Every analytical testing lab is different, sometimes in obvious ways, but the one thing that should not differ is the data that comes from a sample measured by a specific technique using a specific method which uses very expensive equipment to provide us with the ‘right’ number. When the testing lab is given accurate, complete information from the beginning, so the testing method used is the correct one for the analytes being tested — or what we call “fit for purpose”— this process is relatively straightforward.

Now, therein lies an important detail that would be worth a little time trying to better understand so that we are comfortable with the concept of the ‘right’ number or result. The ‘right’ number to a finished product manufacturer may mean that the measured number meets the specification given by the supplier. However, when the ingredient supplier makes their measurement, they may only be concerned that their manufacturing process consistently meets or exceeds an expected specification. Measurement accuracy is not necessarily critical to a supplier for their intended purposes, hence the number they provide on their CofA may not agree with what a lab gets. Why is this a big deal? It’s a testing failure which triggers a time consuming round or three of trying to figure out why. Understanding how this test process works can save time, money and lost sleep.

To satisfy the cGMP’s, one is required to prove that the value which appears on the label reflects the actual content in the bottle. It is very important that all the right information is provided to the lab so that an accurate measurement is performed. There are many factors that go into obtaining a meaningful number that actually satisfies the needs of all parties. Of course, the ‘party’ that really matters is ultimately the FDA. That said, all parties involved with the sample’s Chain of Custody must be able to talk the same language and be sure all understand each other so that the mutually agreed upon goal is met: the parameter being measured is accurate and meaningful and will satisfy strict analytical and regulatory scrutiny.

Now the question is, how can the client, who is trying to stay compliant with the cGMP’s by measuring whatever it is that is on their label before it goes into the bottle, make sure this test is done correctly and accurately? This is where a little understanding can go a long way. In order to get your sample analyzed to produce accurate and meaningful data, there will be specific items on a Sample Submission Form (SSF) that will require special attention. Items such as:

• The correct analyte to be measured or the correct Latin name of the botanical to be identified

• Any special extraction conditions that were used to prepare the test sample and what they are

• Is the substance pure or are there other substances mixed in with the material of interest and what are they?

• Is there a specification that you are trying to meet or is this a research only test?



There are many other questions that could be answered, but if, at a minimum, these few items are addressed, this should provide the lab with the minimum information necessary to analyze the test material correctly, the first time. On the other hand, if these questions are not all answered or are incorrectly answered, then we have multiple scenarios that could evolve. While there are many, here are some of the more poignant ones to consider: 1. The analytical method used is not the correct one for the analytes being tested or it is not fit for purpose. As an example, let’s say you want total ginsenosides measured in your finished product, which is now in a different matrix than the existing method was designed for a.k.a. a blend of multiple components, possibly including some vitamins and/or other herbs. For the uninformed, this seems like an easy task, but for the lab analyst, this is not the same as measuring the ginsenoside content in the crude raw material or the powdered extract by itself. Even though there may be a USP or other monograph that applies to the powdered extract, once this material is combined with other components, the test method may not be fit for purpose. The analysis is not the same now since the sample conditions have changed and there are many things to consider in order for the lab to analyze this material with any degree of accuracy.

Most people don’t realize that different sample conditions — like a crude raw material vs. a powdered extract vs. a blend — all may require different analytical testing conditions and the same method will frequently not work for each of the different matrices equally.

2. If any of the above conditions exist, then the existing method may require additional work to prove that the method being applied to the different matrix with the same test substance in it will actually be accurate with the new or different matrix conditions. This additional work could be as simple as adding a few relatively uncomplicated, non-time consuming procedures to the existing method of analysis to insure that the ‘new’ matrix does not interfere with the measurement process. If this type of ‘feasibility’ study proves that the method is capable of analyzing the new matrix accurately and the testing has been determined to be ‘scientifically valid’ for satisfaction of the cGMP’s, then we are good to go with a minimum of additional effort and cost.

3. If, on the other hand, after a ‘feasibility’ study determines there are significant issues with the ‘new’ matrix interfering with the usual method of analysis for obtaining an accurate and meaningful result, then in order for the analysis to provide an accurate result, the method will have to undergo further ‘method development’ specific to that matrix, and this will require further discussion between the lab and the client as well as additional costs. However, if such is determined to be necessary, it’s a smart investment for the client to make to ensure product identity and potency, and meet regulatory requirements.

With this in mind, taking care to fill out all SSF’s accurately and with all or as much information as is available for the test that is being requested, so that the applicability of the method applied to the test material is appropriate and fit for the purpose intended, can facilitate accuracy in testing, saving you time and money. Quality measurements are not made by accident. They are not the result of a single action, occurrence or event. They are a collection of activities that are planned, interrelated and cohesive; they should be considered alongside the development of manufacturing systems. These activities collectively are referred to as Measurement Assurance. Measurement Assurance is good for product quality and good for business, and is even mandated as it has been in the dietary supplement industry since 2007. However, this has been creating more confusion and/or raising more issues for many companies that are just learning all the details of what it takes to produce valid results for the materials they need to have tested.



A comprehensive Measurement Assurance program designed to mitigate risk and ensure quality has many components. It starts with the product ingredients and identification of the required measurements needed to prove ‘what is on the label is actually in the bottle.’ While there are many components, there are some that play a more important role than others. Obviously, the equipment is important and must be suitable for the measurement tasks and it also must be capable of producing valid results. Even good equipment can produce invalid results if not handled, maintained, used and/or stored properly.

Ideally, it is the process or product specifications that should drive the test and measurement process. Once it is determined what measurements are needed, we have to select a measurement process that has appropriate capability and is practical and affordable from a business perspective. There can be many different measurement techniques or methods to get the needed measurement information, but without reliable or adequate reference materials or standards to be able to generate data of the highest integrity, the method or technique used will not be very useful and the data will be nugatory.

Precision is universally considered to be the mutual agreement of individual measurements about some mean/average value (not necessarily the true value) while accuracy refers to the degree of agreement of individual measurements with some true or accepted reference value of that which is being measured. Accuracy has to do with the difference between individual measurements and some reference value or material. At best, every measurement is an estimate of the true value and it is an integral part of every laboratory’s purpose; to be competent at the chosen measurement process to ensure that the confidence level in the data generated is of the highest integrity. High integrity data is not solely a function of having a qualified reference standard or material, but without it, it would be impossible to achieve accurate measurements no matter what method is used. All other parameters that go into a measurement can vary from lab to lab, operator to operator and instrument to instrument, but will only be as good as the reference standard or material being used to make those measurements.



The most important single attribute of a measurement process is whether it can be made to run in a state of ‘statistical control.’ We know that repetition of measurement, as noted above, is subject to variability. The achievement of statistical control implies that the statistical properties of this variability are uniform over time so that it becomes meaningful to use measurements over a limited time span to predict limits of variation for both those and future measurements. All that said, there are different procedures that apply to qualitative vs. quantitative measurements. With quantitative analyses, we must demonstrate statistical control by evaluating the measurements to be confident that they are consistent with every repetition of the analysis. With qualitative analyses, the measurements, not being quantitative, cannot be evaluated statistically and are dependent on the quality of the reference material used for comparison to minimize variability of the qualitative measurements. This means that the more representative a botanical reference material is, the more capacity it has to measure with greater accuracy the identity of a test sample, thus increasing the confidence in the botanical identity measurement process.

With a qualified botanical reference material combined with suitable measurement methods, such as High Performance Thin-Layer Chromatography (HPTLC) and/or Microscopy, we can analyze an unknown sample based on its unique chemical signature or fingerprint and/or its unique anatomical characteristics to make a confident measurement of the correct genus and species of the test sample.