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Developing Analytical Methods for Food Testing

Foods and various foodstuff products are analyzed and tested by scientists working in many key sectors within the food industry, including manufacturers, suppliers, analytical labs, government labs, and beyond. Beyond the safety of consumers, why is the development of methods for food testing so critically important and what are these methods designed to test for?

Although it varies depending on which organization is doing the testing, the reason behind testing can be whittled down to a few main areas of focus, including nutritional labeling, authenticity, food inspection, food safety, quality control, and research and development. Typically, contract research organizations (CROs) like ºÚÁϲ»´òìÈ are testing for one, or even all, of those areas contingent on what challenges our clients need to find an innovative solution to overcome.

At ºÚÁϲ»´òìÈ, we aim to make tomorrow safer than today, and that includes the food made available to consumers. We work to ensure the products our clients are developing and bringing to market are high quality, nutritious, truthfully labeled, and most importantly, safe.

Key considerations for new method development

As with all analytical methods, the final purpose of the method should guide development activities, meaning sound methodology for food testing ensures the food we eat is safe and consistent with label claims. Regardless of the final purpose, there are a few specific factors to consider. The first consideration is typically the analyte of interest, as that will inform which instrumentation will be suited to achieve the purpose of the method. Some analytes are more challenging than others, and platform methods may exist for the analyte or for closely-related compounds, which can be used as a starting point for analytical method development. In some cases, the analytical method must be developed from scratch via research. If analytes are unknown, then a broader, more investigative approach may be required, rather than a targeted method.

Second is the sample matrix. Specifically with food, this is especially important as matrix effects can be quite strong due to the presence of sugars, salts, and fats. Creative sample preparation techniques for partial purification such as solid phase extraction, liquid-liquid extraction, and centrifugal filters can mitigate matrix effects. Another approach is the use of quantitation strategies that normalize matrix effects, such as the method of standard additions.

The last major consideration is the required sensitivity of the method. Is the analyte present at trace levels or is it a primary constituent? This can also influence the choice of instrumentation, as it is unproductive to overwhelm a highly sensitive instrument with a complex food sample when the required limits of detection can be achieved with a less sensitive, more accurate method.

Overcoming challenges in food method development

ºÚÁϲ»´òìÈ has validated a screening method for 21 mycotoxins, which has also been applied to screening candy matrixes. Utilizing a solid phase extraction procedure to clean up samples and sensitive liquid chromatography with tandem mass spectrometry (LC-MS/MS) methodology, limits of detection were well below necessary regulatory limits for mycotoxins. The US Food and Drug Administration (FDA) requires a limit of 20 ng/g for aflatoxins. Our method LOQ was 0.4 ng/g.

The mycotoxin methods were originally verified in methanol extracts of candy samples. The sample matrix caused many issues with the liquid chromatography mass spectrometer (LC-MS). Columns became clogged and signal suppression made it difficult to obtain the needed sensitivity for regulatory limits. With the addition of a guard column, it helped somewhat with the preserving of the analytical column life, but the signal suppression caused system suitability failures in routine testing. A solid phase extraction procedure, based on a lipid extraction protocol was added to the method and improved method sensitivity, a technique often used by Emma Leishman, Ph.D., ºÚÁϲ»´òìÈ’s Manager of Advanced Analytics.

Additionally, ºÚÁϲ»´òìÈ’s scientists have developed test methods for specific biomarkers of avocado oils. Finding biomarkers specific to avocado oil proved challenging as there are no standards for what constitutes an extra virgin avocado oil. Levels of bioactive compounds can vary by cultivar of avocado, growing conditions, manufacturing conditions, and storage conditions. Biomarkers with lower variability in published ranges were chosen based on published literatures. Furthermore, matrix effects were an issue with these methods, but the use of spiked samples allowed for normalization of data. A great deal of variability between brands of avocado oil was observed, despite similar label claims of “extra virgin.” However, having a method with minimal variability illustrated that most of the variability was from the samples. Without a solid analytical method, no meaningful differences in the samples would have been able to be detected. This analytical approach allowed us to develop a quality metric for avocado oils to compare over 20 different oils.

Furthermore, an LC-MS method for palm leaf alkaloids was developed to determine if these potentially toxic compounds were leaching from palm leaf plates into various food simulants. Similar to what was observed with avocado oils, the palm alkaloid method presented challenges with some lots of palm plates producing higher levels of alkaloids than others. As the method underwent suitable validation, ºÚÁϲ»´òìÈ’s scientists were able to conclude variability was resulting from the samples, and not the analytical methodology.

The benefits of partnering with a CDMO for outsourcing analytical methods for food matrices

While there are many benefits of partnering with lab for outsourcing, where do you begin in finding suitable, beneficial partnerships? Some of the major things to look for when seeking out an outsourcing partner, specifically for method development, are the three E’s: equipment, experience and expertise.

Equipment should be up-to-date and able to meet dynamic regulatory needs. Having a wide range of equipment is another significant benefit, as the most suitable instrumentation can be applied, and multiple analytical methods can be developed simultaneously. A strong indicator of future success is a proven track record of success and experience, both from an organizational standpoint and the scientists that will be responsible for method development and sample analysis. Ideally the company will have experience with similar analytes and matrixes. Aside from scientific experience, having regulatory experience with method development and validation minimizes risk altogether.

Successful outsourcing partners will have scientists on staff who are subject-matter-experts on specific instrumentation. Method development often requires a creative approach, therefore having a broad range of expertise to leverage and troubleshoot is beneficial. Particularly when working with food matrixes, experience with biological matrixes can be an additional bonus, as these scientists will understand that there will be matrix effects to overcome with different sample preparation and normalization approaches. Sufficient expertise can ensure that even the most challenging methods are developed in a timely manner.

Additionally, finding an outsourcing partner who has past experience with similar methodology indicates a high likelihood of future success. Recommendations from previous clients can provide reassurance of top-notch service and quality. It is also important to understand the experience the outsourcing lab has with relevant regulatory authorities, which aids in the initial assessment of quality systems. Regulatory considerations are a guiding principle for method development. As even if a method is not going to be validated, following established guidelines for the validation of analytical procedures, such as ICH Q2, can help guide method development activities, ensuring the analytical method is selective, sensitive, accurate and precise.

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