If you’ve been manufacturing traditional food and beverages, you know the FDA has been regulating homogeneity for some time and even longer if you’ve been working in the pharma industry. So, it stands to reason that homogeneity is a regulated component of the cannabis industry.
However, making an accurately dosed edible is incredibly hard. Edible manufacturers not only have to make sure their products taste good, but they have to make a consistent, yet compliant, medicinal experience.
Colorado has recently updated the way laboratories calculate homogeneity and it could affect the pass/fail results of your production batch.
It all started in 2014…
When the Marijuana Enforcement Division set up the regulations for marijuana infused products, they wanted to make sure that the products consumers purchase are homogenous. Meaning, the infused ingredient is evenly distributed throughout the product, so if you ingest one piece of an edible, you will roughly get the same amount that is in another piece. The original regulation stated that there could be no more than 20% of an active ingredient in any 10% of the product. For example, if you have a 100mg chocolate bar with 10 pieces, one piece could not have more than 20mg.
2020 Regulatory Update
On January 1, 2020, the MED updated the regulations around homogeneity and how laboratories are required to test.
The new regs state:
- For Single Serving products:
A Production Batch of Medical or Retail Marijuana Product shall be considered homogenous if a minimum of a total of four servings from four individual single serve packaged units has a relative standard deviation of less than 10 percent for each Cannabinoid listed on the label.
- For Multi-Serving products:
A Production Batch of Medical or Retail Marijuana Product shall be considered homogenous if a minimum of four servings from two packaged units of a Test Batch has a relative standard deviation of less than 10 percent for each Cannabinoid listed on the label.
What is Relative Standard Deviation?
It’s time to hop in the wayback machine and go to senior year statistics class. Relative Standard Deviation (RSD) tells you whether the “regular” standard deviation is a small or large quantity when compared to the mean (average) for the data set.
For example, you might find in an experiment that the standard deviation is 0.1 and your mean is 4.4. Your RSD for this set of numbers is:
100 x 0.1 / |4.4| = 2.3%.
This result tells you that your standard deviation is 2.3% of the mean of 4.4, which is pretty small. In other words, the data is tightly clustered around the mean. On the other hand, if your percentage was large, say, 55% – this would indicate your data is more spread out.
How does this apply to Homogeneity Testing?
When we receive a test package that requires homogeneity testing, we will take 4 samplings and test those. If the RSD is over 10%, that means the data set is too far apart compared to the mean. As a result, the product isn’t considered to be homogenous and the test package fails.
We’re here to help!
If you’re not happy with your current lab and feel like you’re not getting the right scientific experience to make your business successful, contact us! You can call us at (720) 460-3489 or e-mail us at: firstname.lastname@example.org