Tag Archives: CBDA

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Quality From Canada

Near Infrared, GC and HPLC Applications in Cannabis Testing

By Tegan Adams, Michael Bertone
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When a cannabis sample is submitted to a lab for testing there is a four-step process that occurs before it is tested in the instrumentation on site:

  1. It is ground at a low temperature into a fine powder;
  2. A solution is added to the ground powder;
  3. An extraction is repeated 6 times to ensure all cannabinoids are transferred into a common solution to be used in testing instrumentation.
  4. Once the cannabinoid solution is extracted from the plant matter, it is analyzed using High Pressure Liquid Chromatograph (HPLC). HPLC is the key piece of instrumentation in cannabis potency testing procedures.

While there are many ways to test cannabis potency, HPLC is the most widely accepted and recognized testing instrumentation. Other instrument techniques include gas chromatography (GC) and thin layer chromatography (TLC). HPLC is preferred over GC because it does not apply heat in the testing process and cannabinoids can then be measured in their naturally occurring forms. Using a GC, heat is applied as part of the testing process and cannabinoids such as THCA or CBDA can change form, depending on the level of heat applied. CBDA and THCA have been observed to change form at as low as 40-50C. GC uses anywhere between 150-200C for its processes, and if using a GC, a change of compound form can occur. Using HPLC free of any high-heat environments, acidic (CBDA & THCA) and neutral cannabinoids (CBD, THC, CBG, CBN and others) can be differentiated in a sample for quantification purposes.

Near Infrared

Near infrared (NIR) has been used with cannabis for rapid identification of active pharmaceutical ingredients by measuring how much light different substances reflect. Cannabis is typically composed of 5-30% cannabinoids (mainly THC and CBD) and 5-15% water. Cannabinoid content can vary by over 5% (e.g. 13-18%) on a single plant, and even more if grown indoors. Multiple NIR measurements can be cost effective for R&D purposes. NIR does not use solvents and has a speed advantage of at least 50 times over traditional methods.

The main downfall of NIR techniques is that they are generally less accurate than HPLC or GC for potency analyses. NIR can be programmed to detect different compounds. To obtain accuracy in its detection methods, samples must be tested by HPLC on ongoing basis. 100 samples or more will provide enough information to improve an NIR software’s accuracy if it is programmed by the manufacturer or user using chemometrics. Chemometrics sorts through the often complex and broad overlapping NIR absorption.

Bands from the chemical, physical, and structural properties of all species present in a sample that influences the measured spectra. Any variation however of a strain tested or water quantity observed can affect the received results. Consistency is the key to obtaining precision with NIR equipment programming. The downfall of the NIR technique is that it must constantly be compared to HPLC data to ensure accuracy.

At Eurofins Experchem , our company works with bothHPLC and NIR equipment simultaneously for different cannabis testing purposes. Running both equipment simultaneously means we are able to continually monitor the accuracy of our NIR equipment as compared to our HPLC. If a company is using NIR alone however, it can be more difficult to maintain the equipment’s accuracy without on-going monitoring.

What about Terpenes?

Terpenes are the primary aromatic constituents of cannabis resin and essential oils. Terpene compounds vary in type and concentration among different genetic lineages of cannabis and have been shown to modulate and modify the therapeutic and psychoactive effects of cannabinoids. Terpenes can be analyzed using different methods including separation by GC or HPLC and identification by Mass Spectrometry. The high-heat environment for GC analysis can again cause problems in accuracy and interpretation of results for terpenes; high-heat environments can degrade terpenes and make them difficult to find in accurate form. We find HPLC is the best instrument to test for terpenes and can now test for six of the key terpene profiles including a-Pinene, Caryophyllene, Limonene, Myrcene, B-Pinene and Terpineol.

Quality Systems

Quality systems between different labs are never one and the same. Some labs are testing cannabis under good manufacturing practices (GMP), others follow ISO accreditation and some labs have no accreditation at all.

From a quality systems’ perspective some labs have zero or only one quality system employee(s). In a GMP lab, to meet the requirements of Health Canada and the FDA, our operations are staffed in a 1:4 quality assurance to analyst ratio. GMP labs have stringent quality standards that set them apart from other labs testing cannabis. Quality standards we work with include, but are not limited to: monthly internal blind audits, extensive GMP training, yearly exams and ongoing tests demonstrating competencies.

Maintaining and adhering to strict quality standards necessary for a Drug Establishment License for pharmaceutical testing ensures accuracy of results in cannabis testing otherwise difficult to find in the testing marketplace.

Important things to know about testing

  1. HPLC is the most recommended instrument used for product release in a regulated environment.
  2. NIR is the best instrument to use for monitoring growth and curing processes for R&D purposes, only if validated with an HPLC on an ongoing basis.
  3. Quality Systems between labs are different. Regardless of instrumentation used, if quality systems are not in place and maintained, integrity of results may be compromised.
  4. GMPs comprise 25% of our labour costs to our quality department. Quality systems necessary for a GMP environment include internal audits, out of specification investigations, qualification and maintenance of instruments, systems controls and stringent data integrity standards.

An Introduction to Cannabis Genetics, Part II

By Dr. CJ Schwartz
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Plants and animals have roughly 25,000 to 30,000 genes. The genes provide the information needed to make a protein, and proteins are the building blocks for all biological organisms. An ideal analogy is a blueprint (DNA) for an alternator (the protein) in a car (the plant). Proteins are the ‘parts’ for living things. Some proteins will work better than others, leading to visible differences that we call phenotypes.

geneticspaintedchromMany traits, and the genes controlling them, are of interest to the cannabis industry. For hemp seed oil, quality, quantity and content can be manipulated through breeding natural genetic variants. Hemp fibers are already some of the best in nature, due to their length and strength. Finding the genes and proteins responsible for elongating the fibers can allow for the breeding of hemp for even longer fibers. In cannabis, the two most popular genes are THCA and CBDA synthases. There are currently over 100 sequences of the THCAS/CBDAS genes, and many natural DNA variations are known. We can make a family tree using just the THCAS, gene data and identify ‘branches’ that result in high, low or intermediate THCA levels. Generally most of the DNA changes have little to no effect on the gene, but some of the changes can have profound effects.

In fact, CBDAS and THCAS are related, in other words, they have a common ancestor. At some point the gene went through changes that resulted in the protein producing CDBA, or THCA or both. This is further supported by the fact that certain CBDAS can produce some THCA, and vice-versa. Studies into the THCAS and CBDAS family are ongoing and extensive, with terpene synthase genes following close behind.

Identifying gene (genetic) variants and characterizing their biological function allows us to combine certain genes in specific combinations to maximize yield, but determining which genes are important (gene discovery) is the first step to utilizing marker-assisted breeding.

Gene Discovery & Manipulation

The term genetics is often misused in the cannabis industry. Genetics is actually “the study of heredity and the variation of inherited characteristics.” When people say they have good genetics, what they really mean is that they have good strains, presumably with good gene variants. When people begin to cross or stabilize strains, they are performing genetic manipulation.Slide1

A geneticist will observe or measure two strains of interest, for example a plant branching and myrcene production. The high-myrcene plant is tall and skinny with no branching, reducing the yield. Crossing the two strains will produce F1 hybrid seeds. In some cases, F1 hybrids create unique desirable phenotypes (synergy) and the breeder’s work is completed. More often, traits act additively, thus we would expect the F1 to be of medium branching and medium myrcene production, a value between that of the values recorded for the parents (additive). Crossing F1 plants will produce an F2 population. An F2 population is comprised of the genes from both parents all mixed up. In this case we would expect the F2 progeny to have many different phenotypes. In our example, 25% of the plants would branch like parent A, and 25% of the F2 plants will have high myrcene like parent B. To get a plant with good branching and high myrcene, we predict that 6.25% (25% x 25%) of the F2 plants would have the correct combination.

The above-described scenario is how geneticists assign gene function, or generally called gene discovery. When the gene for height or branching is identified, it can now be tracked at the DNA level versus the phenotype level. In the above example, 93.5% of your F2 plants can be discarded, there is no need to grow them all to maturity and measure all of their phenotypes.Slide1

The most widely used method for gene discovery using natural genetic variation is by quantitative trait loci mapping (QTL). For these types of experiments, hundreds of plants are grown, phenotyped and genotyped and the data is statistically analyzed for correlations between genes (genotype) and traits (phenotype; figure). For example, all high-myrcene F2 plants will have one gene in common responsible for high myrcene, while all the other genes in those F2 plants will be randomly distributed, thus explaining the need for robust statistics. In this scenario, a gene conferring increased myrcene production has been discovered and can now be incorporated into an efficient marker-assisted breeding program to rapidly increase myrcene production in other desirable strains.