Over the past few years, the cannabis industry has made progress in establishing credibility and producing high-quality products to satisfy consumer demand while meeting regulatory requirements. Cannabis testing laboratories and services operations are central and foundational to gaining trust, as they ensure the cannabis products meet consumer expectations for quality, safety, and compliance. These laboratories help growers, cultivators, and processors build consumer and healthcare provider confidence, meet numerous state regulatory requirements, mitigate risks in a rapidly expanding market, and focus on superior products. Most labs have embraced higher quality standards and welcomed proper regulations to meet the new demands and bring superior products to market.
As was with the development of the pharmaceutical industry, quality standards have played a key role in driving testing. Conformance to the ISO/IEC 17025.2017 standard is just one example: “General requirements for the competence of testing and calibration laboratories.” Other industry-leading organizations have designed standards even further. For example, the ASTM Committee D37 on Cannabis and AOAC INTERNATIONAL have focused their standard on safety, quality control, and compliance.
A broad view of today’s cannabis industry is that of a modern Wild West with few quality-focused operations. However, over the past year, the US Food and Drug Administration and other government-regulating organizations have been exhibiting a growing interest in the industry primarily because of the use of cannabis in medical treatment. Such attention and the desire for a higher standard of quality have been pushing many producers and testing labs towards ensuring they are embracing the benefits of CGMPs to prepare for the potential of regulatory compliance. In addition to regulatory compliance, a more competitive market has brought on the need for higher quality products to meet the educated consumer’s desire for a thoroughly vetted product.
Evolving to a Higher Quality Centric Operation
As cannabis operations mature, grow, and expand across state lines, models of relevant industries based on Current Good Manufacturing Practices (CGMPs) become relevant and required. Informatics and advanced data practices are essential to mature operations and can provide evidence and validation of quality processes. Laboratory information management systems (LIMS) will also prepare cannabis testing labs for future regulatory requirements that most realize are coming to fruition.
More recently, at the core of testing labs (both industrial pharmaceutical and cannabis testing), advanced analytics has become a tool for implementing quality. Analyzing the testing data more effectively or trending the results of samples over time are just a few methods being leveraged to produce high quality cannabis products. However, the tools and methods alone will not lead to an embrace of informatics. A strong culture and practice of fundamental data principles are required.
Ensuring Laboratory Data Integrity
In 2016, the FDA published a guidance document entitled “Data Integrity and Compliance With Current Good Manufacturing Practice.” The purpose was to provide guidance and requirements on data integrity and compliance with CGMPs. Data integrity is the need for complete, consistent, and accurate data that should be “attributable, legible, contemporaneously recorded, original or a true copy, and accurate (ALCOA).” The concepts were expanded later to ALCOA+ and added the requirements of data to be complete, consistent, enduring, and available.
Any testing lab, in order to build a foundation based on quality, has at its core an enabling lab information management system (LIMS) that is based on these principles of Data Integrity and necessary for any type of future analysis. Modern labs that leverage basic and advanced analytics must be built on this foundation. Cannabis testing laboratories without this run the risk of errors and variability in cannabis testing and could have a devastating impact on their business and the consumer.
Taking a Data-First Approach Toward the Reduction in Variability
By embracing a data-first approach to production, labs can understand what is causing variability in production and how to best address it. Additionally, data will help track progress over time and ensure the efforts are reducing variability. Finally, sharing data with other growers can help to create best practices for reducing variability in cannabis production. From when a testing order is placed to the endpoint of shipment, adherence to the principles of good laboratory practice (GLP), ISO/IEC 17025 accreditation, and a high-quality LIMS will reduce data errors and provide an opportunity for increased quality.
Leveraging data for Out of Specification results, historical analysis, and traceability
Leveraging data analytics and automation can help alert users to out-of-specification results and support complete traceability of all events as the data moves through the laboratory. By automating data collection and analysis, laboratories can more easily identify outliers and track results throughout the testing process. Additionally, data automation can help ensure that all data is properly collected and recorded, providing a complete picture of what occurred during the course of testing. By supplementing and informing the lab managers and testers with automated data systems, an opportunity exists for error reduction and testing failures through automatic flagging and alerts.
In addition to in-process real-time insights, historical audit trails can show if a lab operator added or removed tests and if they edited test results. Reviewing the audit trail after results authorization and through to the final step of the sample certificate of analysis (COA) release can identify any irregularities and help 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.
Embracing Advanced Analytics for Predicting Quality and Operational Efficiency
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. To ensure the analysis is effective, the first step should always be to evaluate how the data will be used and how to implement changes directed by the predictions from the operator’s perspective. A solid and tested lab information management system is key to managing the data and the process.
In addition, predictive and advanced analytics can support the lab in managing production loads, material needs, and staffing requirements. These available methods also help to optimize their testing protocols and better serve their clients. Modern statistical techniques coupled with the correct data collection and technical strategies offer a means to develop predictions that can inform optimizations in the lab’s sample testing process and the client’s production process.
The Lab of the Future is Required for the Testing Labs of Today
Despite its relatively new nature, the cannabis testing lab of today does not have to be the lab of the future. These labs can safely and economically adopt the technologies, practices, and culture of those manufacturing systems that have been in place to support a variety of regulated and non-regulated production labs. Though a strong federal guideline has not been developed, the industry is not preempted from adopting the practices of prior industries where quality systems and processes are thought of at the start. This situation provides a basis for growth and reduces the cost of future investments and the risks of loss of credibility and quality. A culture of embracing data integrity standards and systems at the outset is a necessary foundation for an industry in constant growth.
Co-Authors:
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 to Inc. magazine’s fastest growing companies list. In March, LabWare, a global leader for LIMS and ELN, acquired CompassRed allowing their 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 is a Sales and Marketing Specialist at LabWare, Inc., the global leader for Laboratory Information Management Systems (LIMS) and Electronic Laboratory Notebooks (ELN).
In this position, he focuses on laboratory informatics solutions for cannabis testing, biopharmaceutical, and other life sciences industries. James earned his B.S. in Biochemistry from the University of the Sciences in Philadelphia and his M.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 James 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.
