Quantitative analysis of endogenous compounds

Thakare, Rhishikesh; Chhonker, Yashpal S.; Gautam, Nagsen; Alamoudi, Jawaher Abdullah; Alnouti, Yazen

doi:10.1016/j.jpba.2016.06.017

Cited by 179 publications

(110 citation statements)

References 107 publications

Supporting

Mentioning

107

Contrasting

Order By: Relevance

“…neat solutions, artificial matrices, human serum albumin or 0.9% sodium chloride) or diluted matrices. If the actual matrix is used, various methods are followed including, background subtraction, or the standard addition method [3,15].…”

Section: Linearity When No Analyte-free Matrix Existsmentioning

confidence: 99%

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

View full text Add to dashboard Cite

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.

show abstract

Section: Linearity When No Analyte-free Matrix Existsmentioning

confidence: 99%

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

View full text Add to dashboard Cite

show abstract

“…Surrogate matrix is commonly used for calibration standard preparation for biomarker assays as authentic matrix contains the endogenous biomarker [24]. It was recommended that when surrogate matrix was used, similar matrix effect and extraction recovery in both the surrogate and original matrices should be demonstrated [24,25].…”

mentioning

confidence: 99%

“…It was recommended that when surrogate matrix was used, similar matrix effect and extraction recovery in both the surrogate and original matrices should be demonstrated [24,25]. In this paper, we highlight a procedure to generate IP-10-free blank cynomolgus monkey serum as the matrix for calibration standards.…”

mentioning

confidence: 99%

Immunoaffinity LC–MS/MS for Quantitative Determination of A Free and Total Protein Target as A Target Engagement Biomarker

Zhang

Shipkova

et al. 2017

Bioanalysis

View full text Add to dashboard Cite

Aim: IP-10 is a protein target for the treatment of Crohn's disease. Inhibition of IP-10 by anti-IP-10 mAbs neutralizes its various biological activities. The measurement of free IP-10 suppression as a target engagement biomarker is required for the assessment of drug effect on the target. Results: The development of highly sensitive immunoaffinity-LC-MS/MS assays for quantifying free and total IP-10 in cynomolgus monkey serum is reported for the first time. This paper details strategies for maximizing assay sensitivity by selecting digestion routes, and optimizing immunocapture to achieve full recovery and minimal matrix effect. For the free IP-10 assay, bioanalytical strategies have been established to minimize drug/ligand dissociation. Conclusion: The assays have been implemented for target engagement measurement, pharmacokinetic-pharmacodynamic correlation, and human dose projections.

show abstract

“…The preferred option for targeted analysis of metabolomics biomarkers is MS in the QqQ approach, as it provides one of the most sensitive tools for metabolites quantitation [10,43,44]. It should not be forgotten that absolute quantitation by this tool requires preparing standard curves in the same matrix as the samples under study so that the matrix effect and the extraction efficiency for the target metabolites must be the same in both the standards and samples.…”

Section: Analytical Tools For Search and Determination Of Biomarkers mentioning

confidence: 99%

“…It should not be forgotten that absolute quantitation by this tool requires preparing standard curves in the same matrix as the samples under study so that the matrix effect and the extraction efficiency for the target metabolites must be the same in both the standards and samples. Taking into account that, by definition, analyte-free biological matrices do not exist for endogenous compounds, the lack of blank matrices for quantification of endogenous compounds by LC-MS/MS must be addressed by different approaches (e.g., standard addition, background subtraction, surrogate matrix, and surrogate metabolite methods) by comparing their advantages and disadvantages [44].…”

Section: Analytical Tools For Search and Determination Of Biomarkers mentioning

confidence: 99%

Metabolomics in the Context of Forensic Omics Biomarkers

LS¹,

Castro²

2017

IJFP

View full text Add to dashboard Cite

Quantitative analysis of endogenous compounds

Cited by 179 publications

References 107 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

Immunoaffinity LC–MS/MS for Quantitative Determination of A Free and Total Protein Target as A Target Engagement Biomarker

Metabolomics in the Context of Forensic Omics Biomarkers

Contact Info

Product

Resources

About