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Five Ways Cannabis Testing Labs Can Leverage Data

By Patrick Callahan

, James Brennan

Published: Apr 27, 2022   
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As more states initiate medical and adult-use marijuana commerce, the industry is working continuously to establish credibility and produce high-quality products to satisfy consumer demand. Knowledgeable consumers, including many patients, are concerned about cannabis product safety and consistent quality. Overall, the cannabis industry realizes the value of proper regulations and stringent third-party analytical testing. Testing services ensure cannabis products meet consumer expectations for quality, safety, and compliance. Cannabis testing laboratories help growers, cultivators, and processors to:

  • Build consumer and healthcare provider trust.
  • Meet numerous state regulatory requirements.
  • Mitigate risks in a rapidly expanding market.
  • Focus on superior products.

At the top of many efforts in the cannabis industry is the use of quality standards. Many cannabis testing laboratories receive accreditation for their conformance to the ISO/IEC 17025:2017 standard, which provides “General requirements for the competence of testing and calibration laboratories.” But some organizations have gone further. The ASTM Committee D37 on Cannabis has developed standards to address quality control, safety, and compliance in the cannabis industry. AOAC INTERNATIONAL also created the Cannabis Analytical Science Program (CASP) to promote analytical excellence with cannabis testing standards.

Cannabis industry standardization is becoming even more essential as the US Food and Drug Administration (FDA) increases its attention on this growing industry because patients use marijuana for numerous medical conditions. Committed to protecting public health, the FDA has offered guidance documents for cannabis products with an eye toward CGMPs (current good manufacturing processes). A recent article authored by members of FDA’s Botanical Review Team evaluated how closely the current state-level regulations follow CGMPs They found some of the written state regulations to be insufficient to support a submission to FDA for human clinical trials.

To compensate for the current and future guidelines, many cannabis testing labs, from start-ups to seasoned multistate operators, are relying on data to monitor the performance of the lab, reduce the variability in testing, automate lab testing, and, as a whole, align with growers to meet the need of any future requirements from both consumers and regulators.

State of the industry:             

Today's cannabis industry lacks harmonized regulations but is evolving towards quality-centric operations. In addition to maintaining compliance with various state laws, many organizations are developing standard operating procedures across state lines to gain efficiencies through standardization. Cannabis companies are starting to embrace the benefits of CGMPs, purpose-built laboratory informatics that support cannabis regulatory compliance, and advanced data practices to maintain this level of quality and meet the growing complexity in the market.

Five ways to leverage data to meet today’s and tomorrow’s challenges

1. Laboratory data integrity is an essential practice for high-quality cannabis.

Producing high-quality cannabis products relies on making sound business decisions based on laboratory data. The integrity of these data should address their completeness, consistency, and accuracy. The FDA issued guidance in 2016 explaining the principles of complete, consistent, and accurate data that should be attributable, legible, contemporaneously recorded, original or a true copy, and accurate (ALCOA). These data integrity concepts have expanded to ALCOA+ and similar acronyms to include complete, consistent, enduring, and available data. Data integrity is essential for any system that receives, stores, processes, or reports data generated during cannabis testing. Robust laboratory information management systems (LIMS) and practical data analysis tools can monitor laboratory performance and provide business intelligence to the laboratory and its clients. Systems that support data integrity concepts can ensure cannabis testing laboratories manage, analyze, and deliver high-quality data.

2. Take a data-first approach to reducing variability in cannabis testing.

Rigorous data management should be at the top of the testing laboratory infrastructure list. The process starts when a customer places an order for testing with the lab. Adherence to the principles of good laboratory practice (GLP), ISO/IEC 17025 accreditation, and a high-quality LIMS can effectively reduce data errors and variability in cannabis testing laboratories.

3. Meet demand without sacrificing high-quality results.

Cannabis testing laboratories can realize a connected ecosystem of data management technology applications: client test ordering portal, LIMS, quality management system (QMS), and data analytics to enable cost reduction, efficiency, and optimization.

As testing laboratories mature with the entire cannabis industry, they must rely on automation to meet client demand and deliver high-quality results. Various commercial solutions support the automation of the many processes in a cannabis testing lab. Selecting commercial systems developed with quality built-in and features that support regulatory compliance is crucial.

4. Leveraging data to analyze what happened.

Data automation should alert users to out-of-specification (OOS) results and support complete traceability of all events as the data moves through the laboratory. Data flagging can bring focus to a test failure that requires further action. Audit trails support data integrity and provide insight into the steps taken, who took the steps, and when. Inspection of the audit trail will show if any system user added or removed tests and if they edited test results. Audit trail review after results authorization and through to the final step of sample COA release can identify any irregularities and implement corrective action to improve laboratory processes or initiate personnel retraining. Leveraging audit trail data throughout the process is a good quality practice and builds credibility for the laboratory. 

5. Leveraging data to predict quality

Cannabis testing laboratories overflow with data that can provide actionable insights to help achieve performance goals. They present the testing results in many ways as an offering to the producers. A roadmap for cannabis analytics starts with getting consistent quality data at the beginning of the testing process. Maintaining data integrity at all steps will ensure that any subsequent reporting or analytics are the highest quality. The lab can offer its customers reliable analytics beyond the CoA, such as trending cannabinoid makeup by strain or presenting outliers in heavy metals results.

Modern statistical methods coupled with the correct data collection and technical strategies offer a means to develop predictions that can inform optimizations in the sample testing process at the lab and the production process for the client. The system that captures sampling results is the operating system of the lab, so keeping all information in an environment with clean and consistent data is imperative to leveraging advanced analysis and predictive tools. To ensure the analysis is effective, the first step should always be to evaluate how the data will be operationalized (or used) and how to implement changes directed by the predictions from the operator’s perspective. Ensure you have a team that understands why a prediction is showing a specific quality measure. Finally, a solid and tested lab information management system is key to managing the data and the process.


The demands of running a complex laboratory as a successful business are immense, but the effort to support cannabis product safety and quality is vital. Looking to data can help the cannabis industry proactively address challenges and be ready for inevitable changes. Cannabis testing labs can learn from other sectors with existing processes to leverage data for efficiency and quality. Efforts to develop standards for cannabis and hemp continue to be developed and contribute to credible and reliable results. While the federal enforcement priorities for cannabis remain unclear, the industry can deliver cannabis quality now by looking to established regulated industries, such as environmental, food, and pharmaceuticals, where quality is built into harmonized processes and systems from the start and not added later. There is little doubt that high-quality data collection and analysis will continue to impact the future growth, credibility, and acceptance of the cannabis industry.

Patrick Callahan

Director of LabWare Analytics

Prior to March 2022, Patrick was the CEO and founder of CompassRed, a mid-Atlantic visionary data analytics company named by Inc. magazine's fastest growing companies list. Then, in March 2022, LabWare acquired CompassRed, bringing its groundbreaking data solutions to reach over 125 countries. Here Patrick oversees a new data innovations center, utilizing advanced expertise in AI and machine learning technology to discover patterns, build predictive models, and create analytics solutions worldwide.

James Brennan

Sales and marketing specialist at LabWare

In his position, James focuses on laboratory informatics solutions for cannabis testing, biopharmaceutical, and other life sciences industries. James earned his Bachelor's in Biochemistry from the University of the Sciences in Philadelphia and his Master's in Chemistry from St. Joseph’s University. He started his career at the Fox Chase Cancer Center in the Pharmacology and Developmental Chemotherapy laboratories developing and validating bioanalytical methods for novel anticancer drugs. In 1996, he moved to DuPont Pharmaceuticals at the Stine-Haskell Research Center. In the Drug Metabolism and Pharmacokinetics Section, he supported regulated bioanalysis for the clinical trials of Sustiva (efavirenz), which is used to fight HIV infection. He became more involved in developing bioanalytical and pharmacokinetic data handling, storage, and retrieval methods. This experience led to a career dedicated to bioanalytical informatics, most recently at LabWare. James has contributed to over thirty peer-reviewed journal articles and scientific meeting abstracts.


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