Fundamentals: Bioanalytical LC/MS method validation - fit for purpose

Ludmila AlexandrovaStaff Scientist, Stanford University Mass Spectrometry (SUMS)

ludmilaa@stanford.edu

SUMS SEMINAR SERIESJULY 2, 2020

Submit your questions!

Related Seminars in SUMS SeriesTHURSDAY APRIL 2, 2020 - SUMS SEMINAR SERIES

Fundamentals: Measuring concentrations of small molecules using mass spectrometry -theory and practice, Part I

THURSDAY APRIL 23, 2020 - SUMS SEMINAR SERIES

Fundamentals: Measuring concentrations of small molecules using mass spectrometry -theory and practice, Part II

THURSDAY May 21, 2020 - SUMS SEMINAR SERIES

Fundamentals: Applications of LC/MS in small molecule drug discovery

Recording and slides are available at https://mass-spec.stanford.edu/events

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Presentation OutlineIntroduction

Ø Bioanalysis in Drug Discovery and DevelopmentØ Fit For Purpose Concept in Bioanalysis

Part 1Ø Method Validation: Bioanalytical Assay Performance Attributes and

Requirements

Part 2Ø Case study 1 – Melphalan LC-MS/MS Method Development and

ValidationØ Case study 2 –Determination of Global DNA Methylation Levels in

Clinical Samples by LC-MS/MS

Conclusion

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Introduction

• Toxicology studies

• Clinical studies

• LC/MS bioanalytical methods

LO P1 P2 P3 Market

Non-GLP method GLP/GCP methodParentMetabolite

LI CCS CLS

GLP: Good Laboratory PracticeGCP: Good Clinical Practice

• Pharmacokinetic/ADME studies

• Biomarker research

AbsorptionDistributionMetabolismExcretion

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It is critical to use well characterized and appropriately validated LC/MS bioanalytical methods to ensure data integrity

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What Is Bioanalysisq Bioanalytical Method (BA) performs quantitative analysis of drugs and

metabolites in biological matrices (e.g. plasma, blood, serum or urine) in support of pharmacokinetic (PK), toxicokinetic (TK) and clinical studies, pharmacology evaluation, biomarker research, formulation development, etc. Small molecule platform – LC/MS/MS

q Fully validated BA methods support pivotal TK/PK and clinical studies that are used in regulatory submissions

q For non regulatory studies, extent of BA method validation may be defined by the purpose of the study.

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Why is Bioanalytical Method Validation Important?q High data quality

Ø Reproducible and reliable dataØ Sensitivity establishedØ Stability investigated

q Data used for safety and efficacy assessmentq Data integrity aids to results interpretation q Increasing demand of peer-reviewed scientific journals

Why Not Done Routinely?q Time consuming and labor intensiveq Not always required e.g. screening studies, exploratory studies, endogenous/biomarkers

quantitation

Fit for purpose approach is a useful tool in conserving resources and time to generate reliable data

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Fit For Purpose (FFP)q “The fit for purpose (FFP) concept states that the level of validation should be

appropriate for the intended purpose of the study”

Ø FFP applies to drugs, their metabolites, endogenous compounds and biomarkers and is used extensively during exploratory stages of drug development

Ø It is important to evaluate study goals and objectives as well as quantification approaches and create validation strategy

Ø Extent of validation and key parameters should be specified and justified in validation plan: e.g. accuracy, precision, stability etc.

Ø Specific validation requirements and acceptance criteria may need to be established for each analyte

Food and Drug administration. Bioanalytical method validation Guidance for industry.https://www.fda.gov/regulatory-information/search-fda-guidance-documents/bioanalytical-method-validation-guidance-industry

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Method Validation: Bioanalytical Assay Performance Attributes and Requirements

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BA Method Validation WorkflowoMethod development

• Instrument sensitivity: optimize column chemistry, mobile phase, mode of ionization, SRM, etc.• Sample preparation: PP simple, L-L less matrix impact, SPE more manipulations • Determine curve fitting/weighting; assess accuracy/precision• Key indicators: ion suppression, lot to lot variability

o Validation (guidance driven)• Precision and Accuracy: 3 runs, each a curve + 4 QC levels (n=6) à %CV and % Bias ±15% (or

±20% at LLOQ)• Stability in biological matrix (room temperature, Freeze-Thaw, frozen storage, auto-sampler) and

stock solution (storage)• Specificity (endogenous interference), matrix effect, selectivity, recovery, carryover

o In-study (routine) analysis• Curve, QC (3 levels, n=2), blank, contamination and carryover, IS, peak shape, RT

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Method Validation: Key Parameterso Small molecule platform – LC-MS/MS in SRM modeo Method Validation plano Bioanalytical assay performance attributes and requirements

o Reference Standards/Internal Standardso Calibration curve, range, regression modelo Sensitivityo QC sampleso Accuracyo Precisiono Dilution effecto Selectivity, Specificityo Recoveryo Stability/Incurred sample reanalysis

o Documentation o Instrumentationo Software

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Reference Standards/ Internal Standards o Certified reference standards with known identity and purity should be used to

prepare spiking solutions of known concentrations (certificate of analysis, CoA)

o Internal standard does not require CoA if it demonstrates that it does not interfere with quantification of analyte

o Analyte stock and working solution stability should be tested to justify duration and storage conditions

o Isotopic exchange stability of IS (analyte specific)

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Calibration Curveo Calibration curve is a relationship between the instrument response and

concentration of analyte within selected concentration rangeØ Calibration curve should be prepared in the same matrix as the samples

and extracted side by side with the same procedureØ Choose concentration range of method on the basis of concentration range

expected in particular study: Lower Limit of Quantification (LLOQ) and Upper Limit of Quantification (ULOQ)

Ø LLOQ defines the method sensitivity and is assessed during method validation

Ø Use simplest regression model that describes the concentration – response relationship; appropriate weighting scheme

Ø If more than one analyte, calibration curve should be generated for all analytes

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Quality Control Sampleso Quality control sample (QC) is a sample spiked with the known amount of

analyte

Ø QCs are prepared in the same matrix as samplesØ QC samples are used to assess precision, accuracy of the assay and

stability of analyte(s)Ø QCs prepared from a separate stock solutionØ It is recommended that blank matrix is screened before QC preparationØ To assess a dilution effect, QCs above Upper Limit of Quantification may

be prepared and analyzed in diluted form and monitored during validation

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Precision and Accuracyo Precision is a repeatability of the series of measurements which is

expressed as % CVo Accuracy is the ability to measure a true value based on nominal value which is

expressed as % deviation from nominal value (% Bias)

Ø Precision and Accuracy of the method is determined based on QC replicate analysis at the LLOQ, Low, Mid and High QC levels over full calibration range conducted over several days (at least 3 independent runs).

Ø Precision and accuracy is calculated within-run (Intra-assay) and between-run (Inter-assay)

Ø Each run includes a calibration curve and multiple QC concentrations that are analyzed in replicates (≥ 5 replicates per each level).

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Selectivity, Specificity and Matrix Effecto Selectivity is the ability to differentiate and measure the analyte of interest in the presence of endogenous

compounds Ø Selectivity demonstrated by analyzing blank samples of appropriate matrix from multiple

sources (at least 6) to determine and minimize interferenceØ Selectivity should demonstrate minimal or no response related to interfering component at the RT of

analyte in blank sample (≤ 20% LLOQ; ≤ 5% of the IS response)

o Specificity is the ability to unequivocally differentiate the analyte of interest in the presence of other analytes Ø Potential interferences: compounds structurally similar to analyte, unstable metabolites (e.g.

esters, unstable glucuronides, N-oxides etc.), isomers, impurities, decomposition products, concomitant medications and other xenobiotics

Ø Internal standard evaluated for interference on analyte quantitation

o Matrix effect is a change in the analyte response due to unspecified components in the matrixØ Evaluated in relevant patients or special populations; hemolyzed or lipemic samples or if

stabilizer or enzyme inhibitor is used during sample collectionØ Determine ion matrix suppression or enhancement

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Recovery, Carryoverq Recovery is the extraction efficiency of analytical process reported as a percentage of the

known amount of analyte carried out through the processing method

o Recovery needs to be determined and optimized to insure it is efficient and reproducible

• It does not need to be 100%, but consistent and reproducible over calibration range (Low, Mid, High)

• Applies to both, analyte and internal standard• Recovery performed by comparing analytical results of extracted samples with

corresponding spiked post-extraction samples, representing 100% recovery

q Carryover is a change in measured concentration due to residual analyte interference from preceding sample o Carryover should be evaluated and eliminatedo If not possible, study samples should not be randomized

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Stability of Analyte(s) in Biological Matrixq QCs are used for stability assessment

○ Autosampler (re-injection reproducibility)Ø Stability of processed samples at autosampler temperature

○ Bench-top (short-term) matrix stabilityØ Laboratory handling conditions. Kept on the bench top at the same temperature

and for the same duration as study samples ○ Extraction/injection (sample processing stability)

Ø In process sample stability to be used during sample analysis○ Freeze-Thaw matrix stability

Ø Stability assessment after multiple cycles of freezing and thawing according to the same procedure applied to the study samples

○ Long-term matrix stabilityØ Stability of analyte should be demonstrated under the same storage conditions

and duration as study samples

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Incurred Sample Reanalysis (ISR)q ISR is a repeat analysis of subset of samples which had been analyzed

previously in a separate runq ISR confirms reliability of reported dataq It is used to support precision, accuracy and stability data established

with QCs. Ø E.g. presence of unstable metabolites which could degrade back to

parent compoundq ISR acceptance criteria measured by % difference of the results

between original value (1) and repeat value (2) divided by mean of 1 and 2

q ISR required for regulatory studies

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Case Study 1

Development and Validation of LC-MS/MS Bioanalytical Method for Determination of Melphalan in Human Plasma

Kim JW, Alexandrova L, DeMarchis E, Lee D, Chien A. (2012) “LC-MS/MS Quantification Of Melphalan Plasma Levels In Children Undergoing Selective Intra-arterial Infusion Of Chemotherapy For Retinoblastoma,” Investigative Ophthalmology & Visual Science. March 2012, 53, 468.

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Backgroundq Melphalan is an alkylating agent with effective tumoricidal properties

but also severe systemic side effects.

q A minority of subjects developed neutropenia, which suggests that systemic diffusion of the drug does occur.

q Developing a reliable LC-MS/MS assay to determine plasma levels of melphalan following ophthalmic artery infusion is critical in optimizing the benefits of this treatment.

Melphalan LC-MS/MS Method Development

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SUMS seminar series

Fundamentals: Measuring concentrations of small molecules using mass spectrometry - theory and practice, Part I

Fundamentals: Measuring concentrations of small molecules using mass spectrometry - theory and practice, Part II

Fundamentals: Applications of LC/MS in small molecule drug discovery

Structures

Melphalan Internal Standard: Melphalan-D8

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LC-MS/MS Method

o TSQ Vantage (Thermo Fisher)o Accela 1250o CTC PAL Autosampler

o ESI+o Column: Polaris A 5 µm C18 50x2.1 mmo Run time 5.6 mino Injection volume – 10 µLo Wash solutions

o Strong – methanolo Weak – 5% methanol/ 95%water

Compound Name

SRM Transition Collision Energy(v)

Melphalan 305→288305→246305→194

122234

Melphalan-D8 313→254313→293

2312

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Time (min) %A (0.1%FA in water)

%B (0.1%FA in acetonitrile)

Flow rate

(mL/min)

0 80 20 0.25

3 5 95 0.25

3.5 5 95 0.25

3.6 80 20 0.25

5.6 80 20 0.25

Extraction Procedure

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KimJ_120402_35370_46 - TIC - SM: 5 RT: 0.62 - 4.62 NL: 4.19E7F: + p ESI SRM ms2 305.032 [ 194.054-194.059, 246.042-246.047, 288.060-288.065]

1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5Time (min)

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RT: 2.62

1.53 3.03 3.682.191.71 2.44 4.083.473.261.97 4.423.861.261.010.75

KimJ_120402_35370_46 - TIC - SM: 5 RT: 0.60 - 4.60 NL: 1.22E7F: + p ESI SRM ms2 313.145 [ 254.098-254.102, 296.118-296.123]

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RT: 2.60

1.54 2.061.84 2.42 3.462.97 3.693.16 4.25 4.523.931.00 1.310.79

o 100 µL plasmao 10 µL melphalan spiking solutionso 10 µL IS (500 ng/mL Melphalan-D8)o 400 µL ice cold methanolo Vortex, centrifugeo Transfer to the injection vialo 10 µL injected

Melphalan

Melphalan-D8

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Melphalan LC-MS/MS Method Validation

Melphalan LC-MS/MS Method Validation Plan

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Experiment QC level (ng/mL)LLOQ LQC MQC HQC

2 6 100 3200

Within-run precision and accuracy n=6 n=6 n=6 n=6

Between-run precision and Accuracy (3 runs) n=6 n=6 n=6

Calibration Curve (10 points – 1 per run) Back calculated concentrations

Acceptance criteria ±20% ±15% ±15% ±15%

Selectivity and Specificity 6 different lots (<20% LLOQ)

Recovery 3/3 3/6 3/6Acceptance criteria NA NA NA

Experiment QC level (ng/mL)

LLOQ LQC MQC HQC2 6 100 3200

Short-term stability (bench) n=1 for all calibration points

Acceptance criteria ±20% ±20% ±20% ±20%

Post-preparative Stability (reinjection) n=6 n=6 n=6

Acceptance criteria ±15% ±15% ±15%

Freeze-Thaw Cycles (n=3) n=6 n=6 n=6

Acceptance criteria ±20% ±20% ±20%

Selectivity

6 different lots of blank human plasma were tested

Some endogenous interference at the retention times of the analyte was observed.

Blank plasma from lot#97 was not used for the method validation.

Acceptance criteria: ≤ 20% LLOQ

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Lot #Measured concentration

(ng/mL) % of LLOQ

95 0.19 9.4

96 0.11 5.6

97 1.39 70.3

1 0 0

2 0 0

3 0 0

KimJ_120329_35370_38 - TIC - SM: 5 RT: 0.57 - 4.57 NL: 1.59E5F: + p ESI SRM ms2 305.032 [ 194.054-194.059, 246.042-246.047, 288.060-288.065]

1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5Time (min)

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RT: 2.57

1.54

3.67

3.522.13

1.73

2.932.311.86

4.46

3.09 3.35 4.124.013.20

0.92

KimJ_120329_35370_38 - TIC - SM: 5 RT: 0.58 - 4.58 NL: 1.76E7F: + p ESI SRM ms2 313.145 [ 254.098-254.102, 296.118-296.123]

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RT: 2.58

1.59 2.03 2.23 3.181.77 2.97 3.53 4.103.84 4.29 4.480.78 1.13 1.39

It is important to screen blank plasma

endogenous

Representative Calibration Curve Data (3 runs)

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Nominal Concentrations

(ng/mL) Mean CV (%) Bias (%)

2 2.02 2.39 1.08

4 3.91 2.95 -2.17

10 9.8 2.49 -2.40

20 19.1 1.99 -4.67

50 48.7 2.07 -2.53

100 101 1.99 0.73

200 198 0.291 -0.83

400 420 4.00 4.88

Melphalan

Y = 0.0171088+0.00829092*X R^2 = 0.9991 W: 1/X^2

0 50 100 150 200 250 300 350 400

ng/mL

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

2.8

3.0

3.2

3.4

3.6

Area

Rat

ioCalibration curve concentration range: 2 ng/ml – 400 ng/mL Lower Limit of Quantification = 2 ng/mLAcceptance criteria: LLOQ ± 20%; Other levels: ±15%

Calibration curve parameters Mean CV(%)

slope 0.008 2.08

Y-int 0.016 7.13

r2 0.998 0.17

QC Precision and Accuracy Data

Within-run and between-run precision and accuracy were assessed by calculating daily and overall concentration values for six replicates of the LLOQ, Low-, Mid- and High-level validation QC samples extracted and analyzed on the same day and in three separate runs

Acceptance criteria: Ø LLOQ - %CV and % Bias ±20%Ø %CV and % Bias ±15%

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LLOQ LQC MQC HQC

Conc. (ng/mL) 2 6 100 3200

Aliquot (mL) 0.1 0.1 0.05 0.01

Dilution factor 1 1 2 10

Within-runMean 1.95 6.39 100 2989% CV 10.3 9.6 7.71 8.63

% Bias -2.50 6.53 0.00 -6.59Between-run

Mean 1.98 6.42 104 3289% CV 9.03 5.79 6.41 8.93

% Bias -0.94 6.95 4.04 2.78

Calibration curve range 2 – 400 ng/mLLLOQ = 2 ng/mLMethod ULOQ = 4000 ng/mL

Melphalan Extraction Recovery

Recovery samples o Extracted QC samples (Extracted )o Control samples: Extract blank plasma spiked with IS and analyte added after extraction

(Post-Extracted)Absolute recovery determined based on analyte/IS area ratio

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QC % Recovery

Low 97.1

Mid 100

High 92.2

Short-Term StabilityBench-top (short-term) matrix stability

Melphalan stored in human plasma on the bench at ambient temperature for ~ 4 hoursSamples at 2ng/mL and 200ng/mL were outside acceptance criteria (>20%)Study plasma samples should be collected and frozen within 4 hours of the sample

collection time point

Autosampler (re-injection reproducibility)Melphalan is stable in human plasma extracts held at 10°C for 24 hoursEither an entire run containing analytical standards or individual samples may be

reinjected as needed during this time period without compromising the accuracy of the determination

Freeze-Thaw CyclesNo significant changes in the measured melphalan concentrations outside the expected

accuracy for the method (% Bias ±20%)Melphalan is stable for at least 3 Freeze-Thaw cycles in human plasma when stored at

-80 ± 10°C.33

Melphalan LC-MS/MS Method Validation Summary

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Standards QCs (Low, Mid and High) LLOQWithin-run Precision (%CV) - 7.71 – 9.6 10.3

Within-run Accuracy (% Bias) - (-6.59) – 6.53 (-2.50)

Between-run Precision (%CV) 0.29 – 4.0 5.79 – 8.93 9.03

Between-run Accuracy (% Bias) (-4.67) – 2.25 2.78 – 6.95 (-0.94)

Analyte Recovery % 92.2 - 100

Selectivity: Matrix Blanks Low interference (≤20% of LLOQ)

StabilityPost Preparative 24 hours at 10°C in autosamplerShort Term (Bench): 4 hours at room temperature in plasma <4 hours at room temperature in plasma

Freeze-Thaw Cycles 3 cyclesIntermediate Solution Stability (Analyte) < 7 months at -80°C

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Resultsü Bioanalytical method for determination of melphalan in human plasma

was shown to be accurate, precise and selective over the concentration range from 2 to 4000 ng/mL

ü Melphalan is stable in human plasma under conditions tested

ü This method is suitable for human plasma samples analysis

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Endogenous/Biomarker Method Validation Recommendations

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Endogenous/Biomarkers: Method Development and Validation Recommendationso No consensus or guidelines for the assay validation approaches

o Utilize the fit for purpose strategy to identify the most important elements of method development and validation studies

o Same workflow as for drug method validationØ Method development, exploratory or definitive method validation, in-

study sample analysis

o Critical to ensure integrity of data when determining biomarker concentrations

o Need to understand what is being measured, biological relevance, and data limitation in a given assay

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Endogenous/ Biomarkers: Calibration Curveq Calibration curve selection and preparation are central for the method development,

validation and its applications○ Evaluate suitability of biological matrix

Ø Matrix may contain residual levels of endogenous analytes which will effect accuracy

Ø Levels may vary because of age, gender, disease etc.Ø Screening for biological matrix with low levels of endogenous analyte which will

not interfere with quantification of analyte (≤20% LLOQ)

o Evaluate surrogate matrix (neat, artificial, stripped matrices) Ø Stable isotope internal standards can be useful Ø Investigate if concentration-response relationship of the analyte in the study

sample matrix is similar as that in a substitute matrix

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Endogenous/Biomarkers: QC Samples/Stabilityo QC Samples

Ø The concentrations of QCs should represent expected study concentrationsØ The endogenous concentration of the analyte in biological matrix evaluated

before QC preparationØ Validation QCs include both: un-spiked and spiked with known amount of

authentic analyteØ Total QC concentrations validated before running samplesØ Alternate QC samples may be used for validation

o Stability (case by case)Ø Short-term and bench-topØ AutosamplerØ Long-term stability

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Case Study 2

Global DNA Methylation as a Risk Marker for Cancer and Nutritional Health.

Yajing Hu1, Ludmila Alexandrova2, Allis S. Chien2, Megan P. Hitchins1; (1)Departments of Medicine, Stanford Cancer Institute, (2)Vincent Coates Foundation Mass Spectrometry Laboratory, Stanford University, Stanford, CA

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Background

DNA methylation in mammals occurs at the 5-carbon site of the cytosine pyrimidine ring within CpG dinucleotides

Methylation states can be modified by environmental or life-style factors and nutrients

Epigenetic modifications including DNA methylation are potentially reversible, however, it remains unknown whether dietary interventions resulting in significant weight loss will reverse pathological global methylation states to normal levels

The goal of the study is to develop, optimize and validate liquid chromatography mass spectrometry (LC-MS/MS) method to accurately and reproducibly quantify 5-methyl-2’-deoxycytidine (MdC), 2’-deoxycytidine (dC) and 2’-deoxyguanosine (dG) in hydrolyzed DNA to determine global DNA methylation levels in clinical samples

MdC

Development and Validation of LC-MS/MS Method for Quantification of MdC, dC and dG in Hydrolyzed DNA

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LC-MS/MS Method Development (Fit For Purpose)

43

SUMS seminar series

Fundamentals: Measuring concentrations of small molecules using mass spectrometry - theory and practice, Part I

Fundamentals: Measuring concentrations of small molecules using mass spectrometry - theory and practice, Part II

Fundamentals: Applications of LC/MS in small molecule drug discovery

44

Nucleoside Structures

MdC (5 Methyl 2’-deoxycytidine)

dC (2’-deoxycytidine)

dG (2’-deoxyguanosine)

15N3-dC

15N5-dG

LC-MS/MS Method

o Shimadzu LC/MS 8030o ESI+o Shimadzu LC-20ADXR Prominenceo Column: Synergy Fusion-RP 80Å, 150x2.0 mm;

4µm particles (Phenomenex)o Column T = 40°Co Flow rate: 0.2 mL/min

• SolventsA: 0.1% formic acid water

• B: 0.1% formic acid acetonitrileo Gradient: 0% to 80% B in 9 minuteso Run time 13 mino Injection volume – 10 µL

CompoundName

SRM Transition

Collision energy (V)

Dwell time (ms)

MdC 241.80>126.10 -12 100

dC 228.00>111.95 -12 50

dG 267.80>151.95 -15 50

15N3-dC 231.00>115.10 -10 50

15N5-dG 275.00>157.10 -10 50

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DNA Extraction and Hydrolysis Procedure

DNA extraction and HydrolysisØ Buffy coat DNA was extracted using standard

phenol chloroform methodØ 0.5 µg of DNA was then hydrolyzed by a 3-

step enzyme digestion

Calibration curveØ Calibration curve was prepared by spiking

standard solutions into DNA buffer mixture and was treated in the same way as DNA samples including enzymatic hydrolysis.

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q Internal standards 15N3-dC and 15N5-dG were added to the hydrolysates.

q DNA digests and calibration standards were diluted with water and filtered to remove large proteins.

q Prepared samples were injected into LC-MS

DNA amount and hydrolysis protocol optimized during LC-MS/MS method development

Calibration Curve Ranges and QC Samples

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Analyte Calibration ranges

MdC 0.746 – 299 ng/mL 3.1 nM - 1.24 µM

dC 18.7 – 1490 ng/mL 82.4 nM – 6.56 µM

dG 18.7 – 1490 ng/mL 70.0 nM – 5.58 µM

QC DNA Methylation Level

QC1-LLOQ Human non methylated DNA

QC2-Mid Pooled human PBL DNA

QC3-High-1 Human fully methylated DNA from HCT 116

QC4-High-2 Human fully methylated DNA from Millipore

PBL: peripheral blood lymphocyte DNA

Non methylated, fully methylated human DNA standards and pooled human PBL DNA ( baseline) were used for the validation

Calculation of Global DNA Methylation Level

• DNA methylation (%) = MdC/(MdC+dC)• DNA methylation (%) = MdC/dG

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Assay # 1 %MdC=MdC/(MdC+dC) %MdC=MdC/dGQC1

Mean 2.64 2.78CV (%) 2.92 2.55

QC2Mean 4.20 4.43CV (%) 2.74 3.49

QC3Mean 4.99 5.38CV (%) 1.30 1.03

QC4Mean 5.61 6.04CV (%) 4.32 5.68

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LC-MS/MS Method Validation (Fit For Purpose)

Method Validation Plan

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Experiment QC for DNA methylation QC1

LLOQQC2Mid

QC3High-1

QC4High-2

Within-run precision n=6 n=6 n=6 n=6

Between-run precision (3 runs) n=4 n=4 n=4 n=4

Calibration Curve (10 points – 1 per run) Back calculated concentrations

Acceptance criteria ±20% ±15% ±15% ±15%

Experiment QC for DNA methylationQC1

LLOQQC2Mid

QC3High-1

QC4High-2

Recovery 3/3 3/3 3/3Acceptance criteria NA NA NA

Selectivity/Specificity/Matrix effectEnsure chromatographic separation for DNA and RNA nucleosides for potential

interference

Post-preparative Stability (reinjection 72hr) n=6

Acceptance criteria ±15%

Freeze-Thaw Cycles (n=3) n=4

Acceptance criteria ±20%

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Selectivity, Specificity and Matrix effect (Fit For Purpose)

LC-MS nucleoside separationEnsure chromatographic separation for DNA and RNA nucleosides for potential interference

0 50 100 150 200 250Concentration (ng/mL).

0.00

0.25

0.50

0.75

1.00

1.25

Area

Rat

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Representative MdC Calibration Curve Data: Precision and Accuracy (3 runs)

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Nominal Concentrations

(nM) Mean CV (%) Bias (%)

3.11 3.35 4.2 7.77

6.22 5.40 6.8 13.0

15.5 16.0 0.7 2.86

31.1 31.7 6.8 1.93

62.2 63.2 10.8 1.77

124 118 7.2 -5.24

311 325 2.8 4.42

498 505 2.0 1.92

622 612 5.5 -1.34

1244 1263 7.3 1.33

MdC

Calibration Curve parameters Mean CV (%)

slope 0.0041 5.53

y-int. 0.0005 7.47

r2 0.9940 0.14

Y = (0.00420620)X + (-7.91350e-005) R^2 = 0.996 W: 1/X^2

Calibration curve concentration range: 3.11 nM – 1.24 µM Lower Limit of Quantification = 3.11 nMAcceptance criteria: LLOQ ± 20%; Other levels: ±15%

QC Precision Data

Within-run precision was assessed by calculating CV values for six replicates of the validation QC samples extracted and analyzed on the same day

Between-run precision was determined by calculating CV values for 4 replicates of validation QC samples extracted and analyzed on 3 different days

Acceptance criteria: Ø LLOQ - %CV ±20%Ø %CV ±15%

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DNA Methylation %MdC=MdC/(MdC+dC)QC1 QC2 QC3 QC4

non methylated pooled blood

Fully methylated

HCT116

Fully methylated

MPAliquot (ug) 0.5 0.5 0.5 0.5

Dilution factor 1 1 1 1

Within-runMean 2.97 5.00 6.11 6.31% CV 5.1 4.58 2.60 3.45

Between-runMean 2.81 4.48 5.87 5.80% CV 7.2 12.1 13.3 7.7

Extraction Recovery: MdC, dC and dG

Recovery samples o Add analyte and internal standard prior to

hydrolysis and extraction (Extracted )o Control samples: Extract sample spiked with

IS and analyte added after hydrolysis and extraction (Post-Extracted)

Absolute recovery determined based on analyte/IS area ratio

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nM % Recovery MdC

Low (15.5) 100Mid (125) 103High (622) 110

dCLow (81.9) 100Mid (656) 93.3

High (3290) 107dG

Low (69.7) 103Mid (558) 96.3

High (2790) 107

Freeze-Thaw Stability

DNA methylation values are stable when stored at -80°C for at least 3 freeze/thaw cycles

No significant changes in the measured DNA methylation values outside the expected precision and accuracy of the method were found, indicating that 3 Freeze-Thaw cycles did not affect the sample integrityAcceptance criteria: Ø %CV and % Bias ±20%

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DNA Methylation %MdC=MdC/(MdC+dC)

QC2pooled blood

Aliquot (µg) 0.5Dilution factor 1

Freeze-Thaw 1Mean 4.20% CV 2.74

Freeze-Thaw 3Mean 4.27% CV 2.96

Global DNA Methylation: Method Validation Summary

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Standards QCs (Low, Mid and High) LLOQWithin-run Precision (%CV) - 2.6 - 4.58 5.1

Within-run Accuracy (% Bias) - - -

Between-run Precision (%CV) 0.7 – 10.8 7.7 – 13.3 7.2

Between-run Accuracy (% Bias) (-5.24) – 13 - -

Analyte Recovery % 93.3 - 110

Selectivity, Specificity, Matrix effect Low interference

StabilityPost Preparative 72 hours at RT in autosampler

Freeze-Thaw Cycles 3 cyclesIntermediate Solution Stability (Analytes) 4 months at -80°C

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Pilot Study: Effect of Low Fat vs. Low-Carbohydrate Diet on Global DNA Methylation

Ø DNA methylation levels were determined in 16 paired clinical samples collected during a trial of obese individuals prior to, and following the dietary intervention (Prof. C. Gardner)

Ø Results show trend of reduced methylation level 12 months after intervention (p-value=0.069, Wilcoxon signed ranks test).

DNA methylation (%) MdC/(MdC+dC)

Diet Type Baseline 12 months Difference

Low Carb 4.31 4.05 -0.26

Low Carb 4.18 3.94 -0.24

Low Carb 4.6 3.8 -0.80

Low Carb 4.06 3.92 -0.14

Low fat 4.2 3.9 -0.30

Low fat 3.96 4.07 0.11

Low fat 4.06 4.05 -0.01

Low fat 3.77 3.82 0.05

ResultsLC-MS/MS method to accurately and reproducibly measures global DNA methylation

levels developed and validated.

Fit for purpose approach was used to validate and monitor assay performance.▪ DNA buffer matrix was evaluated and used for calibration curve preparation.▪ Non-methylated and fully methylated human DNA commercial standards were

utilized as quality control samples

LC-MS/MS method was successfully applied to a pilot diet intervention study to investigate global DNA methylation levels as a potential marker to monitor health/disease status

Preliminary results showed trend of reduced methylation levels 12 months after dietary intervention (p-value=0.069, Wilcoxon signed ranks test)

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ConclusionØ Method validation is an important tool in drug discovery and development

Ø Assay performance parameters by their design may give an idea of method capabilities and limitations that can be experienced during routine sample analysis

Ø Fit for purpose validation is faster and less labor intensive and used extensively in drug discovery and biomarker research

Ø A practical fit for purpose validation delivers quality results to make informed project decisions

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ReferencesLiterature:

○ Bioanalytical Method Validation; Guidance for Industry -https://www.fda.gov/media/70858/download

○ Handbook of LC-MS Bioanalysis. Best Practices, Experimental Protocols and Regulations by Li W., Zhang J., and Tse F.L.S.

○ Biomarkers in Drug Discovery and Development: A Handbook of Practice, Application, and Strategy, Second Edition by Rahbari R., Van Neiwaal J. and Bleavins M. R.

Standards:○ Cambridge Isotope Labs - www.isotope.com○ Cerriliant - www.cerilliant.com○ Anaspec – www.anaspec.com○ Sigma-Aldrich – www.sigmaaldrich.com

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Acknowledgements

SUMS staff

Stanford Dean of Research

Vincent and Stella Coates Foundation

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Proteomics

Ryan Leib, PhDFang Liu, PhD

Rowan Matney, BAKratika Singhal, MS

Protein IDQuantitative – PRM, TMT

Protein interactionsProtein structure

Phosphoproteomics, PTMs

Small Molecule

Ludmila Alexandrova, PhDKarolina Krasinska, MS

Beryl Xia, PhD(Theresa McLaughlin, MS)

Absolute quantitationTargeted metabolomics

PK, Stability studies Metabolite ID Intact protein

Open Access

Theresa McLaughlin, MS(Beryl Xia, PhD)

GC/MSLC/MSHRMS

MALDI-TOF

Director – Allis Chien, Ph.D.

Applications

People

SUMS Group

Accounting Associate – William Lee, BS62

July 9, 2020In-depth shotgun triacylglyceride profilingSpeaker: Matias Cabruja, PhD – Dept. of Genetics, Stanford University School of Medicine

July 16, 2020Improved protein and PTM characterization with a practical electron-based fragmentation on Q-ToFs and ion mobility separationsSpeaker: Prof. Joe Beckman, PhD – Dept. of Biochemistry & Biophysics, Oregon State University

Stay tunedMore webinars on Thursdays, noon-1pm

Details & registration: mass-spec.stanford.edu/events

Requests welcome!

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http://mass-spec.stanford.edu

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We are Stanford University Core Lab

iLab help: - SUMS website - William Lee

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