Opinion: How data can raise confidence in cannabis mold testing methods

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Image of aspergillus in a testing lab petri dish.

(Photo by sinhyu/stock.adobe.com)

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Pat Bird

In 2023, more than 155 million Americans, nearly half the U.S. population, will live in one of the 39 states or Washington DC in which marijuana is legalized for medical use.

As demand for cannabis continues to trend upward, there’s been an increase of product cultivation to meet this growing demand, resulting in a correlating uptick in the volume of microbiology testing required to ensure product can be released into the market.

Cannabis is a high-maintenance, agricultural commodity with complex cultivation considerations.

If you’re involved in any part of the seed-to-sale process, you must anticipate that a portion of your product will fail state limits – the standard failure rate for the industry is 10%-20% of the product that is tested.

On the lookout for aspergillus

The most common cause of failure is high levels of fungal, or mold, contamination, specifically with a subset of aspergillus species, which is a known human pathogen.

The increase of the volume of testing in recent months has returned a corresponding rise of aspergillus detection among product sampling, resulting in a dangerous emerging narrative that the results are “false” positives, casting doubt on the validity of aspergillus testing methods as a whole.

The reality is that this false positive narrative is a mirage: Diagnostic data testing shows that the average positive detection rate for aspergillus maintains failure rates of 10%-20%, even as volume of testing increases.

The aspergillus mold is a primary focus for diagnostic testing in cannabis, as inhalation can cause infection – and even death – in immunocompromised or medical patients.

Aspergillus is everywhere and anywhere you go. The genus has more than 250 identified species and spores rapidly and easily dispersed through air, soil and water and, as a result, is highly present in the cannabis cultivation process.

Much of the current cannabis diagnostic testing conversation across the industry surrounds how the data collected can ensure confidence in testing methods and results while also providing a clear line of sight into process gaps that must be adjusted for.

Data tells the story

Diagnostic data collected from testing should tell a story that raises confidence in testing-method design and the validity of results.

If your failure rate is above 20%, this can likely be attributed to a gross failure of either the testing methodology or a significant breach of sanitary conditions in production.

In evaluating your testing methodology, the most important considerations include:

• Fit for purpose: There is a growing number of diagnostic testing solutions on the market as cannabis production fails.

Sometimes, even state-level remediation efforts allow for labs to retest samples on a different application, which can lead to result discrepancies.

It’s important for you to ensure that your testing method has been fit for purpose and designed for your specific lab – otherwise, you’re getting skewed results.

To explain this further – and with a cooking analogy – a deep oil fryer and air fryer return similar results in the kitchen, but the methodology in which they cook is different, requiring unique adjustments between these appliances to ensure a similar, but not exact, outcome.

This is the same in the cannabis testing field – you can’t simply run a sample on a secondary method that isn’t designed for your lab and have confidence in the results. The fact that the method is fit for purpose is essential.

• Access to peer-reviewed data: The backbone of the scientific industry is community collaboration to verify results. Your methodology should be peer reviewed in credible, third-party scientific journals for endorsement.

This peer-review process should include reference to the method’s specificity, or its ability to detect target strains and differentiate them from nontargets.

This testing includes both wet lab analysis and in silico analysis.

In silico, data is gathered in the method design process through computer simulations of the method’s targets against known databases of bacterial or fungal DNA to ensure consideration of the inclusion of the community’s collective knowledge base of the target organism(s).

You don’t have to be a scientist or microbiologist to understand the peer-reviewed process – when in the consideration stage, you can ask your testing partner directly for the peer reviewed data for your reference.

• Diagnostic collaboration: One thing always remains true – you can’t test your way into compliance.

Data is only as good as your plan of what to do with it, and you don’t have to tackle your process gaps alone.

Confidence in diagnostic testing is best achieved when there is a true collaboration between the method developer and their testing partner.

No method developer expects labs to understand everything about testing on their own.

Testing is a necessary and vital part of success in the cannabis industry, so look for partners that offer data analysis, remediation guidance, field visits and attention to your specific considerations to drive compliance within your existing process.

You must anticipate the common result of testing positive for aspergillus and have confidence in your testing method.

Given the nature of aspergillus, it’s best practice to assume that your aspergillus positives are true positives.

The best way to do this is to regularly review data to develop proactive plans to address gaps in your process to lower your failure rate to align with industry standards.

Pat Bird is the senior manager of scientific affairs at bioMérieux, based in Cincinnati, Ohio. He can be reached at patrick.bird@biomerieux.com.

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