.com/feature_article/applications-for-tissue-culture-in-cannabis-growing-part-1/.

[7] Brodie, James S., et al. “Polypharmacology Shakes Hands with Complex Aetiopathology.” Trends in Pharmacological Sciences, vol. 36, no. 12, 2015, pp. 802–821.

The Practical Chemist

Building the Foundation of Medical Cannabis Testing – Understanding the Use of Standards and Reference Materials – Part 1

By Joe Konschnik
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In previous articles, you may recall that Amanda Rigdon, one our contributing authors, stated that instrument calibration is the foundation of all data quality. In this article, I would like to expand on that salient point. A properly calibrated instrument will, in fact, produce reliable data. It is the foundation we build our data upon. All foundations are comprised of building blocks, and our laboratory is no exception. If we take this analogy further, the keystone to the laboratory foundation, the stone that all data relies upon, is the analytical reference material. Proper calibration means that it is based on a true, accurate value. That is what the reference material provides. In this article, I would like to expand on the use and types of reference materials in analytical testing.

To develop sound analytical data, it is important to understand the significance of reference materials and how they are properly used. The proper selection and use of reference materials ensures the analytical certainty, traceability and comparability necessary to produce scientifically sound data. First, let’s take a moment to define the types of commonly used reference materials. According to the International Vocabulary of Metrology (VIM), a Reference Standard (RS) is something that is reused to measure against, like a balance or a set of weights. A Reference Material (RM) is a generic term. It is described as something that is prepared using a RS that is homogeneous, stable and is consumed during its use for measurement. An example of an RM is the solutions used to construct a calibration curve, often referred to as calibration standards, on your GC or LC. Due to the current state of cannabis testing, reference materials can be hard to find and, even more critical, variable in their accuracy to a known reference standard. Sometimes this is not critical, but when quantifying an unknown, it is paramount.

RMs can be either quantitative or qualitative. Qualitative RMs verify the identity and purity of a compound. Quantitative RMs, on the other hand, provide a known concentration, or mass, telling us not only what is present, and its purity, but also how much. This is typically documented on the certificate that accompanies the reference material, which is provided by the producer or manufacturer. The certificate describes all of the properties of the starting materials and steps taken to prepare the RM. For testing requirements, like potency, pesticides, etc., where quantitation is expected, it is important to use properly certified quantitative RMs.

Now, the pinnacle of reference materials is the Certified Reference Material (CRM). VIM defines a Certified Reference Material (CRM) as an RM accompanied by documentation issued by an authoritative body and provides one or more specified property values, with associated uncertainties and traceability using valid procedures. A CRM is generally recognized as providing the highest level of traceability and accuracy to a measurement – the strongest keystone you can get for your foundation. It is also important to recognize that the existence of a certificate does not make a reference material a CRM. It is the process used in manufacturing that makes it a CRM, and these are typically accreditations earned by specific manufacturers who have invested on this level of detail.

Now that we understand the types of reference materials we can choose, in the next article of this series we will describe what a CRM provider must do to ensure the material and how we can use them to develop reliable data. Without properly formulated and prepared CRMs, instrument calibration and the use of internal standards are less effective at ensuring the quality of your data.


If you have any questions please contact me, Joe Konschnik at (800) 356-1688 ext. 2002 by phone, or email me at joe.konschnik@restek.com.

The Practical Chemist

Calibration – The Foundation of Quality Data

By Amanda Rigdon
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This column is devoted to helping cannabis analytical labs generate valid data right now with a relatively small amount of additional work. The topic for this article is instrument calibration – truly the foundation of all quality data. Calibration is the basis for all measurement, and it is absolutely necessary for quantitative cannabis analyses including potency, residual solvents, terpenes, and pesticides.

Just like a simple alarm clock, all analytical instruments – no matter how high-tech – will not function properly unless they are calibrated. When we set our alarm clock to 6AM, that alarm clock will sound reproducibly every 24 hours when it reads 6AM, but unless we set the correct current time on the clock based on some known reference, we can’t be sure when exactly the alarm will sound. Analytical instruments are the same. Unless we calibrate the instrument’s signal (the response) from the detector to a known amount of reference material, the instrument will not generate an accurate or valid result.

Without calibration, our result may be reproducible – just like in our alarm clock example – but the result will have no meaning unless the result is calibrated against a known reference. Every instrument that makes a quantitative measurement must be calibrated in order for that measurement to be valid. Luckily, the principle for calibration of chromatographic instruments is the same regardless of detector or technique (GC or LC).

Before we get into the details, I would like to introduce one key concept:

Every calibration curve for chromatographic analyses is expressed in terms of response and concentration. For every detector the relationship between analyte (e.g. a compound we’re analyzing) concentration and response is expressible mathematically – often a linear relationship.

Now that we’ve introduced the key concept behind calibration, let’s talk about the two most common and applicable calibration options.

Single Point Calibration

This is the simplest calibration option. Essentially, we run one known reference concentration (the calibrator) and calculate our sample concentrations based on this single point. Using this method, our curve is defined by two points: our single reference point, and zero. That gives us a nice, straight line defining the relationship between our instrument response and our analyte concentration all the way from zero to infinity. If only things were this easy. There are two fatal flaws of single point calibrations:

  1. We assume a linear detector response across all possible concentrations
  2. We assume at any concentration greater than zero, our response will be greater than zero

Assumption #1 is never true, and assumption #2 is rarely true. Generally, single point calibration curves are used to conduct pass/fail tests where there is a maximum limit for analytes (i.e. residual solvents or pesticide screening). Usually, quantitative values are not reported based on single point calibrations. Instead, reports are generated in relation to our calibrator, which is prepared at a known concentration relating to a regulatory limit, or the instrument’s LOD. Using this calibration method, we can accurately report that the sample contains less than or greater than the regulatory limit of an analyte, but we cannot report exactly how much of the analyte is present. So how can we extend the accuracy range of a calibration curve in order to report quantitative values? The answer to this question brings us to the other common type of calibration curve.

Multi-Point Calibration:

A multi-point calibration curve is the most common type used for quantitative analyses (e.g. analyses where we report a number). This type of curve contains several calibrators (at least 3) prepared over a range of concentrations. This gives us a calibration curve (sometimes a line) defined by several known references, which more accurately expresses the response/concentration relationship of our detector for that analyte. When preparing a multi-point calibration curve, we must be sure to bracket the expected concentration range of our analytes of interest, because once our sample response values move outside the calibration range, the results calculated from the curve are not generally considered quantitative.

The figure below illustrates both kinds of calibration curves, as well as their usable accuracy range:

Calibration Figure 1

This article provides an overview of the two most commonly used types of calibration curves, and discusses how they can be appropriately used to report data. There are two other important topics that were not covered in this article concerning calibration curves: 1) how can we tell whether or not our calibration curve is ‘good’ and 2) calibrations aren’t permanent – instruments must be periodically re-calibrated. In my next article, I’ll cover these two topics to round out our general discussion of calibration – the basis for all measurement. If you have any questions about this article or would like further details on the topic presented here, please feel free to contact me at amanda.rigdon@restek.com.