Use of Internal Standards in LC‐MS Bioanalysis

Tan, Aimin; Awaiye, Kayode

doi:10.1002/9781118671276.ch17

Cited by 30 publications

(31 citation statements)

References 40 publications

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“…The role of IS concentration on the linearity of the calibration curve has been demonstrated by Tan et al [13]. They presented a case in which decreasing concentration of the IS from 100% For the quadratic regression model, the F-value of the lack-of-fit test and the P-value for testing significance of the second-order coefficient for the quadratic regression model are represented.…”

Section: Practical Example 3: Is Concentration and The Linearitymentioning

confidence: 94%

“…The choice of IS is also depending on the extraction method. Tracking an analyte during a simple protein precipitation procedure would be less stringent than that for liquid-liquid extraction (LLE) or solid-phase extraction (SPE) method [13].…”

Section: Internal Standard (Is)mentioning

confidence: 99%

“…In this method, after the injection of the sample containing the analyte of interest, a standard solution is also injected, which result in two peaks for the analyte, one from the sample and the other from the standard solution with constant concentration (an echo peak). By using their response ratio for quantitation, the ME might be compensated for because the two peaks are affected by the coeluted matrix components similarly [13].…”

Section: Internal Standard (Is)mentioning

confidence: 99%

“…IS should be added as early as possible to compensate for the variabilities during sample preparation and analysis; however, if the IS structure is not very close to the analyte, it can be used to reduce the variabilities due to the ion suppression or enhancement only and not sample extraction [13].…”

Section: Internal Standard (Is)mentioning

confidence: 99%

“…In that case, the cross-contribution from the analyte to the IS is equivalent to 5% of the concentration of the analyte. The cross-signal contribution from the analyte to the IS is either due to the isotope interference or chemical impurity in reference standard [13].…”

Section: Practical Example 3: Is Concentration and The Linearitymentioning

confidence: 99%

See 4 more Smart Citations

Linearity of Calibration Curves for Analytical Methods: A Review of Criteria for Assessment of Method Reliability

Moosavi¹,

Ghassabian²

2018

Calibration and Validation of Analytical Methods - A Sampling of Current Approaches

104

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Calibration curve is a regression model used to predict the unknown concentrations of analytes of interest based on the response of the instrument to the known standards. Some statistical analyses are required to choose the best model fitting to the experimental data and also evaluate the linearity and homoscedasticity of the calibration curve. Using an internal standard corrects for the loss of analyte during sample preparation and analysis provided that it is selected appropriately. After the best regression model is selected, the analytical method needs to be validated using quality control (QC) samples prepared and stored in the same temperature as intended for the study samples. Most of the international guidelines require that the parameters, including linearity, specificity, selectivity, accuracy, precision, lower limit of quantification (LLOQ), matrix effect and stability, be assessed during validation. Despite the highly regulated area, some challenges still exist regarding the validation of some analytical methods including methods when no analyte-free matrix is available.

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Section: Practical Example 3: Is Concentration and The Linearitymentioning

confidence: 94%

Section: Internal Standard (Is)mentioning

confidence: 99%

Section: Internal Standard (Is)mentioning

confidence: 99%

Section: Internal Standard (Is)mentioning

confidence: 99%

Section: Practical Example 3: Is Concentration and The Linearitymentioning

confidence: 99%

See 3 more Smart Citations

Linearity of Calibration Curves for Analytical Methods: A Review of Criteria for Assessment of Method Reliability

Moosavi¹,

Ghassabian²

2018

Calibration and Validation of Analytical Methods - A Sampling of Current Approaches

104

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Nonspecific Binding in LC–MS Bioanalysis

Tan

Fanaras

2017

Targeted Biomarker Quantitation by LC–MS

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Impact of introducing a new biological matrix into a validated bioanalytical method: Focus on matrix protein content

Brown

2024

Biomedical Chromatography

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International guidance on bioanalytical method validation recommends the practice of partial validation when introducing a new matrix from the same species into a previously fully validated assay. Planning the partial validation protocol should include an evaluation of analyte chemistry, consideration of sample container materials, and a comparison of properties between the relevant biological matrices. Transition of a serum/plasma‐validated bioanalytical method to analysis from a low‐protein matrix, such as urine, cerebral spinal fluid, or oral fluid can result in inconsistent analyte recovery. The low recovery can potentially be mistaken for signal suppression or lack of drug stability and may be more pronounced in low‐concentration or low‐volume samples. In addition, adsorption and absorption interactions with containers may be exacerbated in low‐protein matrices. Several possibilities exist for mitigating the impact of non‐specific binding and low‐protein matrices, including surfactants, bovine serum albumin, and β‐cyclodextrin. Finally, higher matrix protein can facilitate analyte stability. Given all this, matrix protein content should not be overlooked when anticipating a partial bioanalytical method validation.

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Use of Internal Standards in LC‐MS Bioanalysis

Cited by 30 publications

References 40 publications

Linearity of Calibration Curves for Analytical Methods: A Review of Criteria for Assessment of Method Reliability

Linearity of Calibration Curves for Analytical Methods: A Review of Criteria for Assessment of Method Reliability

Nonspecific Binding in LC–MS Bioanalysis

Impact of introducing a new biological matrix into a validated bioanalytical method: Focus on matrix protein content

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