Optimizing LC-MS Drug Testing: Best Practices for Method Validation

Liquid chromatography-mass spectrometry (LC-MS) testing combines two highly selective techniques that isolate and measure the target analyte of interest in complex biological matrices. The liquid chromatography component differentiates the compounds based on their physicochemical properties, whereas the MS detector differentiates compounds based on their mass-to-charge ratio. This dual selectivity makes LC-MS drug testing a powerful analytical tool. Besides, the mass spectrometer not only detects the compound but can also identify individual species corresponding to chromatography peaks. 

Whether researchers are performing ELISA, DDPCR assay, or LC-MS/MS analysis, each method requires in-depth development and validation. LC-MS method development and validation remains crucial for all LC-MS laboratories. The current article considers these requirements and shares best practices for LC-MS method validation. 

Best practices for validating and optimizing LC-MS drug testing 

An LC-MS method is often developed for use in routine analysis. However, before starting LC-MS assays for routine measurements, researchers should demonstrate its validity for reproducible and accurate results. 

LC-MS method validation is a process for establishing and reporting that a particular LC-MS system can produce data that is fit for its intended application. This requirement needs evaluation of different parameters that influence the assay performance. Generally, researchers obtain data for most of these parameters during the method development phase. However, additional experiments are needed to validate the acquired results and generate a final performance report before the developed method is used for routine analysis. 

Let us evaluate some crucial points while conducting LC-MS method validation. 

• Method validation should not just incorporate end measurements but also evaluate the performance of the entire procedure. 
• Method performance should include assessment of materials that may represent the materials with known value or test samples. 
• Before deeming a method as fit for purpose, one should upgrade the performance parameters before generating results. 
• Method validation should always include estimation of measurement and certainty even when the report does not require such specification. 
• Ideally, a method validation study should follow for a fit-for-purpose approach.

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Some of the parameters evaluated during LC-MS method validation include: 

Selectivity: the ability to measure the target analyte without any interfering components.

Precision: repeatability provides similar results when experiments are conducted under the same conditions. Reproducible results are when the measurement is estimated in separate laboratories. Moreover, intermediate precision is where results are provided with measurements observed in the same laboratory but in different work conditions.

Bias: any deviation from the true value, for example, certified values provided through reference material. 

Detection limit: this limitation is the lowest concentration where the target analyte is identified reliably. Notably, sensitivity is obtained after evaluating the detection capacities of an instrument.

Quantitation limit: this boundary is the lowest concentration where the target is reliably measured. 

Linearity and working range: the concentration range where the developed LC-MS method will produce data within an acceptable uncertainty. 

Robustness: this parameter evaluates the susceptibility of the LC-MS method against changes in external parameters such as environmental conditions. 

In conclusion

Robust LC-MS method validation remains critical for instilling confidence in the developed method.