Funding Opportunity Number: NIJ-2014-3732 

Development and Validation of Two Innovative Quantitative 

Liquid Chromatography Tandem Mass Spectrometry Methods 

for Forensic Toxicology Laboratories: Novel Analysis of 

Designer Drugs and Simultaneous Method for Cocaine and 

Opioids in Biological Matrices

Submitted via Grants.gov to: 

U.S. Department of Justice 

Office of Justice Programs

National Institute of Justice

810 Seventh St., NW 

Washington, DC 20531 

Submitted by:

Virginia Department of Forensic Science

700 North Fifth St. 

Richmond, VA 23219 

December 12, 2014 

Principal Investigator and Technical Point of Contact: 

[Redacted]

Administrative Point of Contact: 

[Redacted]
TABLE OF CONTENTS

SECTION PAGE NUMBER

PROGRAM NARRATIVE

Statement of the Problem 1 

Purpose, Goals, and Objectives 

Review of Relevant Literature

Project Design and Implementation 3 

Method Development 

Method Validation

Dissemination Strategy 8 

Planned Scholarly Products 

Potential Impact 8 

Capabilities/Competencies 9 

Management Plan and Organization 

APPENDICES:

Appendix A - References

Appendix B - Target Compounds and Internal Standards

Appendix C - Supporting Data

Appendix D - Key Personnel and Qualifications

Appendix E - Project Timeline

Appendix F - Data Archiving Plan

Appendix G - List of Previous and Current NIJ Awards

Appendix H - Privacy Certificate

OTHER ATTACHMENTS TO APPLICATION IN GRANTS.GOV: 

Project Abstract

Proof of Laboratory Accreditation 

Budget Detail Worksheet

Budget Narrative

Applicant Disclosure of Pending Applications 

Research and Evaluation Independence and Integrity

Standard Assurances

Certifications 
1 

Statement of the Problem 

With the advent of liquid chromatography tandem mass spectrometry (LC-MS-MS) technology, 

and an increasing number of toxicology laboratories utilizing these instruments, it is imperative 

to have methods validated for biological matrices to ensure accurate results are being obtained 

and reported for quantitative data. The Virginia Department of Forensic Science (VADFS) has 

made a significant investment in the procurement of LC-MS-MS systems for the Toxicology 

Sections. Extensive work has been performed within the agency focusing on the best practices 

for the development, validation, and implementation of new quantitative LC-MS-MS methods. 

The goal of this research project is to develop and validate two quantitative LC-MS-MS methods

for the analysis of whole blood and additional biological matrices in accordance with guidelines 

promulgated by the Scientific Working Group for Forensic Toxicology (SWGTOX) Standard 

Practices for Method Validation in Forensic Toxicology.1 The objectives for this project are: 1) 

develop and validate a technique that addresses the recent proliferation of designer drugs such as 

cannabimimetic agents and designer stimulants, 2) develop and validate a combined method for 

cocaine and its metabolites and opioids, and 3) disseminate the methods to the toxicology 

community. 

The inherent increased sensitivity and selectivity of LC-MS-MS makes the technology more 

advantageous over gas chromatography mass spectrometry (GC-MS) for the analysis of 

biological specimens which is traditionally viewed as the “gold standard” in forensic toxicology. 

The superiority of LC-MS-MS is not only due to the increased sensitivity and selectivity, but 

also in the sample preparation and ionization.2 GC-MS often requires time-consuming 

derivatization of compounds prior to analysis, which directly impacts laboratory efficiency. Also, 

due to the high temperatures utilized in the injection port of GC-MS instruments, thermally labile 

compounds are difficult to quantitatively evaluate. Also within the injection port, a high degree 

of fragmentation occurs, making spectral interpretation difficult without database searching 

capabilities.3 The two validated methods will directly impact the criminal justice system in a 

multitude of ways by providing a new quantitative analysis method that currently does not exist 

for designer drugs as well as increasing laboratory productivity and decreasing turnaround times 

for cocaine and opioid cases. 

An increased submission of designer drugs in VADFS Controlled Substances Section indicates a 

need for a robust quantitative method for these drugs in the Toxicology Section. Since 

September 2012, VADFS’s Controlled Substances Section has confirmed 680 cases containing 

designer drugs. Currently, VADFS does not have a method validated for the quantitative 

evaluation of these compounds in biological matrices. Designer drugs, including cannabimimetic 

compounds and designer stimulants are becoming an increased concern in the United States.

These structural analogues are manufactured to mimic the effects of scheduled compounds 

posing a twofold threat to the criminal justice system.

4-8 These drugs pose legal concerns due to 

their ability to avoid provisions of drug laws and they have a high potential for abuse, which 

impacts toxicological analysis.

9 In 2012, federal legislation enacted Senate Bill 3187, which 

includes the addition of twenty-six synthetic drugs to the list of Schedule I substances to the 

Controlled Substances Act.10 

Currently, the literature has limited information pertaining to concentrations associated with the 

effects of these drugs making interpretation for driving under the influence of drugs (DUID) and 
2 

medicolegal death investigation nearly impossible.

11, 12 The implementation of a quantitative 

method for biological matrices validated to exceed the SWGTOX Standard Practices for Method 

Validation in Forensic Toxicology guidelines will enable the reporting and dissemination of 

blood and tissue concentrations within the forensic science community to aid in the 

establishment of human subject concentration information. The target compounds will include 

those indicated with high prevalence in VADFS Controlled Substances Section, which have been 

historically tracked since September 2012. The acquisition of concentration data will provide 

information that will be advantageous for interpreting the meaning of the quantitative results for 

both DUID cases and death investigation casework, nationwide. 

Not only is it crucial for forensic laboratories to validate and implement methods for the 

quantitative assessment of newly abused/developed compounds such as designer drugs, it is also 

important to evaluate historical methods to increase laboratory productivity and efficiency. The 

Toxicology Section of VADFS analyzes approximately 2500 driving under the influence/driving 

under the influence of drugs (DUI/DUID), 4600 death investigation, and 300 non-implied 

consent police cases per year. Approximately eight percent of the cases analyzed are reported 

with quantitative values associated with cocaine, benzoylecgonine, and cocaethylene and 

approximately thirty one percent are reported with quantitative values associated with opioids. 

Many cases submitted involve a combination of drugs that require multiple extractions and 

quantitative analyses. Therefore, combining analytical methods will result in backlog reduction 

and decreased turnaround times. 

The literature contains a variety of methods for the analysis of cocaine and its metabolites using 

LC-MS-MS. The matrices evaluated include urine, serum, plasma, whole blood, brain tissue, 

hair, saliva, and meconium.13-18 The literature also contains similar information for LC-MS-MS 

analysis of opioids in various matrices.19-23 Although methods exist for the simultaneous analysis 

of cocaine and opioids in hair, plasma, placenta, and umbilical cord, limited literature is available 

for an equivalent method in whole blood and matrices received in medicolegal death 

investigations such as liver and tissue.7, 24 In addition to the limited matrices evaluated, the 

methods are not validated to meet current forensically acceptable method validation guidelines 

published by SWGTOX. These guidelines are anticipated to become validation requirements 

with the advent of the Organization of Scientific Area Committees (OSAC), which was 

constructed by the National Institute of Standards and Technology (NIST). Therefore, there is a 

significant need for the development and validation of a simultaneous cocaine and opioid 

quantitative LC-MS-MS method in whole blood and other biologically significant matrices that 

meets the scope and standards of the forensic community. 

Currently, VADFS utilizes GC-MS for the analysis of cocaine and opioids in biological matrices 

individually. Both extractions utilize a significant volume of blood for analysis, totaling four 

milliliters for the analysis of the two drug classes. The extractions include a solid phase 

extraction as well as a time-consuming derivatization prior to GC-MS analysis. Given the nature 

of limited sample volume in forensic toxicology applications, re-evaluation of historical methods 

to establish multi-drug class methods, with decreased sample volume, using modern data 

analysis software will have a significant impact on laboratory efficiency. The target compounds 

will include the compounds currently evaluated in the VADFS Toxicology Section in multiple 

methods as well as the addition of other targets that may be useful in circumstances of 

medicolegal death investigation such as anhydroecgonine methyl ester (AEME) and acetyl 
3 

fentanyl. The newly validated method will contain cocaine and its metabolites as well as natural, 

semi-synthetic, and synthetic opioids enabling the combination of four current VADFS methods 

into one overarching method. The increased efficiency obtained, from the development and 

validation of a quantitative LC-MS-MS that simultaneously evaluates cocaine and opioids, will 

directly impact the criminal justice system. The increased efficiency will reduce turnaround 

times for case completion enabling Certificates of Analysis to be issued more rapidly. This will 

also be advantageous for medicolegal death investigations, enabling for a more timely cause of 

death determination by medical examiners. 

This proposed project has the potential to significantly impact the forensic science community. 

Upon completion of the project, two methods will be fully validated to exceed the generally 

accepted SWGTOX validation guidelines. The methods will include a comparison and validation 

of three different sample extraction techniques, including solid phase extraction, liquid-liquid 

extraction, and protein precipitation as well as complete validations not only in whole blood, but 

also other common death investigation biological matrices. The comparisons of sample 

preparation techniques within an individual method will enable for the determination of the most 

efficient, specific, and cost-effective method that can be immediately implemented into any 

forensic toxicology laboratory across the United States. This proposed project will facilitate a 

transition from independent laboratory developed methods to universally standardized methods, 

enabling a more globalized consistent approach within the toxicology community. 

Project Design and Implementation

Within this research project, two methods will be developed and validated to exceed the 

SWGTOX Standard Practices for Method Validation in Forensic Toxicology guidelines. The 

method development and validation process will be similar for each method to establish an 

evaluation of sample preparation techniques as well as optimal instrumental conditions that will 

not only demonstrate accuracy and precision, but also a level of efficiency and cost analysis for 

each method. This will be accomplished by completing a validation of three sample preparation 

techniques including solid phase extraction, liquid-liquid extraction, and protein precipitation for 

each quantitative method. Finally, the Uncertainty of Measurement will be evaluated for each 

target contained within the two methods validated enabling further confidence in the methods. 

The SWGTOX Standard Practices for Method Validation in Forensic Toxicology guidelines 

were first published in May 2013 and have become generally accepted as validation guidelines in 

forensic laboratories. The validation of these two proposed methods will exceed the validation 

requirements set forth by SWGTOX. The project design is a twofold process consisting of 

method development prior to method validation. The following experiments will be completed to 

establish objective evidence that demonstrates the two methods are capable of contributing 

reproducible and robust methods to the forensic science community. 

Method Development

Instrumental Method Optimization

An Agilent Technologies 1290 Infinity liquid chromatography system coupled to a 6430 

quadrupole mass spectrometer will be utilized for the development and validation of these two 
4 

methods. The Agilent Technologies MassHunter Optimizer software as well as peer-reviewed 

literature references will be used to optimize ion selection for each target as well as develop 

optimal mass spectrometer conditions. Appendix B delineates a proposed list of target 

compounds and internal standards for each method. Upon optimization of individual target 

compounds, the liquid chromatography separation will be developed for all targets contained 

within in the method. A standard reverse phase Agilent Technologies Poroshell 120 EC-18 (2.1 x 

100 mm, 2.7μm pore size) column will be used as the stationary phase. If acceptable separation 

is not achieved with standard reverse phase chromatography, a more selective column will be 

used such as a phenyl-hexyl or diphenyl stationary phase column. Also, mobile phase 

composition, gradient, and flow rates will be adjusted to achieve optimal separation of the target 

compounds. 

Upon completion of instrumental method development, a neat methanolic calibration curve will 

be prepared for each method containing all targets as well as associated deuterium labeled 

internal standards. The calibration range for the designer drugs method will encompass a wide 

concentration range (at minimum two orders of magnitude) since limited information is known 

about relative biological concentrations in human subjects. The cocaine and opioids method will 

contain a concentration range that encompasses therapeutic, toxic, and lethal ranges. The neat 

methanolic calibration analysis will serve to ensure proper instrument performance without 

contribution from the matrix. 

Sample Preparation Extraction 

Sample preparation is a pivotal component to laboratory efficiency. To enable a thorough 

evaluation of the newly developed methods, at minimum, three extraction techniques will be 

developed and evaluated. Traditionally, solid phase extractions and liquid-liquid extractions are 

used extensively in forensic toxicology laboratories. The utilization of protein precipitation is 

becoming a useful extraction tool in forensic toxicology because of the limited sample volume 

required and the rapid nature of the extraction. Therefore, at minimum, a solid phase extraction, 

liquid-liquid extraction, and protein precipitation extraction will be developed for each method. 

The extraction methods will be developed for whole blood since the majority of evidentiary 

samples submitted are whole blood. The methods will then be extended to other matrices 

received in medicolegal death investigations such as liver and tissue where available. 

During the development of the sample extraction methods, several parameters will be optimized 

and evaluated including, but not limited to, sample volume, extraction complexity, and extraction 

time. The sample volume will be adjusted for each method to determine the smallest sample 

volume possible to still maintain the integrity of the calibration range. The methods will be 

developed to have minimal complexity and the three methods will be compared for complexity 

by evaluating the number of steps for each extraction. The extraction time will be kept to a 

minimum for each method and a comparison of overall sample extraction time will be compared 

for each method. This will be significantly impacted by incubation times, solid phase extraction 

steps, and centrifugation times. The goal is to create three methods with limited sample volume, 

minimal complexity, and high efficiency. Upon development of three optimal extraction methods 

for each of the proposed methods, an extensive validation will be completed as delineated in 

following section of this proposal. Example calculations are provided in Appendix C, which also 

delineates a validation summary document. 
5 

Method Validation 

Accuracy/Precision

The accuracy and precision of the methods will be evaluated using pooled matrix samples. To 

evaluate accuracy, three concentrations distributed equally across the calibration range will be 

analyzed in triplicate over a minimum of five batches. The percent accuracy shall not exceed ±20 

% accuracy at each concentration level. All samples evaluated for accuracy will be included into 

the accuracy determination. The same data used in the accuracy studies will also be used to 

determine the within-run and intermediate precision of the methods. 

Precision will be expressed as the coefficient of variation (% CV) and two different types of 

precision studies will be assessed during validation: within-run precision and intermediate 

precision. To assess within-run precision, the precision of each batch will be evaluated whereas 

intermediate precision will evaluate the precision of the method over multiple batches. The 

greatest within-run precision over each batch will be utilized for the within-run precision of the 

process. Precision, like accuracy, should not exceed ±20 % precision for within-run and 

intermediate precision. 

Sensitivity 

The limit of detection and limit of quantitation will be evaluated for each method. To determine 

the target limit of detection and quantitation, serial dilutions will be prepared and analyzed to 

determine the lowest concentration that is capable of achieving acceptable predetermined 

identification criteria. Once estimated, triplicate determinations of fortified samples from at least 

three different sources will be assessed to verify the concentration meets the identification 

criteria. The predetermined acceptance criterion for limit of detection is a retention time within ± 

5% of the average of the calibrator retention time, a qualifier ion ratio within ±20 % of the 

average ratio of the calibrators, and a signal to noise ratio greater than three to one. The 

acceptance criterion for the limit of quantitation is the same as the limit of detection for retention 

time and ion qualifier ratios, but the signal to noise must be greater than ten to one, in addition 

the back calculated concentration must be within ±20 % of the target concentration. 

Linearity and Calibration Model 

The calibration model for each target compound within the two methods will be established by 

determining the range of analyte concentrations over which the method will be used. The 

calibration range will be evaluated using at minimum seven calibrators across the calibration 

range. To establish the calibration model, a minimum of six replicate determinations will be 

utilized. Although the least squares model for regression is preferred, the best and simplest 

model (e.g. weighted, non-weighted, liner, quadratic) that fits the data will be chosen. The model 

will be established by residual plot analysis as well as statistical comparisons. The origin will be 

ignored in all calibration models, the correlation coefficient must also be ≥ 0.985, and the back 

calculated calibrator concentrations shall be within ±20 % of the target concentration for 

acceptance of the calibration model. 
6 

The statistical analysis techniques that will be utilized in the determination of the calibration 

model for each target will be the analysis of variance (ANOVA). The standard deviation of the 

residuals will be compared between the linear, quadratic, weighted, and non-weighted calibration 

models. The t-test and f-test will be utilized to determine statistically significant differences 

between linear and quadratic calibration models. If the two groups are determined not to be 

statistically different, a linear calibration model will be applied to the target. If the two groups 

are determined to be statistically different, the quadratic calibration model will be applied. To 

determine weighting of the calibration model, the sum of the relative residual errors will be 

evaluated. The weighting that minimizes the sum of relative residual errors for all batches 

evaluated will be the weighting model applied to the target. 

Ion Suppression/Enhancement 

Ion suppression and enhancement will be addressed with neat standards and post-extraction 

fortified samples. Two different sets of samples will be prepared and their peak areas will be 

compared between sets. Neat standards, at low, medium, and high concentrations, will be 

prepared in neat extraction solvent and injected a minimum of six times for each concentration 

level. The responses will be averaged for the three different concentrations. A minimum of ten 

pairs of post-extraction fortified samples, at three different concentrations, will be prepared to 

compare to the neat standards. The samples for each pair of post-extraction fortified samples will 

be from different sources. Post-extraction fortified samples are blank matrix samples that are 

extracted and then fortified with analytes after extraction. The responses will be averaged for the 

two concentrations and the ratio between the averages of the sets will then be used to assess ion 

suppression or enhancement. 

Recovery 

Recovery will be represented as a percentage of the analyte response after sample preparation 

compared to that of a solution containing the analyte at a concentration corresponding to 100 %. 

The solution containing the 100 % (double blank) analyte concentration will be prepared by 

extracting a minimum of six high, medium, and low concentrations of post extraction fortified 

samples. A minimum of six extractions of a high, medium, and low concentration of samples 

fortified prior to extraction will enable a recovery comparison. The post extraction fortified 

samples nullify the matrix effect enabling an accurate recovery comparison.

Carryover

Carryover will be evaluated with solvent blanks injected immediately following progressively 

higher concentrations of analyte of interest fortified into blank matrix. A solvent blank shall 

immediately follow a fortified sample in the injection sequence. The highest analyte 

concentration at which no analyte carryover is observed in the matrix blank is determined to be 

the concentration at which the method is free from carryover. This concentration will then be 

confirmed using triplicate analysis. 

Interferences 
7 

Interferences from several sources will be evaluated in the validations of these methods. 

Interferences associated with endogenous compounds will be evaluated by analyzing a minimum 

of ten negative matrix samples from different sources without the addition of internal standard or 

analyte. Interferences from the contribution of high concentrations of analyte to internal standard 

and high concentrations of internal standard to analyte will also be evaluated. This will be 

accomplished by evaluating three sources of matrix fortified with high concentration of internal 

standard and no target compounds and high concentration of target compounds with no internal 

standard. Also, high concentrations of target compounds will be evaluated independently to 

assess contribution to other compounds within the method. Interferences will also be evaluated 

by analyzing commonly encountered analytes. A minimum of three matrix samples will be 

fortified with commonly encountered drugs in the VADFS Toxicology Section as well as 

metabolites and other structurally similar compounds. The void of peaks is indicative of no 

interferences associated with endogenous compounds, target compounds, and commonly 

encountered compounds. 

Dilution Integrity 

The effect of sample dilution will be assessed using both large and small volume dilutions where 

applicable. Large volume dilutions are useful for evidentiary samples with sufficient volume, but 

concentration above the upper limit of detection. The small volume dilution is necessary for 

evidentiary samples containing limited sample volumes that do not meet the volume 

requirements of the method. The dilution limit will be determined by preparing fortified pooled 

samples and analyzing the dilutions in triplicate. The dilutions evaluated will be common 

dilutions performed on evidentiary samples such as (1:2, 1:5, and 1:10). Accuracy and precision 

studies will be utilized to determine if the dilution meets the predetermined acceptance criteria of 

±20 % of the target concentration for accuracy and precision. 

Stability 

The stability of extracted samples that are not analyzed immediately will be evaluated. At 

minimum, two concentrations of samples will be extracted and analyzed at minimum every 

twenty four hours for a seven day period with triplicate injections at each time point. Samples 

will be immediately analyzed following extraction for day one instrumental response 

determination. The samples will then remain in the autosampler of the instrument in normal 

laboratory conditions and injected over the seven day period. The instrumental response will be 

evaluated for each target at each time point. Day one will be considered 100 % and subsequent

injections will be compared to the initial instrumental response. The samples will be considered 

stable if the average signal of the triplicate injections for a time point does not increase above 

120 % or decrease below 80 % of the original response. This experiment will simulate the 

stability of the targets if an instrumental run is abruptly interrupted or delayed. 

Uncertainty of Measurement 

The robustness and reproducibility of the two validated methods will be addressed during the 

collection of data for the estimation of uncertainty of measurement. During the validation, 

controls will be analyzed within every validation batch. Control charts will be created to evaluate 

the historical variance of the methods over the validation period. Also, multiple scientists will 
8 

conduct an analysis of each method including the analysis of calibrators, controls, and pooled 

samples to further assist with an accurate estimation of historical data. Uncertainty of 

measurement budgets will be developed for every target within the methods including individual 

budgets for each extraction technique in accordance with the ASCLD/LAB Policy on 

Measurement Uncertainty and ISO/IEC 17025:2005 General Requirements for the Competence 

of Testing and Calibration Laboratories.25, 26 

Dissemination Strategy 

Upon completion of the project, the information will be disseminated using various forums 

including publication in peer-reviewed journals and presentations. Publications will be 

submitted to a peer-reviewed journal such as the Forensic Science International, Journal of 

Chromatography B, or the Journal of Analytical Toxicology. Also, the work completed within 

the scope of this project will be disseminated in the form of presentations at scientific 

conferences such as the Society of Forensic Toxicologists (SOFT) Conference. There is also the 

potential for dissemination to a broad audience by presenting the work using an international 

webinar forum, such as Research Triangle Institute. VADFS has previously presented two 

international webinars on the validation of quantitative methods. Finally, VADFS publishes all 

departmental Procedures Manuals on the Department’s website providing a continuous means of 

dissemination of information to its customers, other agencies, or interested parties. Interested 

parties seeking validation information have the ability to contact the Department to obtain copies 

of validation information, creating a seamless transition of methods to other laboratories 

Potential Impact 

This project has the potential to significantly impact the forensic science community in multiple 

ways. Upon completion of the project, two methods will be fully validated to exceed the 

generally accepted SWGTOX validation guidelines. The two methods will include a comparison 

and validation of three different sample extraction techniques as well as complete validations not 

only in whole blood, but also other common death investigation matrices. The comparisons of 

sample preparation methods will enable for the determination of the most efficient, accurate, and 

cost-effective method that can be immediately implemented into any forensic toxicology 

laboratory. 

The validation of a designer drug method including cannabimimetic compounds and cathinone 

analogues based on the SWGTOX guidelines will enable the forensic community to collect 

biological concentration information for these increasingly popular compounds. The culmination 

of data will aid the forensic community in gathering essential information for interpretation of 

DUID cases as well as medicolegal death investigations. 

The validation of a combined cocaine and opioid method has the potential to help decrease 

laboratory backlogs and turnaround times by decreasing the number of analyses needed to 

evaluate an individual case. Also, the method has the potential to utilize less sample volume than 

current methods that require significant volumes, which is critical in forensic applications where 

case sample volume is limited. The validation will also increase awareness of best practices to 

the forensic community given the comparative nature of the project as well as inclusion of the 

estimation of uncertainty of measurement within the validation. 
9 

Capabilities/Competencies 

[Redacted PI information] 

A Forensic Laboratory Specialist II will be hired to perform some of the experimentation 

within this project. The specialist will be under the direct supervision of [PI]. It is 

anticipated that the specialist will spend no more than twenty nine hours per week working on 

the project. Please see Appendix D for a biographical sketch of the Forensic Laboratory 

Specialist II position. 

The Virginia Department of Forensic Science Toxicology Section currently has five Agilent 

Technologies liquid chromatography tandem mass spectrometers. One of these instruments is 

currently utilized for method development and validation. Therefore, no new analytical 

instrumentation must be requisitioned for the purpose of this project. The laboratory 

also currently has all other equipment needed for successful management and validation 

of the proposed methods, which is demonstrated by the four previously validated and 

implemented methods within the Department. Project timeline and data archiving plans are 

delineated in Appendix E and Appendix F respectively. The principal investigator also 

possesses the statistical knowledge required for method validations of this magnitude. 

Therefore, statisticians outside of VADFS are not required within the scope of this project. 

VADFS already possesses a working relationship with the Virginia Office of the Chief 

Medical Examiner for the acquisition of available death investigation matrices, such as liver 

and tissue. 
APPENDIX A 

REFERENCES

1. Scientific Working Group for Toxicology, Standard Practices for Method Validation in

Forensic Toxicology SWGTOX: 2013; pp 1-52.

2. French, D., The challenges of LC-MS/MS analysis of opiates and opioids in urine. Bioanalysis

2013, 5 (22), 2803-20.

3. Garcia, R. C.; Dati, L. M.; Fukuda, S.; Torres, L. H.; Moura, S.; de Carvalho, N. D.;

Carrettiero, D. C.; Camarini, R.; Levada-Pires, A. C.; Yonamine, M.; Negrini-Neto, O.; Abdalla,

F. M.; Sandoval, M. R.; Afeche, S. C.; Marcourakis, T., Neurotoxicity of anhydroecgonine

methyl ester, a crack cocaine pyrolysis product. Toxicol Sci 2012, 128 (1), 223-34.

4. Elsohly, M. A.; Gul, W.; Wanas, A. S.; Radwan, M. M., Synthetic cannabinoids: analysis and

metabolites. Life Sci 2014, 97 (1), 78-90.

5. Ammann, J.; McLaren, J. M.; Gerostamoulos, D.; Beyer, J., Detection and quantification of

new designer drugs in human blood: Part 1 - Synthetic cannabinoids. J Anal Toxicol 2012, 36

(6), 372-80.

6. Goebel, A.; Boehm, M.; Kirchherr, H.; Kuhn-Velten, W. N., Simultaneous identification and

quantification of synthetic cannabinoids (cannabimimetics) in serum, hairm and urine by rapid

and sensitive HPLC tandem mass spectrometry screenings: overview and experience from

routine testing. J Lab Med 2013, 37 (4), 167-80.

7. de Castro, A.; Diaz, A.; Pineiro, B.; Lendoiro, E.; Cruz, A.; Lopez-Rivadulla, M.; Concheiro,

M., Simultaneous determination of opiates, methadone, amphetamines, cocaine, and metabolites

in human placenta and umbilical cord by LC-MS/MS. Anal Bioanal Chem 2013, 405 (12), 4295-

305.

8. Yanes, E. G.; Lovett, D. P., High-throughput bioanalytical method for analysis of synthetic

cannabinoid metabolites in urine using salting-out sample preparation and LC-MS/MS. J

Chromatogr B Analyt Technol Biomed Life Sci 2012, 909, 42-50.

9. Swortwood, M. J.; Boland, D. M.; DeCaprio, A. P., Determination of 32 cathinone derivatives

and other designer drugs in serum by comprehensive LC-QQQ-MS/MS analysis. Anal Bioanal

Chem 2013, 405 (4), 1383-97.

10.One Hundred Twelfth Congress of the United States of America, Food and drug

administration safety and innovation act. S. 3187, Subtitle D, Sec. 1152: 2012.

11. Prosser, J. M.; Nelson, L. S., The toxicology of bath salts: a review of synthetic cathinones. J

Med Toxicol 2012, 8 (1), 33-42.
12. Hasegawa, K.; Wurita, A.; Minakata, K.; Gonmori, K.; Nozawa, H.; Yamagishi, I.; Suzuki,

O.; Watanabe, K., Identification and quantification of a new cathinone designer drug PV9 in an

"aroma liquid" product, antemortem whole blood and urine specimens, and a postmortem whole

blood speciment in a fata poisoning case Forensic Toxicol 2014, 32, 243-50.

13. Napolentano, S.; Montesano, C.; Compagnone, D.; Curini, R.; D'ascenzo, G.; Roccia, C.;

Sergi, M., Determination of illicit drugs in urine and plasma by micro-SPE followed by HPLCMS/MS. Chromatographia 2012, 75, 55-64.

14. Xia, Y.; Wang, P.; Bartlett, M. G.; Solomon, H. M.; Busch, K. L., An LC-MS-MS method

for the comprehensive analysis of cocaine and cocaine metabolites in meconium. Anal Chem

2000, 72 (4), 764-71.

15. Moore, C.; Coulter, C.; Crompton, K., Determination of cocaine, benzoylecgonine,

cocaethylene and norcocaine in human hair using solid-phase extraction and liquid

chromatography with tandem mass spectrometric detection. J Chromatogr B Analyt Technol

Biomed Life Sci 2007, 859 (2), 208-12.

16. Johansen, S. S.; Bhatia, H. M., Quantitative analysis of cocaine and its metabolites in whole

blood and urine by high-performance liquid chromatography coupled with tandem mass

spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 2007, 852 (1-2), 338-44.

17. Berg, T.; Lundanes, E.; Christophersen, A. S.; Strand, D. H., Determination of opiates and

cocaine in urine by high pH mobile phase reversed phase UPLC-MS/MS. J Chromatogr B

Analyt Technol Biomed Life Sci 2009, 877 (4), 421-32.

18. Alves, M. N.; Zanchetti, G.; Piccinotti, A.; Tameni, S.; De Martinis, B. S.; Polettini, A.,

Determination of cocaine and metabolites in hair by column-switching LC-MS-MS analysis.

Anal Bioanal Chem 2013, 405 (19), 6299-306.

19. Rook, E. J.; Hillebrand, M. J.; Rosing, H.; van Ree, J. M.; Beijnen, J. H., The quantitative

analysis of heroin, methadone and their metabolites and the simultaneous detection of cocaine,

acetylcodeine and their metabolites in human plasma by high-performance liquid

chromatography coupled with tandem mass spectrometry. J Chromatogr B Analyt Technol

Biomed Life Sci 2005, 824 (1-2), 213-21.

20. Karinen, R.; Andersen, J. M.; Ripel, A.; Hasvold, I.; Hopen, A. B.; Morland, J.;

Christophersen, A. S., Determination of heroin and its main metabolites in small sample volumes

of whole blood and brain tissue by reversed-phase liquid chromatography-tandem mass

spectrometry. J Anal Toxicol 2009, 33 (7), 345-50.

21. Coles, R.; Kushnir, M. M.; Nelson, G. J.; McMillin, G. A.; Urry, F. M., Simultaneous

determination of codeine, morphine, hydrocodone, hydromorphone, oxycodone, and 6-

acetylmorphine in urine, serum, plasma, whole blood, and meconium by LC-MS-MS. J Anal

Toxicol 2007, 31 (1), 1-14.
22. Gergov, M.; Nokua, P.; Vuori, E.; Ojanpera, I., Simultaneous screening and quantification of

25 opioid drugs in post-mortem blood and urine by liquid chromatography-tandem mass

spectrometry. Forensic Sci Int 2009, 186 (1-3), 36-43.

23. Steuer, A. E.; Forss, A. M.; Dally, A. M.; Kraemer, T., Method development and validation

for simultaneous quantification of 15 drugs of abuse and prescription drugs and 7 of their

metabolites in whole blood relevant in the context of driving under the influence of drugs--

Usefulness of multi-analyte calibration. Forensic Sci Int 2014, 244C, 92-101.

24. Imbert, L.; Dulaurent, S.; Mercerolle, M.; Morichon, J.; Lachatre, G.; Gaulier, J. M.,

Development and validation of a single LC-MS/MS assay following SPE for simultaneous hair

analysis of amphetamines, opiates, cocaine and metabolites. Forensic Sci Int 2014, 234, 132-8.

25. ASCLD/LAB Policy on Measurement Uncertainty ASCLD/LAB-International, Ed. 2013.

26. International Organization for Standardization/International Electrotechnical Commission,

International standard ISO/IEC 17025:2005 General requirements for the competence of testing

and calibration laboratories In ISO/IEC 17025:2005(E), Second ed..
APPENDIX B

TARGET COMPOUNDS AND INTERNAL STANDARDS

Proposed compounds for the quantitative analysis of designer drugs method using LC-MS-MS. 

The method will include, but is not limited to, the compounds delineated in the table. 

Compounds for LC-MS-MS Designer Drug Quantitative Method

Targets Internal Standards 

AB-CHMINACA JWH-018 4-Hydroxypentyl Metabolite-D5

FUB-144 JWH-073 3-Hydroxybutyl Metabolite-D5

AB-PINACA AM2201 4-Hydroxypentyl Metabolite-D5

AB-FUBINACA Butylone-D3

5-Fluoro-THJ Ethylone-D5

FUBIMINA Methylone-D3

PB-22 Mephedrone-D3

5-Fluoro PB-22

BB-22

UR-144

XLR11

THJ2201

HU-210

JWH-018

JWH-073

AM1248

Butylone

Ethylone

Methylone

Mephedrone

Pentedrone

Alpha-Pyrrolidinonpentiophenone

Methcathinone

Bupropion

Methylenedioxypyrovalerone
Proposed compounds for combined quantitative cocaine and opioid method using LC-MS-MS. 

The method will include, but is not limited to, the compounds delineated in the table. 

Compounds for LC-MS-MS Cocaine and Opioid Quantitative Method

Targets Internal Standards 

Cocaine Cocaine-D3

Benzoylecgonine Benzoylecgonine-D3

Cocaethylene Cocaethylene-D3

Anhydroecgonine methyl ester Morphine-D3

Morphine Codeine-D3

Codeine Oxycodone-D3

Oxycodone Oxymorphone-D3

Oxymorphone Hydromorphone-D3

Hydromorphone Hydrocodone-D3

Hydrocodone 6-Acetylmorphine-D3

6-Acetylmorphine Fentanyl-D5

Fentanyl Methadone-D3

Acetyl fentanyl Meperidine-D4

Methadone Buprenorphine-D4

Meperidine Norbuprenorphine-D3

Tramadol Naloxone-D5

Buprenorphine

Norbuprenorphine

Naloxone
APPENDIX C

SUPPORTING DATA

Validation Summary 

The following is an example of a validation summary for the confirmation and quantitation of 

target compounds in whole blood using LC-MS-MS. 

I Accuracy and Precision 

i Accuracy 

ii Within Run Precision

iii Intermediate Precision

II Sensitivity (LOD, LOQ)

i Limit of detection

ii Limit of quantitation

III Linearity and Calibration Model 

IV Ion Suppression/Enhancement 

V Recovery 

VI Carryover

VII Interferences

i Endogenous Compounds (blanks) 

ii Internal Standard 

iii Commonly Encountered Analytes 

VIII Dilution Integrity

IX Stability 

X Robustness 

XI Training 

XII Summary

XIII References 

XIV Appendix A 
Validation experiments were conducted for the following target analytes. 

Target Internal Standard

R(+)Methcathinone Mephedrone-D3

R,R(-)Pseudoephedrine Pseudoephedrine-D3

Methylone HCl Methylone-D3

(±)Amphetamine Amphetamine-D11

(±)Methamphetamine Methamphetamine-D11

(±)3,4-Methylenedioxyamphetamine (MDA) MDA-D5

Methedrone HCl Mephedrone-D3

(±)3,4-Methylenedioxy-N-methylamphetamine (MDMA) MDMA-D5

Phentermine Methamphetamine-D11

Mephedrone Mephedrone-D3

α-Pyrrolidinopentiophenone (α-PVP) Mephedrone-D3

3,4, Methylenedioxypyrovalerone HCl (MDPV) Mephedrone-D3

Bupropion HCl Mephedrone-D3

The method includes an alkaline liquid-liquid extraction and subsequent quantitation and 

confirmation via LC-MS-MS (Agilent 6430) adopted from the literature references provided 

herein. 

I Accuracy and Precision 

Accuracy 

Accuracy was assessed by analyzing pooled blank blood samples fortified with thirteen target 

compounds at three different concentrations (low, medium, and high) in triplicate with each 

batch for a total of five batches. The pooled fortified blood samples were prepared by spiking a 

large volume of blank blood with the respective concentrations of target analytes (0.03, 0.3, and 

1.5 mg/L). Aliquots (1.0 mL) were then taken from the pooled sample and extracted prior to 

quantitative analysis using LC-MS-MS. 

Accuracy was assessed using the following equation: 

Equation 1. 

Accuracy (%) = ���Mean of calculated values

Expected value � × 100%� − 100�

The acceptance criterion for pooled accuracy was ±20 % for all three concentrations levels. All 

back calculated concentrations were utilized in determining the overall accuracy for the method. 

Table 1 represents the accuracy for the pooled blood samples. The percent accuracy also 

demonstrates bias within the measurements. The n was fifteen for all three concentration levels. 
Table 1. Percent accuracy for amphetamines, phentermine, and designer stimulants

quantitated by LC-MS-MS

Pooled Accuracy

% Accuracy (SD); n=15

Target 0.03 mg/L 0.3 mg/L 1.5 mg/L

Methcathinone 100(4) 100(6) 102(5)

Pseudoephedrine 100(3) 99(3) 102(5)

Methylone 97(3) 99(3) 97(4)

Amphetamine 102(4) 99(2) 93(5)

Methamphetamine 104(5) 100(2) 95(5)

MDA 100(4) 97(2) 99(5)

Methedrone 101(3) 98(2) 99(6)

MDMA 99(4) 98(2) 97(4)

Phentermine 98(5) 99(3) 99(6)

Mephedrone 99(3) 99(3) 102(5)

α-PVP 105(6) 101(3) 101(6)

MDPV 102(4) 98(3) 97(5)

Bupropion 99(7) 95(5) 97(12)

The accuracy ranged from 93±5 % to 105±6 %. All targets were within the acceptance criteria of 

±20 %. The accuracy was within ±5 % for all target compounds. 

Precision

The within-run and intermediate precision was assessed using fortified pooled blood samples. 

The within-run precision was established by analyzing three different concentrations (0.03, 0.3, 

and 1.5 mg/L) of the target compounds in triplicate over five batches. The highest imprecision 

was reported for each concentration level. The intermediate precision was calculated by 

analyzing three different concentrations (0.03, 0.3, and 1.5 mg/L) of the target compounds in 

triplicate over five batches. 

The pooled fortified blood samples were prepared by spiking a large volume of blank blood with 

the respective concentrations of target analytes (0.03, 0.3, and 1.5 mg/L). Aliquots (1.0 mL) were 

then taken from the pooled sample and extracted prior to quantitative analysis using LC-MS-MS.

Precision was measured as the coefficient of variance (%CV) for the within-run and intermediate 

precision analysis. The following equations were utilized to determine the within-run and 

intermediate precision for the target compounds using LC-MS-MS.

Equation 2. 

Within − run Precision (%CV) = �

Standard deviation of batch mean

Calculated mean of batch � × 100%

Equation 3. 

Intermediate Precision (%CV) = �

Standard deviation of combined means

Calculated grand mean � × 100%
The predetermined acceptance criterion for within-run and intermediate precision was ±20 % at 

each concentration level. Table 2 represents the within-run precision data for the pooled samples 

at three concentrations. 

Table 2. Within-run precision of amphetamines, phentermine, and designer stimulants

quantitated by LC-MS-MS

Pooled Within-Run Precision

Mean ± SD(%CV); n=3

Target 0.03 mg/L 0.3 mg/L 1.5 mg/L

Methcathinone 0.029±0.002(7) 0.285±0.010(3) 1.53±0.06(4)

Pseudoephedrine 0.029±0.001(3) 0.301±0.008(3) 1.47±0.04(3)

Methylone 0.028±0.001(5) 0.300±0.005(2) 1.43±0.05(3)

Amphetamine 0.029±0.002(7) 0.300±0.004(1) 1.37±0.05(4)

Methamphetamine 0.030±0.002(8) 0.306±0.006(2) 1.37±0.06(4)

MDA 0.028±0.001(4) 0.284±0.005(2) 1.42±0.05(3)

Methedrone 0.030±0.001(4) 0.297±0.007(2) 1.39±0.05(4)

MDMA 0.028±0.001(3) 0.284±0.005(2) 1.40±0.05(3)

Phentermine 0.029±0.003(11) 0.298±0.008(3) 1.40±0.04(3)

Mephedrone 0.029±0.002(6) 0.298±0.005(2) 1.47±0.05(3)

α-PVP 0.033±0.004(11) 0.308±0.005(1) 1.44±0.10(7)

MDPV 0.031±0.002(8) 0.293±0.014(5) 1.40±0.05(4)

Bupropion 0.029±0.004(14) 0.274±0.025(9) 1.48±0.23(16)

As shown in Table 2, all targets were within the predetermined acceptance criteria of ±20 % for 

the coefficient of variation. The percent CV ranged from 1 % to 16 % for the target compounds.

Bupropion had the largest imprecision (16 %) at the highest concentration. The overall highest 

percent CV over the five batches for each target was represented in Table 2. 

Table 3 represents the intermediate precision for the target compounds at three concentrations 

levels. The n was fifteen for the determination of intermediate precision. 

Table 3. Intermediate precision of amphetamines, phentermine and designer stimulants

quantitated by LC-MS-MS

Pooled Intermediate Precision

Mean ± SD(%CV); n=15

Target 0.03 mg/L 0.3 mg/L 1.5 mg/L

Methcathinone 0.030±0.001(5) 0.299±0.017(6) 1.53±0.08(5)

Pseudoephedrine 0.030±0.001(3) 0.296±0.009(3) 1.53±0.07(4)

Methylone 0.029±0.001(3) 0.297±0.009(3) 1.46±0.06(4)

Amphetamine 0.030±0.001(4) 0.297±0.007(2) 1.40±0.07(5)

Methamphetamine 0.031±0.001(5) 0.299±0.006(2) 1.43±0.07(5)

MDA 0.030±0.001(4) 0.291±0.007(2) 1.49±0.07(5)

Methedrone 0.030±0.001(3) 0.295±0.006(2) 1.48±0.09(6)

MDMA 0.030±0.001(4) 0.293±0.007(2) 1.46±0.07(5)

Phentermine 0.029±0.002(5) 0.298±0.009(3) 1.48±0.09(6)

Mephedrone 0.030±0.001(3) 0.298±0.009(3) 1.52±0.07(5)

α-PVP 0.032±0.002(6) 0.302±0.010(3) 1.52±0.09(6)

MDPV 0.031±0.001(4) 0.294±0.009(3) 1.45±0.08(5)

Bupropion 0.030±0.002(7) 0.284±0.016(6) 1.45±0.19(13)
All targets were within the predetermined acceptance criterion of a percent CV within ±20 % for 

the intermediate precision. The percent CV ranged from 2 % to 13 %. The largest imprecision 

was bupropion (13 %) at 1.5 mg/L. All other targets were within a percent CV of ±10 %. 

The accuracy and precision of the method meets the general acceptance criterion of ±20 % for 

accuracy, within-run precision, and intermediate precision. All thirteen targets were within the 

acceptance criterion. 

II Sensitivity (LOD, LOQ)

i Limit of Detection

The limit of detection (LOD) was addressed by spiking three different blank blood sources at 

0.005, 0.0025, and 0.00125 mg/L along with calibrators (0.01-2.0mg/L). The lowest 

concentration that was capable of achieving acceptable predetermined identification criteria (e.g. 

retention time, peak shape, signal-to-noise ratio, etc.) was considered the target LOD. 

Predetermine acceptance criteria: 

Retention Time - ±5 % 

Qualifier Ratio - ±20 % 

Signal to Noise – > 3 

Table 4 demonstrates the LOD for compounds within the amphetamine and bath salt LC-MS-MS 

quantitative method. 

Table 4. Limit of detection for amphetamines, phentermine, and designer stimulants

quantitation by LC-MS-MS

Limit of Detection

Target LOD (mg/L)

Methcathinone 0.005

Pseudoephedrine 0.005

Methylone 0.0025

Amphetamine 0.005

Methamphetamine 0.005

MDA 0.00125

Methedrone 0.00125

MDMA 0.00125

Phentermine 0.01

Mephedrone 0.00125

α-PVP 0.0025

MDPV 0.00125

Bupropion 0.00125

The LOD for MDA, methedrone, MDMA, mephedrone, MDPV, and bupropion was determined 

to be 0.00125 mg/L. The LOD for methylone and α-PVP was determined to be 0.0025 mg/L. 

Methcathinone, pseudoephedrine, amphetamine, and methamphetamine had an LOD of 0.005 

mg/L. Phentermine was the only analyte that did not meet the acceptance criteria at any 

concentration. Therefore the LOD for phentermine was determined to be 0.01 mg/L. 
ii Limit of Quantitation

The limit of quantitation (LOQ) was addressed by spiking three different blank blood sources at 

0.005, 0.0025, and 0.00125 mg/L along with calibrators (0.01-2.0 mg/L). The lowest 

concentration that was capable of achieving acceptable predetermined identification and 

quantitation criteria was considered the target LOQ. 

Predetermine acceptance criteria: 

Retention Time - ±5 % 

Qualifier Ratio - ±20 % 

Signal to Noise - > 10 

Back Calculated Concentration - ±20 % 

Table 5 demonstrates the LOQ for compounds within the amphetamine and bath salt LC-MS-MS 

quantitative method. 

Table 5. Limit of quantitation for amphetamines, phentermine, and designer stimulants

quantitation by LC-MS-MS

Limit of Quantitation

Target LOQ (mg/L)

Methcathinone 0.01

Pseudoephedrine 0.005

Methylone 0.005

Amphetamine 0.01

Methamphetamine 0.01

MDA 0.005

Methedrone 0.005

MDMA 0.005

Phentermine 0.01

Mephedrone 0.0025

α-PVP 0.005

MDPV 0.0025

Bupropion 0.01

The LOQ for mephedrone and MDPV were determined to be 0.0025 mg/L. Pseudoephedrine, 

methylone, MDA, methedrone, MDMA, and α-PVP had a LOQ of 0.005 mg/L. The LOQ for 

methcathinone, amphetamine, methamphetamine, phentermine, and bupropion were determined 

to be 0.01 mg/L. 

III Linearity and Calibration Model 

The best fit calibration model was determined using multiple statistical analysis techniques as 

well as the analysis of residual plots. A total of five fortified blank blood sources over nine 

batches were analyzed to determine the calibration model for each target. The calibration range 

assessed was from 0.01mg/L to 2.0 mg/L. A total of eight calibrators (0.01, 0.02, 0.05, 0.10, 

0.25, 0.50, 1.0, and 2.0 mg/L) were used in the determination of the calibration model. To 

determine the linear/quadratic nature of the model, ANOVA was used to compare the standard 
deviation of residuals from all nine batches. The t-test and f-test were utilized from the ANOVA. 

The t-test determined if there was a statistically significant difference between the linear and 

quadratic models. 

If p-value < 0.05 (level of significance), the null hypothesis was rejected 

If p-value > 0.05 (level of significance), the null hypothesis was not rejected 

The null hypothesis states that there was no statistically significant difference between 

groups. 

The f-test is utilized to determine if there was a statistically significant difference in the variance 

between two groups. 

If f > Fcrit, the null hypothesis was rejected 

If f < Fcrit, the null hypothesis was not rejected 

The null hypothesis states that the variances between the two groups were equal. 

If the two groups were determined not to be statistically different, a linear calibration model was 

applied to the target. This was to ensure that a quadratic fitting model was not applied to the data 

if there was no statistical significance. If the two groups were statistically different, the quadratic 

calibration model was applied to the target. 

To determine the weighting of the calibration model (non-weighted or 1/x weighting), a t-test 

was used to assess if there was a significant difference between the two groups. The t-test was 

completed after the linear/quadratic nature of the model was established. The weighted and nonweighted sum of relative error for the residual was compared using the t-test. 

If p-value < 0.05 (level of significance), the null hypothesis was rejected 

If p-value > 0.05 (level of significance), the null hypothesis was not rejected 

The null hypothesis states that there was no statistically significant difference between 

groups. 

The weighting of the calibration model was determined by applying the weighting that 

minimizes the sum of relative error for the residuals. The sum of relative error was averaged for 

an overall relative sum over the nine batches analyzed. The relative residual error was calculated 

using Equation 4 for each concentration in the calibration curve. 

Equation 4. 

Relative Residual Error = |Residual Error|

Theoretical Concentration
The relative residual errors for a calibration curve were then summed. The sums of the relative 

errors for the nine batches were then averaged and the lowest average between the weighted and 

non-weighted groups was determined to be the best fit weighting model for the curve. 

Table 6 summarizes the best fit calibration models for each target in the amphetamines, 

phentermine, and designer stimulants quantitative LC-MS-MS method. 

Table 6. Calibration models for amphetamines, phentermine, and designer stimulants

quantitation by LC-MS-MS 

Regression Analysis

Target Linear/Quadratic Weighting 

Methcathinone Linear Weighted (1/x) 

Pseudoephedrine Linear Weighted (1/x) 

Methylone Linear Weighted (1/x) 

Amphetamine Quadratic Weighted (1/x) 

Methamphetamine Quadratic Weighted (1/x) 

MDA Quadratic Weighted (1/x) 

Methedrone Quadratic Weighted (1/x) 

MDMA Quadratic Weighted (1/x) 

Phentermine Quadratic Weighted (1/x) 

Mephedrone Linear Weighted (1/x) 

α-PVP Quadratic Weighted (1/x) 

MDPV Quadratic Weighted (1/x) 

Bupropion Quadratic Weighted (1/x) 

The best fit calibration model for methcathinone, pseudoephedrine, methylone, and mephedrone 

was determined to be a linear weighted (1/x) model. All other targets in the method were 

determined to have a quadratic weighted (1/x) model. The ANOVA and t-test results are 

depicted in Appendix A. The linear, linear weighted, quadratic, and quadratic weighted residual 

plots a reviewable on the validation data CDs. 

IV Ion Suppression/Enhancement

Ion suppression or enhancement was addressed by assessing the instrumental response of postextraction fortified samples and neat standards. Post-extraction fortified samples were prepared 

from blank matrix that was subject to the liquid-liquid extraction protocol. After the extraction, 

the blank samples were spiked with both target and internal standard. The neat samples were 

prepared by spiking a comparable quantity of standard stock solution and internal standard for a 

total of 200 μL of sample. 

Equation 5 was used to calculate the ion suppression/enhancement for all targets and internal 

standards. The ion suppression/enhancement was assessed at three different concentrations (0.02, 

0.25, and 1.0 mg/L) and averaged for an overall suppression/enhancement. 

Equation 5. 

Ion Suppression/Enhancement = � Mean signal of double blank

Mean signal of neat standard� × 100%
The post-extraction fortified samples were analyzed in triplicate using blank blood, liver, and 

urine. Five sources of blank blood, four sources of liver, and two sources of urine were analyzed 

to determine the suppression/enhancement of each matrix type. Table 7 describes the overall 

suppression/enhancement for each target compound. 

Table 7. Overall suppression/enhancement of target compounds

%Suppression/Enhancement (SD)

Analyte Blood Suppression/ 

Enhancement (%)

Liver Suppression/ 

Enhancement (%)

Urine Suppression/ 

Enhancement (%)

Methcathinone 98(12) 83(33) 92(10)

Pseudoephedrine 75(11) 64(21) 81(7)

Methylone 110(7) 88(33) 97(3)

Amphetamine 94(12) 77(28) 103(3)

Methamphetamine 112(9) 88(37) 109(3)

MDA 112(11) 87(31) 103(5)

Methedrone 120(8) 94(36) 108(4)

MDMA 116(7) 90(36) 109(5)

Phentermine 107(12) 88(35) 107(5)

Mephedrone 111(7) 91(33) 101(3)

α-PVP 113(7) 101(35) 98(7)

MDPV 118(7) 100(36) 102(4)

Bupropion 94(10) 95(28) 97(5)

Values of 100 % were indicative of no ion suppression or enhancement in the samples. Values 

greater than 100 % indicated ion enhancement and values less than 100 % indicated ion 

suppression. In blood samples, the ion suppression/enhancement ranged from 75 % to 120 %. 

The greatest suppression was seen with pseudoephedrine and the greatest enhancement was seen 

with methedrone. In liver samples, the ion suppression/enhancement ranged from 64 % to 101 

%. The greatest suppression was seen with pseudoephedrine and the greatest enhancement was 

seen with α-PVP. The urine samples had a range of ion suppression/enhancement from 81 % to 

109 %. The target with the greatest suppression was pseudoephedrine and the target with the 

greatest enhancement was MDMA. It was noted that the suppression and enhancement seen in 

the samples did not affect the quantitative result for the samples. 

The overall suppression/enhancement was also assessed in the internal standards as seen in Table 

8. The suppression and enhancement of internal standards was evaluated in the same manner as

the target compounds.

Table 8. Overall suppression/enhancement of internal standards 

%Suppression/Enhancement (SD)

Analyte Blood Suppression/ 

Enhancement (%)

Liver Suppression/ 

Enhancement (%)

Urine Suppression/ 

Enhancement (%)

Amphetamine-D11 99(14) 88(32) 92(2)

MDA-D5 97(5) 80(26) 93(2)

MDMA-D5 107(4) 87(35) 96(2)

Mephedrone-D3 106(7) 93(34) 99(2)

Methamphetamine-D11 105(7) 87(37) 98(2)

Methylone-D3 101(4) 86(32) 88(2)

Pseudoephedrine-D3 81(10) 75(25) 83(4)
The range of suppression/enhancement for the blood samples was from 81 % to 106 %. The 

internal standard with the greatest suppression was pseudoephedrine-D3 and the internal standard 

with the greatest enhancement was mephedrone-D3. In the liver samples, the 

suppression/enhancement ranged from 75 % to 93 %. There was no enhancement indicated with 

the liver samples. The internal standard with the most suppression was pseudoephedrine-D3. In 

urine samples, the suppression/enhancement ranged from 83 % to 99 %. There was no 

enhancement indicated in the urine samples. The internal standard with the greatest suppression 

in the urine samples was pseudoephedrine-D3. 

V Recovery 

Recovery was addressed by assessing the instrumental response of pre-extraction fortified 

samples and post-extraction fortified samples. Pre-extraction fortified blanks were prepared from 

blank matrix that was spiked with both target and internal standard compounds prior to 

extraction. Post-extraction fortified blanks were prepared from blank matrix that was subject to 

the liquid-liquid extraction protocol. After the extraction, the blank samples were spiked with 

both target and internal standard compounds. 

Equation 6 was used to calculate the recovery for all targets and internal standards. The recovery 

was assessed at three different concentrations (0.02, 0.25, and 1.0 mg/L) and average for an 

overall recovery for each matrix. 

Equation 6. 

Recovery = �

Average pre − extraction spike

Average post − extraction spike� × 100%

The pre-extraction and post-extraction fortified samples were analyzed in triplicate using blank 

blood, liver, and urine. Five sources of blank blood, three sources of liver, and two sources of 

urine were analyzed to determine the average recovery of each matrix type. Table 9 describes the 

average recovery for the target compound with each of the matrix types. 

Table 9. Average recovery of target compounds 

%Recovery (SD)

Analyte Blood 

Recovery (%)

Liver 

Recovery (%)

Urine 

Recovery (%)

Methcathinone 77(22) 71(21) 78(2)

Pseudoephedrine 101(25) 89(19) 98(10)

Methylone 82(8) 77(26) 83(1)

Amphetamine 86(17) 75(20) 85(3)

Methamphetamine 100(31) 76(23) 87(3)

MDA 82(9) 73(19) 86(3)

Methedrone 80(8) 70(20) 82(1)

MDMA 85(9) 72(21) 87(2)

Phentermine 86(14) 77(22) 86(2)

Mephedrone 95(36) 75(18) 82(1)

α-PVP 90(12) 85(17) 87(2)

MDPV 88(8) 81(16) 87(3)

Bupropion 98(16) 86(13) 86(2)
The range of target compound recovery in blood was 77 % to 101 % with methcathinone having 

the lowest recovery. In liver samples, the recovery ranged from 70 % to 89 %. Methedrone had 

the lowest recovery in the liver samples. The recovery of the compounds in urine ranged from 78 

% to 98 % with methcathinone having the lowest recovery and pseudoephedrine having the 

highest recovery. It was noted that the quantitation was not affected in cases where compounds 

had a lower recovery.

The average recovery was also assessed in the internal standards as seen in Table 10. The 

recovery of internal standards was evaluated in the same manner as the target compounds. 

Table 10. The average recovery for internal standards 

%Recovery (SD)

Analyte Blood

Recovery (%)

Liver 

Recovery (%)

Urine 

Recovery (%)

Amphetamine-D11 85(16) 71(21) 89(3)

MDA-D5 83(9) 72(20) 89(3)

MDMA-D5 87(9) 71(22) 91(2)

Mephedrone-D3 86(10) 71(17) 86(2)

Methamphetamine-D11 87(12) 71(23) 90(3)

Methylone-D3 83(9) 70(19) 86(2)

Pseudoephedrine-D3 96(20) 83(22) 88(3)

In blood samples the range of internal standard recovery was 83 % to 96 %. MDA-D5 and 

pseudoephedrine-D3 had the lowest and highest recoveries respectively. The recovery range for 

liver samples was 70 % to 83 % with methylone-D3 having the lowest and pseudoephedrine-D3

having the highest percent recovery. In urine samples, the recovery ranged from 86 % to 91 %. 

Methylone-D3 demonstrated the lowest percent recovery while methamphetamine-D3

demonstrated the highest percent recovery. 

VI Carryover 

Carryover was evaluated by injecting solvent blanks immediately following progressively higher 

concentrations of analyte of interest fortified into blank matrix. The highest concentration of 

analytes injected was 5.0 mg/L and no carryover was detected at this concentration. The 

concentration was confirmed by triplicate analysis. 

VII Interferences 

i Endogenous Compounds (Blanks) 

Interferences from endogenous compounds were evaluated by analyzing multiple sources of 

matrix without the addition of the target compounds or internal standard. A total of six blank 

blood, three blank liver, and two blank urine matrices were analyzed for interferences. No 

interferences were detected in the matrices. 
ii Internal Standard 

To evaluate potential interferences of internal standard by a high concentration of analyte, three 

negative blood matrix samples were fortified with a high concentration (2.0 mg/L) of the target 

compounds. The samples were analyzed for the absence of response for the internal standard. No 

contributions were detected in the internal standard from a high concentration of target 

compounds. 

To evaluate potential interferences of target compounds by a high concentration of internal 

standard, three negative blood matrix samples were fortified with a high concentration (2.0 

mg/L) of internal standard compounds. The samples were analyzed for the absence of response 

of target compounds. No contributions were detected in the target compounds from high 

concentrations of internal standards. 

iii Commonly Encountered Analytes 

Interferences from commonly encountered compounds were evaluated by analyzing three 

sources of blank matrix fortified with high concentrations of commonly encountered drugs, 

metabolites, and other structurally similar compounds. Table 11 depicts the compounds that were 

assessed for interferences.

Table 11. Interferents and concentrations of commonly encountered analytes

Drug Class Drug Concentration 

(mg/L) 

Opioids Codeine, Morphine, Hydrocodone, Hydromorphone, 

Oxycodone, Oxymorphone

0.8

6-Monoacetylmorphine 0.2

Cocaine Cocaine, Cocaethylene, Benzoylecgonine 4.0

Benzodiazepines Alprazolam, Clonazepam, Lorazepam, Diazepam, 

Nordiazepam, Oxazepam, Temazepam, Zaleplon, 

Zolpidem, Zopiclone

2.0

Cannabinoids THC, Carboxy-THC 0.1/0.5

Barbiturates Butalbital, Secobarbital, Phenobarbital 30

Carisoprodol and 

Meprobamate 

Carisoprodol, Meprobamate 100

Fentanyl Fentanyl 0.1

Acetaminophen, 

Salicyclic Acid 

Acetaminophen, Salicylic acid 400/200

Base Drugs Diphenhydramine, PCP, Tramadol, Methadone, 

Amitriptyline, Nortriptyline, Cyclobenzaprine, Trazodone, 

Citalopram, Fluoxetine, Chlorpheniramine, 

Dextromethorphan, Propoxyphene, Mirtazepine, 

Sertraline, Diltiazem, Bupropion, Ketamine, Fluvoxamine, 

Doxylamine, Brompheniramine, Doxepin, Paroxetine 

6.0

Acid/Neutral 

Drugs 

Ibuprofen, Butalbital, Acetaminophen, Meprobamate, 

Caffeine, Gluetheminde, Naproxen, Metaxolone, 

Carbamazepine, Diazepam

6.0

There were no interferences detected from the three blank matrices fortified with commonly 

encountered analytes with the exception of bupropion. Three matrix sources were spiked with the 
statewide base quantitation controls I, II, and III. Upon analysis, a peak was identified as 

bupropion in all three matrices. It was determined that bupropion was present in the spiked 

samples and therefore no interference was detected. 

VIII Dilution Integrity 

The effect of sample dilution on the accuracy and precision of samples was assessed using both 

large and small volume dilutions. When assessing large volume dilutions, a pooled blood sample 

was fortified with the targets at a concentration of 2.0 mg/L. Aliquots of the pooled sample 

where then taken and analyzed as undiluted, 1:2, 1:5, 1:10, and 1:20 dilution. The 1:2 dilutions 

were prepared by taking a 2.0 mL aliquot of pooled sample and diluting with 2.0 mL of blank 

blood. The 1:5 dilutions were prepared by taking 1.0 mL of pooled sample and diluting with 4.0 

mL of blank blood. To prepare the 1:10 dilutions, a 1.0 mL aliquot of the pooled sample was 

diluted with 9.0 mL of blank blood. The 1:20 dilutions were prepared by diluting a 1.0 mL 

aliquot of pooled sample with 19.0 mL of blank blood. Three 1.0 mL aliquots of each dilution 

along with an undiluted sample were then extracted and analyzed for accuracy and precision. 

The overall accuracy and intermediate precision were evaluated for the large volume dilution as 

seen in Table 12 and Table 13. The predetermined acceptance criterion for accuracy and 

precision was ±20 % accuracy and ±20 % percent CV. 

Table 12. Large volume dilution integrity percent accuracy for amphetamines, 

phentermine, and designer stimulants quantitation by LC-MS-MS 

Dilution Integrity Accuracy (Large Volume)

% Accuracy (SD)

Target 1: 2 Dilution 1:5 Dilution 1:10 Dilution 1:20 Dilution

Methcathinone 102(3) 103(2) 100(1) 99(2)

Pseudoephedrine 88(2) 88(1) 88(1) 89(2)

Methylone 90(2) 90(1) 90(1) 90(3)

Amphetamine 87(3) 88(1) 91(2) 93(1)

Methamphetamine 88(2) 91(1) 94(2) 97(3)

MDA 89(3) 88(1) 88(1) 88(2)

Methedrone 87(1) 87(2) 88(3) 88(5)

MDMA 89(2) 90(1) 90(1) 91(1)

Phentermine 90(3) 90(1) 93(3) 93(1)

Mephedrone 91(2) 90(1) 90(1) 90(2)

α-PVP 87(2) 83(1) 89(4) 90(5)

MDPV 82(8) 77(4) 80(5) 86(2)

Bupropion 83(11) 81(8) 79(12) 89(8)

The accuracy for all target compounds was within the acceptance criterion of ±20 % accuracy for 

all large volume dilution ratios with the exception of MDPV and bupropion. MDPV did not meet 

the predetermined acceptance criteria using a 1:5 large volume dilution ratio. Therefore, 

casework samples can be diluted by no more than a 1:2 large volume dilution to still maintain the 

predetermine acceptance criteria for MDPV. Bupropion did not meet the predetermined 

acceptance criteria using a 1:10 large volume dilution ratio. Therefore, casework samples can be 

diluted by no more than a 1:5 large volume dilution to still maintain the predetermine acceptance 

criteria for bupropion. 
Table 13. Large volume dilution integrity intermediate precision for amphetamines, 

phentermine, and designer stimulants quantitation by LC-MS-MS

Dilution Integrity Intermediate Precision (Large Volume)

Mean ± SD (%CV)

Target 1: 2 Dilution 1:5 Dilution 1:10 Dilution 1:20 Dilution

Methcathinone 1.02±0.03(3) 0.41±0.01(2) 0.199±0.002(1) 0.099±0.002(2)

Pseudoephedrine 0.88±0.02(2) 0.35±0.01(1) 0.176±0.001(1) 0.089±0.002(2)

Methylone 0.90±0.02(2) 0.36±0.01(1) 0.179±0.002(1) 0.090±0.003(3)

Amphetamine 0.87±0.03(3) 0.35±0.01(1) 0.181±0.005(3) 0.093±0.001(1)

Methamphetamine 0.88±0.02(2) 0.36±0.01(1) 0.189±0.003(2) 0.097±0.003(3)

MDA 0.89±0.03(3) 0.35±0.01(1) 0.175±0.001(1) 0.088±0.002(2)

Methedrone 0.87±0.01(2) 0.35±0.01(2) 0.177±0.006(4) 0.088±0.004(5)

MDMA 0.89±0.02(3) 0.36±0.01(1) 0.181±0.002(1) 0.091±0.001(1)

Phentermine 0.90±0.03(3) 0.36±0.01(2) 0.186±0.006(4) 0.093±0.001(2)

Mephedrone 0.91±0.02(3) 0.36±0.01(1) 0.180±0.001(1) 0.090±0.002(3)

α-PVP 0.87±0.02(2) 0.33±0.01(1) 0.178±0.009(5) 0.090±0.005(5)

MDPV 0.82±0.08(10) 0.31±0.02(5) 0.160±0.011(7) 0.086±0.002(3)

Bupropion 0.83±0.11(13) 0.32±0.03(10) 0.159±0.023(15) 0.089±0.008(9)

The predetermined acceptance criterion for intermediate precision was a percent CV within ±20 

%. All target compounds were within the acceptance criteria at all of the large volume dilution 

ratios. 

To evaluate small volume dilution integrity small volumes of the fortified pooled blood sample 

were diluted up to a 1.0 mL volume. The 1:2 dilutions were prepared by diluting 0.5 mL of the 

pooled sample with 0.5 mL of blank blood. The 1:5 dilutions were prepared by diluting 0.2 mL 

of the pooled sample with 0.8 mL of blank blood. To prepare the 1:10 dilutions, 0.1 mL of 

pooled sample was dilution with 0.9 mL of blank blood. The 1:20 dilutions were prepared by 

diluting 0.05 mL of pooled sample with 0.95 mL of blank blood. All dilutions were performed 

using serological pipettes with the exception of the 1:20 dilutions. The 1:20 dilutions were 

prepared using a positive displacement pipette. 

The overall accuracy and intermediate precision were evaluated for the small volume dilution as 

seen in Table 14 and Table 15. The predetermined acceptance criterion for accuracy and 

precision was ±20 % accuracy and ±20 % percent CV. 
Table 14. Small volume dilution integrity percent accuracy for amphetamines, 

phentermine, and designer stimulants quantitation by LC-MS-MS

Dilution Integrity Accuracy (Small Volume)

% Accuracy (SD)

Target 1: 2 Dilution 1:5 Dilution 1:10 Dilution 1:20 Dilution

Methcathinone 109(4) 103(2) 88(10) 94(4)

Pseudoephedrine 95(3) 87(1) 77(9) 84(1)

Methylone 96(3) 89(1) 78(9) 84(1)

Amphetamine 91(2) 88(1) 80(8) 87(2)

Methamphetamine 94(3) 91(1) 83(9) 93(1)

MDA 97(4) 88(1) 77(9) 83(1)

Methedrone 92(5) 86(1) 75(9) 82(3)

MDMA 95(2) 88(1) 80(9) 85(2)

Phentermine 96(3) 92(2) 83(9) 93(2)

Mephedrone 97(3) 90(1) 78(8) 84(1)

α-PVP 85(3) 86(2) 81(3) 97(2)

MDPV 88(4) 76(3) 74(8) 82(6)

Bupropion 92(4) 81(5) 79(9) 87(6)

The accuracy of the 1:5 dilutions was within the predetermined acceptance criterion for all 

targets with the exception of MDPV. The following target compounds did not meet the 

predetermine accuracy acceptance criteria for small volume dilutions at a 1:10 dilution ratio: 

pseudoephedrine, methylone, MDA, methedrone, mephedrone, MDPV, and bupropion. 

Therefore, those compounds shall be diluted by no more than a 1:5 small volume dilution is 

casework samples. The remaining compounds passed the acceptance criteria for the 1:20 small 

volume dilution. 

Table 15. Small volume dilution integrity intermediate precision for amphetamines, 

phentermine, and designer stimulants quantitation by LC-MS-MS

Dilution Integrity Intermediate Precision (Small Volume)

Mean ± SD (%CV)

Target 1: 2 Dilution 1:5 Dilution 1:10 Dilution 1:20 Dilution

Methcathinone 1.09±0.04(3) 0.41±0.01(2) 0.177±0.021(12) 0.094±0.004(4)

Pseudoephedrine 0.95±0.03(3) 0.35±0.01(1) 0.154±0.017(11) 0.084±0.001(1)

Methylone 0.96±0.03(4) 0.36±0.01(1) 0.156±0.017(11) 0.084±0.001(1)

Amphetamine 0.91±0.02(2) 0.35±0.01(1) 0.161±0.015(9) 0.087±0.002(2)

Methamphetamine 0.94±0.03(3) 0.36±0.01(1) 0.166±0.018(11) 0.093±0.001(1)

MDA 0.97±0.04(4) 0.35±0.01(1) 0.154±0.018(11) 0.083±0.001(1)

Methedrone 0.92±0.05(6) 0.34±0.01(1) 0.149±0.017(12) 0.082±0.003(3)

MDMA 0.95±0.02(3) 0.35±0.01(1) 0.159±0.017(11) 0.085±0.002(3)

Phentermine 0.96±0.03(3) 0.37±0.01(2) 0.166±0.018(11) 0.093±0.002(2)

Mephedrone 0.97±0.03(4) 0.36±0.01(2) 0.157±0.016(10) 0.084±0.001(1)

α-PVP 0.85±0.03(3) 0.35±0.01(2) 0.163±0.005(3) 0.097±0.002(2)

MDPV 0.88±0.04(5) 0.30±0.01(4) 0.148±0.016(11) 0.082±0.006(8)

Bupropion 0.92±0.04(5) 0.32±0.02(6) 0.157±0.018(11) 0.087±0.006(7)

The predetermined acceptance criterion for intermediate precision was a percent CV within ±20 

%. All target compounds were within the acceptance criteria at all of the small volume dilution 

ratios. The percent CV significantly increases, but remains within the acceptance criteria, with 

the 1:10 small volume dilution ratio. Both inaccuracy and imprecision increase with the 1:10 
 

dilution for all target compounds and decrease with the 1:20 dilution ratio. This may be due to 

the utilization of a more accurate and precise pipette. The 1:10 dilution used a disposable 

serological pipette where the 1:20 dilution utilized a mechanical positive displacement pipette. 

IX Stability 

The stability of extracted samples that were not analyzed immediately was evaluated at two 

concentrations (1.0 mg/L and 0.02 mg/L). The samples were extracted and injected immediately 

to establish Day 1 instrumental responses. Both concentration levels were injected in triplicate 

and the instrumental response was compared over a seven day period. If the average instrumental 

response decreased below 80 % or increased above 120 %, then the target was considered 

unstable after that time period. 

Table 16 and Table 17 show the seven day stability at 1.0 mg/L and 0.02 mg/L for the target 

compounds. Chart 1 and Chart 2 graphically represent the tabulated accuracy data. 

Table 16. Stability of a 1.0 mg/L concentration of analytes over a seven day period 

Deviation From Day 1 Response 1.0 mg/L 

Accuracy(%); n=3 

Target Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 

Methcathinone 100 112 117 118 113 103 102 

Pseudoephedrine 100 90 96 95 97 88 88 

Methylone 100 99 102 101 96 90 93 

Amphetamine 100 91 99 98 97 90 90 

Methamphetamine 100 93 99 99 92 86 85 

MDA 100 86 94 93 85 79 79 

Methedrone 100 93 96 97 93 86 86 

MDMA 100 91 96 96 92 85 85 

Phentermine 100 92 98 98 91 87 87 

Mephedrone 100 94 98 98 94 88 87 

α-PVP 100 97 101 101 93 91 90 

MDPV 100 98 101 102 93 92 92 

Bupropion 100 95 99 98 93 90 89 
Chart 1. Graphic representation of seven day stability of a 1.0 mg/L concentration of 

analytes 

Table 17. Stability of a 0.02 mg/L concentration of analytes over a seven day period 

Deviation From Day 1 Response 0.02 mg/L 

Accuracy(%); n=3 

Target Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 

Methcathinone 100 116 119 121 116 103 104 

Pseudoephedrine 100 94 97 98 98 86 87 

Methylone 100 98 100 101 93 86 88 

Amphetamine 100 89 95 95 92 83 86 

Methamphetamine 100 95 99 99 92 83 83 

MDA 100 89 93 93 93 90 88 

Methedrone 100 96 99 99 97 87 86 

MDMA 100 94 96 97 93 83 86 

Phentermine 100 93 98 98 94 85 88 

Mephedrone 100 96 98 101 96 86 87 

α-PVP 100 98 101 101 94 89 90 

MDPV 100 101 102 103 96 91 92 

Bupropion 100 99 101 101 95 89 90 
Chart 2. Graphic representation of seven day stability of a 0.02 mg/L concentration of 

analytes 

All compounds were stable up to seven days after being extracted with the exception of 

methcathinone. The day four injection of methcathinone was greater than the upper limit 

acceptance criteria of 120 %. During analysis, the sample remained in the autosampler of the 

instrument. After five days it appears that the accuracy is beginning to decrease but still remains 

within the acceptance criteria for all compounds with the exception of methcathinone. 

X Robustness

Robustness was demonstrated by the completion of nine successful batches of samples, 

completed by three analysts over a six week period. Each batch was comprised of calibrators and 

controls. Results of the batches were previously described within the validation summary. 

XI Training 

Scientists trained to perform methods involving liquid-liquid extraction and LC/MS-MS 

confirmation and quantitation may use this method. Additional training of scientists will follow 

this validation, as necessary.

XII Summary

All target compounds passed the comprehensive validation. The accuracy and precision for all 

compounds was within the predetermined acceptance criteria. The LOD and LOQ were also 

established for each compound. Phentermine had the highest LOD at 0.01 mg/L. The LOQ was 
established to be 0.01 mg/L for methcathinone, amphetamine, methamphetamine, phentermine, 

and bupropion. All other targets have a lower LOQ than 0.01 mg/L. 

The best fit calibration model was determined for each target compound using statistical analysis 

and residual plots to determine linearity as well as weighting. Methcathinone, pseudoephedrine, 

methylone, and mephedrone were best fit with a linear weighted (1/x) calibration model. The 

remaining targets were best fit using a quadratic weighted (1/x) model. 

Suppression/enhancement was assessed by comparing the instrument response of post-extraction 

fortified samples with neat samples. The suppression/enhancement was assessed using blank 

blood, liver, and urine samples. Any suppression or enhancement noted did not have an effect on 

the overall accuracy and precision of the method. Recovery was also assessed with the same 

matrices by comparing the instrumental response of pre-extraction and post-extraction fortified 

samples. The recovery for the three matrices was no less than 70 % and did not have a significant 

impact on the accuracy and precision of the method. 

Carryover as well as interference was evaluated for the method. There was no carryover seen in a 

blank sample after the injection of a 5.0 mg/L sample. Also, there were no interferences seen 

from endogenous compounds, internal standard, target analytes, or commonly encountered 

analytes. 

Processed sample stability was evaluated by analyzing two concentrations of target compounds 

over a seven day period. After seven days there was no significant instability with any of the 

target compounds. The dilution integrity was also established using large and small volume 

dilutions. The accuracy and precision of the 1:2, 1:5, 1:10, and 1:20 dilutions were evaluated. 

The accuracy for all target compounds was within the acceptance criterion of ±20 % accuracy for 

all large volume dilution ratios with the exception of MDPV and bupropion. MDPV did not meet 

the predetermined acceptance criteria using a 1:5 large volume dilution ratio. Therefore, 

casework samples can be diluted by no more than a 1:2 large volume dilution to still maintain the 

predetermine acceptance criteria for MDPV. Bupropion did not meet the predetermined 

acceptance criteria using a 1:10 large volume dilution ratio. Therefore, casework samples can be 

diluted by no more than a 1:5 large volume dilution to still maintain the predetermine acceptance 

criteria for bupropion. 

The following target compounds did not meet the predetermine accuracy acceptance criteria for 

small volume dilutions at a 1:10 dilution ratio: pseudoephedrine, methylone, MDA, methedrone, 

mephedrone, MDPV, and bupropion. Therefore, those compounds shall be diluted by no more 

than a 1:5 small volume dilution in casework samples. The remaining compounds passed the 

acceptance criteria for the 1:20 small volume dilution. 

This method provides a rapid and sensitive technique for the detection and quantitation of 

amphetamines, phentermine, and designer stimulants by LC-MS-MS. 
XIII References 

DFS Quality Manual

Toxicology SOP 

F. T. Peters, O. H. Drummer, and F. Musshoff. Validation of new methods. Forensic Science 

International. 2007 Jan 17;165(2-3):216-24. 

R. C. Baselt and R. H. Cravey, Disposition of Toxic Drugs and Chemicals in Man, 4th Edition,

Chemical Toxicology institute, Foster City, CA, 1995.

B. S. Levine, Editor, Principles of Forensic Toxicology, 2nd Ed., Ch. 5. 

Remane D, Meyer MR, Wissenbach DK and Maurer HH. “Ultra high performance liquid 

chromatographic-tandem mass spectrometric multi-analyte procedure for target screening and 

quantification in human blood plasma: validation and application for 31 neuroleptics, 28 

benzodiazepines, and Z-drugs”, Anal Bioanal Chem., 2011, 401(4), pp. 1341-52. 
Appendix A

Regression Analysis 

Methcathinone 

Comparison of Linear Weighted (1/x) and Quadratic Weighted (1/x) using ANOVA

The standard deviation of the residuals was used to determine the linear/quadratic nature of the 

calibration model. 

P-value = 0.08758 > 0.05 and therefore the null hypothesis was not rejected and the

groups were determined to be insignificantly different.

F = 3.37339 < 4.60011 (Fcrit) and therefore the null hypothesis was not rejected and the 

variances were determined to be equal.

From these results, it was determined that there was an insignificant difference between a linear 

weighted calibration model and a quadratic weighted calibration model. Therefore, the linear 

calibration model will be utilized for methcathinone. 

Comparison of Linear Non-weighted and Linear Weighted (1/x) using a t-test

The sum of errors of the residuals was used to determine the weighting for the calibration model. 

P-value = 0.025866173 < 0.05 and therefore the null hypothesis was rejected and the

groups were determined to be significantly different.

The linear weighted model was determined to be the most appropriate calibration model for 

methcathinone. The t-test for the comparison of weighted and non-weighted linear models 

indicated a significant difference between the two groups and therefore the linear weighted 

model was selected as the best fit. This is due to the average sum of relative error for the 

residuals being lower than the non-weighted model (weighted 0.3228 and non-weighted 0.9313). 

Methcathinone: linear-weighted calibration model
Pseudoephedrine

Comparison of Linear Weighted (1/x) and Quadratic Weighted (1/x) using ANOVA

The standard deviation of the residuals was used to determine the linear/quadratic nature of the 

calibration model. 

P-value = 0.61296 > 0.05 and therefore the null hypothesis was not rejected and the

groups were determined to be insignificantly different.

F = 0.26769 < 4.60011 (Fcrit) and therefore the null hypothesis was not rejected and the 

variances were determined to be equal.

From these results, it was determined that there was an insignificant difference between a linear 

weighted calibration model and a quadratic weighted calibration model. Therefore, the linear 

calibration model will be utilized for pseudoephedrine. 

Comparison of Linear Non-weighted and Linear Weighted (1/x) using a t-test

The sum of errors of the residuals was used to determine the weighting for the calibration model. 

P-value = 0.073155106 > 0.05 and therefore the null hypothesis was not rejected and the

groups were determined to be insignificantly different.

The linear weighted model was determined to be the most appropriate calibration model for 

pseudoephedrine. The t-test for the comparison of weighted and non-weighted linear models 

indicated an insignificant difference between the two groups and therefore the linear weighted 

model was selected as the best fit. This was due to the average sum of relative error for the 

residuals being lower than the non-weighted model (weighted 0.1801 and non-weighted 0.3894). 

Pseudoephedrine: linear-weighted calibration model
Methylone 

Comparison of Linear Weighted (1/x) and Quadratic Weighted (1/x) using ANOVA

The standard deviation of the residuals was used to determine the linear/quadratic nature of the 

calibration model. 

P-value = 0.09703 > 0.05 and therefore the null hypothesis was not rejected and the

groups were determined to be insignificantly different.

F = 3.16323 < 4.60011 (Fcrit) and therefore the null hypothesis was not rejected and the 

variances were determined to be equal.

From these results, it was determined that there was an insignificant difference between a linear 

weighted calibration model and a quadratic weighted calibration model. Therefore, the linear 

calibration model will be utilized for methylone. 

Comparison of Linear Non-weighted and Linear Weighted (1/x) using a t-test

The sum of errors of the residuals was used to determine the weighting for the calibration model. 

P-value = 0.052107025 > 0.05 and therefore the null hypothesis was not rejected and the

groups were determined to be insignificantly different.

The linear weighted model was determined to be the most appropriate calibration model for 

methylone. The t-test for the comparison of weighted and non-weighted linear models indicated 

an insignificant difference between the two groups and therefore the linear weighted model was 

selected as the best fit. This was due to the average sum of relative error for the residuals being 

lower than the non-weighted model (weighted 0.2344 and non-weighted 0.5074). 

Methylone: linear-weighted calibration model
Amphetamine 

Comparison of Linear Weighted (1/x) and Quadratic Weighted (1/x) using ANOVA

The standard deviation of the residuals was used to determine the linear/quadratic nature of the 

calibration model. 

P-value = 0.0112 < 0.05 and therefore the null hypothesis was rejected and the groups

were determined to be significantly different.

F = 8.52452 > 4.60011 (Fcrit) and therefore the null hypothesis was rejected and the 

variances were determined to be different.

From these results, it was determined that there was significant difference between a linear 

weighted calibration model and a quadratic weighted calibration model. Therefore, the quadratic 

calibration model will be utilized for amphetamine. 

Comparison of Quadratic Non-weighted and Quadratic Weighted (1/x) using a t-test

The sum of errors of the residuals was used to determine the weighting for the calibration model. 

P-value = 0.000697638 < 0.05 and therefore the null hypothesis was rejected and the

groups were determined to be significantly different.

The quadratic weighted model was determined to be the most appropriate calibration model for 

amphetamine. The t-test for the comparison of weighted and non-weighted quadratic models 

indicated a significant difference between the two groups and therefore the quadratic weighted 

model was selected as the best fit. This was due to the average sum of relative error for the 

residuals being lower than the non-weighted model (weighted 0.2051 and non-weighted 0.7667).

Amphetamine: quadratic weighted calibration model
Methamphetamine 

Comparison of Linear Weighted (1/x) and Quadratic Weighted (1/x) using ANOVA

The standard deviation of the residuals was used to determine the linear/quadratic nature of the 

calibration model. 

P-value = 9.71x10-8 < 0.05 and therefore the null hypothesis was rejected and the groups

were determined to be significantly different.

F = 99.37609016 > 4.60011 (Fcrit) and therefore the null hypothesis was rejected and the

variances were determined to be different.

From these results, it was determined that there was significant difference between a linear 

weighted calibration model and a quadratic weighted calibration model. Therefore, the quadratic 

calibration model will be utilized for methamphetamine. 

Comparison of Quadratic Non-weighted and Quadratic Weighted (1/x) using a t-test

The sum of errors of the residuals was used to determine the weighting for the calibration model. 

P-value = 0.001233953 < 0.05 and therefore the null hypothesis was rejected and the

groups were determined to be significantly different.

The quadratic weighted model was determined to be the most appropriate calibration model for 

methamphetamine. The t-test for the comparison of weighted and non-weighted quadratic 

models indicated a significant difference between the two groups and therefore the quadratic 

weighted model was selected as the best fit. This was due to the average sum of relative error for 

the residuals being lower than the non-weighted model (weighted 0.3500 and non-weighted 

1.0318).

Methamphetamine: quadratic weighted calibration model 
MDA 

Comparison of Linear Weighted (1/x) and Quadratic Weighted (1/x) using ANOVA

The standard deviation of the residuals was used to determine the linear/quadratic nature of the 

calibration model. 

P-value = 9.3x10-5 < 0.05 and therefore the null hypothesis was rejected and the groups

were determined to be significantly different.

F = 29.1881 > 4.60011 (Fcrit) and therefore the null hypothesis was rejected and the 

variances were determined to be different.

From these results, it was determined that there was significant difference between a linear 

weighted calibration model and a quadratic weighted calibration model. Therefore, the quadratic 

calibration model will be utilized for MDA. 

Comparison of Quadratic Non-weighted and Quadratic Weighted (1/x) using a t-test

The sum of errors of the residuals was used to determine the weighting for the calibration model. 

P-value = 0.007963787 < 0.05 and therefore the null hypothesis was rejected and the

groups were determined to be significantly different.

The quadratic weighted model was determined to be the most appropriate calibration model for 

MDA. The t-test for the comparison of weighted and non-weighted quadratic models indicated a 

significant difference between the two groups and therefore the quadratic weighted model was 

selected as the best fit. This was due to the average sum of relative error for the residuals being 

lower than the non-weighted model (weighted 0.2163 and non-weighted 0.5959).

MDA: quadratic weighted calibration model
Methedrone 

Comparison of Linear Weighted (1/x) and Quadratic Weighted (1/x) using ANOVA

The standard deviation of the residuals was used to determine the linear/quadratic nature of the 

calibration model. 

P-value = 9.5x10-5 < 0.05 and therefore the null hypothesis was rejected and the groups

were determined to be significantly different.

F = 29.0722 > 4.60011 (Fcrit) and therefore the null hypothesis was rejected and the 

variances were determined to be different.

From these results, it was determined that there was significant difference between a linear 

weighted calibration model and a quadratic weighted calibration model. Therefore, the quadratic 

calibration model will be utilized for methedrone. 

Comparison of Quadratic Non-weighted and Quadratic Weighted (1/x) using a t-test

The sum of errors of the residuals was used to determine the weighting for the calibration model. 

P-value = 0.004233459 < 0.05 and therefore the null hypothesis was rejected and the

groups were determined to be significantly different.

The quadratic weighted model was determined to be the most appropriate calibration model for 

methedrone. The t-test for the comparison of weighted and non-weighted quadratic models 

indicated a significant difference between the two groups and therefore the quadratic weighted 

model was selected as the best fit. This was due to the average sum of relative error for the 

residuals being lower than the non-weighted model (weighted 0.1840 and non-weighted 0.4785). 

Methedrone: quadratic weighted calibration model 
MDMA

Comparison of Linear Weighted (1/x) and Quadratic Weighted (1/x) using ANOVA

The standard deviation of the residuals was used to determine the linear/quadratic nature of the 

calibration model. 

P-value = 0.04751 < 0.05 and therefore the null hypothesis was rejected and the groups

were determined to be significantly different.

F = 4.71845 > 4.60011 (Fcrit) and therefore the null hypothesis was rejected and the 

variances were determined to be different.

From these results, it was determined that there was significant difference between a linear 

weighted calibration model and a quadratic weighted calibration model. Therefore, the quadratic 

calibration model will be utilized for MDMA. 

Comparison of Quadratic Non-weighted and Quadratic Weighted (1/x) using a t-test

The sum of errors of the residuals was used to determine the weighting for the calibration model. 

P-value = 0.001078124 < 0.05 and therefore the null hypothesis was rejected and the

groups were determined to be significantly different.

The quadratic weighted model was determined to be the most appropriate calibration model for 

MDMA. The t-test for the comparison of weighted and non-weighted quadratic models indicated 

a significant difference between the two groups and therefore the quadratic weighted model was 

selected as the best fit. This was due to the average sum of relative error for the residuals being 

lower than the non-weighted model (weighted 0.1631 and non-weighted 0.3970). 

MDMA: quadratic weighted calibration model 
Phentermine

Comparison of Linear Weighted (1/x) and Quadratic Weighted (1/x) using ANOVA

The standard deviation of the residuals was used to determine the linear/quadratic nature of the 

calibration model. 

P-value = 3.1x10-6 < 0.05 and therefore the null hypothesis was rejected and the groups

were determined to be significantly different.

F = 55.4897 > 4.60011 (Fcrit) and therefore the null hypothesis was rejected and the 

variances were determined to be different.

From these results, it was determined that there was significant difference between a linear 

weighted calibration model and a quadratic weighted calibration model. Therefore, the quadratic 

calibration model will be utilized for phentermine. 

Comparison of Quadratic Non-weighted and Quadratic Weighted (1/x) using a t-test

The sum of errors of the residuals was used to determine the weighting for the calibration model. 

P-value = 0.0225470281 < 0.05 and therefore the null hypothesis was rejected and the

groups were determined to be significantly different.

The quadratic weighted model was determined to be the most appropriate calibration model for 

phentermine. The t-test for the comparison of weighted and non-weighted quadratic models 

indicated a significant difference between the two groups and therefore the quadratic weighted 

model was selected as the best fit. This was due to the average sum of relative error for the 

residuals being lower than the non-weighted model (weighted 0.4326 and non-weighted 0.7782). 

Phentermine: quadratic weighted calibration model
Mephedrone 

Comparison of Linear Weighted (1/x) and Quadratic Weighted (1/x) using ANOVA

The standard deviation of the residuals was used to determine the linear/quadratic nature of the 

calibration model. 

P-value = 0.24563 > 0.05 and therefore the null hypothesis was not rejected and the

groups were determined to be insignificantly different.

F = 1.46855 < 4.60011 (Fcrit) and therefore the null hypothesis was not rejected and the 

variances were determined to be equal.

From these results, it was determined that there was an insignificant difference between a linear 

weighted calibration model and a quadratic weighted calibration model. Therefore, the linear 

calibration model will be utilized for mephedrone. 

Comparison of Linear Non-weighted and Linear Weighted (1/x) using a t-test

The sum of errors of the residuals was used to determine the weighting for the calibration model. 

P-value = 0.05867927 > 0.05 and therefore the null hypothesis was not rejected and the

groups were determined to be insignificantly different.

The linear weighted model was determined to be the most appropriate calibration model for 

mephedrone. The t-test for the comparison of weighted and non-weighted linear models 

indicated an insignificant difference between the two groups and therefore the linear weighted 

model was selected as the best fit. This was due to the average sum of relative error for the 

residuals being lower than the non-weighted model (weighted 0.1685 and non-weighted 0.4994). 

Mephedrone: linear-weighted calibration model 
α-PVP

Comparison of Linear Weighted (1/x) and Quadratic Weighted (1/x) using ANOVA

The standard deviation of the residuals was used to determine the linear/quadratic nature of the 

calibration model. 

P-value = 0.00096 < 0.05 and therefore the null hypothesis was rejected and the groups

were determined to be significantly different.

F = 17.3103 > 4.60011 (Fcrit) and therefore the null hypothesis was rejected and the 

variances were determined to be different.

From these results, it was determined that there was significant difference between a linear 

weighted calibration model and a quadratic weighted calibration model. Therefore, the quadratic 

calibration model will be utilized for α-PVP. 

Comparison of Quadratic Non-weighted and Quadratic Weighted (1/x) using a t-test

The sum of errors of the residuals was used to determine the weighting for the calibration model. 

P-value = 0.002566127 < 0.05 and therefore the null hypothesis was rejected and the

groups were determined to be significantly different.

The quadratic weighted model was determined to be the most appropriate calibration model for 

α-PVP. The t-test for the comparison of weighted and non-weighted quadratic models indicated a 

significant difference between the two groups and therefore the quadratic weighted model was 

selected as the best fit. This was due to the average sum of relative error for the residuals being 

lower than the non-weighted model (weighted 0.3145 and non-weighted 0.7673). 

α-PVP: quadratic weighted calibration model 
MDPV

Comparison of Linear Weighted (1/x) and Quadratic Weighted (1/x) using ANOVA

The standard deviation of the residuals was used to determine the linear/quadratic nature of the 

calibration model. 

P-value = 0.00019 < 0.05 and therefore the null hypothesis was rejected and the groups

were determined to be significantly different.

F = 25.1836 > 4.60011 (Fcrit) and therefore the null hypothesis was rejected and the 

variances were determined to be different.

From these results, it was determined that there was significant difference between a linear 

weighted calibration model and a quadratic weighted calibration model. Therefore, the quadratic 

calibration model will be utilized for MDPV. 

Comparison of Quadratic Non-weighted and Quadratic Weighted (1/x) using a t-test

The sum of errors of the residuals was used to determine the weighting for the calibration model. 

P-value = 0.001072084 < 0.05 and therefore the null hypothesis was rejected and the

groups were determined to be significantly different.

The quadratic weighted model was determined to be the most appropriate calibration model for 

MDPV. The t-test for the comparison of weighted and non-weighted quadratic models indicated 

a significant difference between the two groups and therefore the quadratic weighted model was 

selected as the best fit. This was due to the average sum of relative error for the residuals being 

lower than the non-weighted model (weighted 0.2617 and non-weighted 0.7232). 

MDPV: quadratic weighted calibration model 
Bupropion

Comparison of Linear Weighted (1/x) and Quadratic Weighted (1/x) using ANOVA

The standard deviation of the residuals was used to determine the linear/quadratic nature of the 

calibration model. 

P-value = 0.00877 < 0.05 and therefore the null hypothesis was rejected and the groups

were determined to be significantly different.

F = 9.26024 > 4.60011 (Fcrit) and therefore the null hypothesis was rejected and the 

variances were determined to be different.

From these results, it was determined that there was significant difference between a linear 

weighted calibration model and a quadratic weighted calibration model. Therefore, the quadratic 

calibration model will be utilized for bupropion. 

Comparison of Quadratic Non-weighted and Quadratic Weighted (1/x) using a t-test

The sum of errors of the residuals was used to determine the weighting for the calibration model. 

P-value = 0.000664256 < 0.05 and therefore the null hypothesis was rejected and the

groups were determined to be significantly different.

The quadratic weighted model was determined to be the most appropriate calibration model for 

MDPV. The t-test for the comparison of weighted and non-weighted quadratic models indicated 

a significant difference between the two groups and therefore the quadratic weighted model was 

selected as the best fit. This was due to the average sum of relative error for the residuals being 

lower than the non-weighted model (weighted 0.5010 and non-weighted 1.4417). 

MDPV: quadratic weighted calibration model 
APPENDIX D 

LIST OF KEY PERSONNEL 

CURRICULUM VITAE FOR [PI] 

BIOGRAPHICAL SKETCH FOR FLS II POSITION 
NAMES AND AFFILIATIONS OF KEY PERSONNEL

Point of Contact for this Grant: 

[Redacted]
BIOGRAPHICAL SKETCH

Forensic Laboratory Specialist II 

Virginia Department of Forensic Science 

Chemistry Program Division of Technical Services 

700 North Fifth Street 

Richmond, VA 23219

Required Qualifications 

High school diploma or equivalent with college courses in mathematics and science; experience 

working in a scientific laboratory environment using basic laboratory equipment, techniques, and 

laboratory safety procedures; the ability to accurately record data and maintain record, follow 

written protocols, and oral instructions, establish work priorities, and independently perform 

routine duties; good oral and written communication skills; valid driver’s license and/or other 

means of reliable transportation.

Preferred Qualifications 

Bachelor’s degree in a natural science are or college level courses in biology, chemistry, and/or 

biochemistry; experience handling human physiological fluids; experience in the use of mass 

spectrometry, liquid chromatography, and or liquid chromatography tandem mass spectrometry; 

experience in a forensic science laboratory; experience with computers in a laboratory 

environment. 
APPENDIX E

PROJECT TIMELINE

Date Action 

January 2015 • Award of grant 

• Posting and advertising of Toxicology Forensic Laboratory Specialist II 

(FLSII) position

February 2015 • Interview and award of FLSII position 

• Ordering of initial reagents and supplies for combined cocaine and opioid 

method

March 2015 • Start of FLSII position 

• Training of FLSII

• Submission of first quarterly financial report

April 2015 • Instrumental method development for combined cocaine and opioid 

method

• Development of three sample preparation techniques for combined 

cocaine and opioid method 

May 2015 • Completion of sample preparation method development for combined 

cocaine and opioid method

June 2015 • Begin validation of all three sample preparation methods for whole blood 

• Submission of second quarterly financial report

July 2015 • Continued validation of three sample preparation method for whole blood 

• Submission of first semi-annual progress report

August 2015 • Completion of validation studies for three sample preparation methods in 

whole blood 

• Begin validation of all three sample preparation methods for available 

medicolegal matrices 

September 2015 • Continued validation of three sample preparation methods for available 

medicolegal matrices 

• Submission of third quarterly financial report 

November 2015 • Complete validation of three sample preparation techniques for available 

medicolegal matrices

• Completion of data review and begin preparation of cocaine and opioid 

validation summary

December 2015 • Finalize validation summary for combined cocaine and opioid method 

• Ordering of initial reagents and supplies for designer drug method

• Submission of fourth quarterly financial report

• Submission of fist annual progress report

January 2016 • Instrumental method development for designer drug method

February 2016 • Development of three sample preparation techniques for designer drug 

method

March 2016 • Completion of sample preparation method development for designer drug

• Submission of fifth quarterly financial report
April 2016 • Begin validation of all three sample preparation methods for whole blood 

May 2016 • Continued validation of three sample preparation method for whole blood

June 2016 • Completion of validation studies for three sample preparation methods in 

whole blood 

• Submission of sixth quarterly financial report

July 2016 • Begin validation of all three sample preparation methods for available 

medicolegal matrices

• Submission of second semi-annual progress report

August 2016 • Continued validation of three sample preparation methods for available 

medicolegal matrices 

September 2016 • Complete validation of three sample preparation techniques for available 

medicolegal matrices

• Submission of seventh quarterly financial report 

November 2016 • Completion of data review and begin designer drug validation summary

• Begin preparation of final report 

December 2016 • Finalize validation summary for designer method 

• Submit documents to peer-reviewed journal articles 

• Prepare abstract for SOFT conference presentation 

• Submission of eighth quarterly financial report 

• Submission of final report
APPENDIX F

DATA ARCHIVING PLAN

The Virginia Department of Forensic Science will comply with the data archiving requested by 

NIJ. All instrumental data files are maintained on the instrument computer, CD/DVD or other 

appropriate storage devices, and further stored on a departmental network folder. Instrumental 

files, such as method and report template files will also be maintained in the same manner. All 

documentation pertaining to the results of the validation including Microsoft Excel and 

Microsoft Word files will also be stored on CD/DVD or other appropriate storage devices and on 

the departmental network folder. All such information and files will also be submitted to NIJ 

upon completion of the project. 
Page 1 of 8

APPENDIX G

VIRGINIA DEPARTMENT OF FORENSIC SCIENCE

PREVIOUS AND CURRENT NIJ AWARDS

1996 Forensic DNA Laboratory Program, Phase 1, NIJ Grant #96IJ-CX-0059, $375,000, 

with $125,000 matching state funds

Funding provided to purchase necessary equipment and supplies and conduct training to 

accelerate STR DNA analysis capabilities for typing the backlog of convicted offender 

samples and for typing the backlog of casework samples in three of the Division’s four 

laboratories.

1998 Forensic DNA Laboratory Improvement Program, Phase 2, NIJ Grant #98-DN-VX0018, $375,000, with $125,000 matching state funds 

Funding provided to purchase equipment and supplies for DNA STR fluorescence imaging 

analysis of forensic cases in all four of the Division’s laboratories.

1999 Forensic DNA Laboratory Program, Phase 4, NIJ Grant #98-DN-VX-0018 (S-1)

$250,000, with $83,334 state matching funds 

Funding provided to purchase equipment and supplies for validating and implementing 

the remaining CODIS core STR loci for forensic casework in all four of the 

Division’s laboratories and for the analysis of convicted offender samples in the Central 

Laboratory. DFS will also purchase CODIS equipment upgrades for the Central and 

Eastern Laboratories and an additional CODIS workstation for the Central Laboratory to 

maximize efficiency in this area.

2000 FY 2000 DNA Backlog Reduction Program, NIJ Grant #2000-RC-CX-0018,

$1,800,000

Funding provided for the analysis of 36,000 convicted offender samples outsourced to 

vendor laboratory, with 371 no suspect cases analyzed for the state match requirement [360 

cases, 1% of the convicted offender samples analyzed, required].

2001 Vendor services received under the Convicted Offender DNA Backlog Reduction 

Program (FY2001)

24,000 convicted offender samples and 1,714 quality assurance samples, totaling 25,714 

samples outsourced to vendor laboratory, with more than 257 no suspect cases analyzed as 

the state match requirement [257, 1% of the 25,714 convicted offender and quality 

assurance samples analyzed, required]. 

2002 Crime Laboratory Improvement Program FY 2002, NIJ Grant #2003-LP-CX-K003,

$237,651, with $83,514 state matching funds
Page 2 of 8

Funding provided to purchase equipment and supplies for the Eastern and Western 

Laboratories for extracting/isolating DNA from crime scene samples on the Beckman 

Coulter BioMek® 2000 Laboratory Automation Workstation using Promega’s DNA IQTM 

System. Funding also provided to purchase an FMBIO® III Plus Fluorescent Imaging 

Analysis System for the Central Laboratory, newer model CODIS workstations for the 

Eastern and Western Laboratories, and CODIS file servers for all three of the Division’s 

regional laboratories. 

2002 Vendor services received under the FY2002 Convicted Offender DNA Backlog 

Reduction Program (Outsourcing)

Funding provided for the analysis of 18,000 convicted offender samples and 900 quality 

assurance samples, at the PowerPlexTM 1.1 and 2.1 Systems loci and 50,300 convicted 

offender samples and 2,515 quality assurance samples at the PowerPlexTM 2.1 System loci. 

2003 No Suspect Casework DNA Backlog Reduction Program, NIJ Grant#2003-DN-BXK051, $529,964

Funding provided to contract with the Virginia Institute of Forensic Science and Medicine 

to train four examiners to conduct DNA analysis on forensic cases (6 months) and to 

subsequently provide four qualified DNA examiners to screen and conduct DNA analysis 

on a minimum of 360 no suspect cases (1 year). Laboratory space will be renovated to 

accommodate four examiners in the Central Laboratory and equipment and supplies 

purchased for their use. 

2004 DNA Capacity Enhancement Program Formula Grant, FY04, NIJ #2004-DN-BXK167, $431,770.00

Funding provided to purchase equipment for the Eastern and Central Laboratory and 

renovate space in the Central Laboratory to accommodate additional examiners. 

2004 Forensic Casework DNA Backlog Reduction Program Formula Grant, FY04, NIJ 

#2004-DN-BX-K160, $796,725

Funding provided for four fully qualified “restricted position” DNA examiners for 18 

months and five fully qualified “restriction position” DNA examiners for six months to 

analyze a minimum of 650 backlogged cases. Funding also provided for five “restricted 

position” support staff and to purchase supplies to analyze backlogged cases. 

2004 National Institute of Justice Congressionally Directed Awards, FY04, NIJ #2004-LPCX-0001, $1,490,250 with $496,750 state matching funds

Funding provides for training examiners for DNA and other forensic disciplines by an 

outside vendor at the Division’s Central Laboratory using the Division’s training protocols, 

equipment, and methods of assessing trainees’ performance. 
Page 3 of 8

The second component of the project are the following facility modifications and 

equipment purchases to enhance and/or expand current capabilities: remodeling space and 

purchasing two comparison microscopes in the Eastern Laboratory’s Firearms/Toolmarks 

Section; replacing the FTIRs in the Central and Western Laboratories’ Controlled 

Substance Sections; purchasing a scanning electron microscope for the Eastern 

Laboratory’s Trace Evidence Section; providing a Crimescope to the Latent Prints Sections 

in each regional laboratory; and developing an enhanced laboratory management 

information system.

2005 DNA Capacity Enhancement Program Formula Grant, FY05, NIJ #2005-DA-BXK029, $621,250

Funding provided to purchase equipment for the Eastern and Central Laboratory and to 

renovate space in the Eastern Laboratory to accommodate additional examiners. 

2005 Forensic Casework DNA Backlog Reduction Program Formula Grant, FY05, NIJ 

#2005-DN-BX-K070, $594,320.28 (Federal Funds - $539,204; State Funds - $55,116

Funding provided for six fully qualified “restricted position” DNA examiners for seven

months to analyze a minimum of 170 backlogged cases. Funding also provided for one 

“restricted position” support staff for the Central Laboratory. Additional funding provided 

to purchase supplies to analyze backlogged cases. 

2006 DNA Capacity Enhancement Program Formula Grant, FY06, NIJ #2005-DN-BXK153, $768,640 

Funding provided to screen and conduct DNA analysis in-house on a minimum of 768 

backlogged cases, and to purchase equipment associated with conducting DNA analysis on 

these backlogged cases. 

2006 Forensic Casework DNA Backlog Reduction Program Formula Grant, FY06, NIJ 

#2005-DN-BX-K120, $385,992

Funding provided to screen and conduct DNA analysis in-house on a minimum of 300 

backlogged forcible rape and homicide/non-negligent manslaughter cases and to purchase 

supplies associated with screening and conducting DNA analysis on these cases.

2007 Forensic DNA Backlog Reduction Program Formula Grant, FY07, NIJ #2007-DNBX-K159, $1,019,119

Funding provided for the salaries and benefits of two “restricted position” full time support 

personnel (one for the Central Laboratory and one for the Northern Laboratory). The 

remaining grants funds are to purchase supplies and equipment associated with screening 

and conducting DNA analysis on backlogged aggravated assault, forcible rape, murder,

and robbery cases. 
Page 4 of 8

2007 Convicted Offender and/or Arrestee DNA Backlog Reduction Program Grant, 2007-

DN-BX-K004, $360,000

Funding provided for the overtime salaries and benefits for five DNA Data Bank analysts

to analyze offender and arrestee samples and perform technical review of the data, and two 

support staff to accession the offender and arrestee samples and enter the identifying 

information into computer databases used to track the samples. The remaining funds will 

be used to purchase supplies and commercially available STR kits (PowerPlex® 16 BIO 

System kits) accepted by the National DNA Index System (NDIS) for the DNA Data Bank 

analysts to conduct DNA analysis on these backlogged offender and arrestee samples.

2008 Paul Coverdell Forensic Science Improvement Program, 2008-CD-BX-0044, $59,000

Funding provided to purchase various supplies and equipment items to improve capacity in 

the Controlled Substances and Toxicology Sections.

2008 Research and Development in the Area of Controlled Substances Detection and 

Analysis, 2008-DN-BX-K140, $49,774

Funding provided for a portion of the salary and benefits for two Forensic Scientists to 

evaluate the use of CMAs, including β-cyclodextrin (BCD) and hydroxypropyl-βcyclodextrin (HPBCD), in reverse-phase thin layer chromatography (RPTLC) for the 

differentiation of enantiomeric drug substances including but not limited to 

dextromethorphan, levomethorphan, dextrorphanol, levorphanol, dextropropoxyphene, 

levopropoxyphene, dextro-methamphetamine and levo-methamphetamine in order to find a 

simple, fast, cost effective alternative for enantiomer determination that any forensic 

laboratory would be able to use regardless of budgetary or space constraints. Funding also 

provided to purchase necessary supplies and small equipment items. The results of this 

research project were presented as follows: “Development of a Thin Layer 

Chromatography Method for the Separation of Enantiomers Using Chiral Mobile Phase 

Additives”, presented by Robyn Larson at the 2010 NIJ Grantees Meeting (at the annual 

meeting of the American Academy of Forensic Science in Seattle) and “Investigation of 

Thin Layer Chromatography Methods for the Separation of Enantiomers Using Chiral 

Mobile Phase Additives”, presented by Kelly Howerter at the 2012 meeting of the MidAtlantic Association of Forensic Sciences.

2008 FY 2008 Forensic DNA Backlog Reduction Program, 2008-DN-BX-K036, $ 942,280 

Funding provided for the salaries and fringe benefits for two “restricted position” part-time 

support personnel (one for the Central Laboratory and one for the Northern Laboratory). 

DNA analysis will be conducted in-house on a minimum of 945 backlogged cases giving 

priority first to rape, murder, aggravated assault, and robbery cases. Funding also provided 

to purchase supplies and equipment associated with screening and conducting DNA 

analysis on the backlogged cases.
Page 5 of 8

2008 Governor-Mandated Post-Conviction DNA Testing of Biological Evidence in Case 

Files, 2008-DN-BX-K128, $ 4,520,295

Funding provided to pay the overtime salaries and FICA benefits for fully qualified DFS

examiners who will complete reviews of approximately 2,200 post-conviction cases that 

involved forcible rape, murder, or non-negligent manslaughter in order to identify cases 

that meet project selection criteria for DNA testing. A minimum of 700 post-conviction 

cases, with approximately 5,600 samples, will be forwarded to a private laboratory for the 

DNA analysis. Project funds will be used to pay the contract fees per sample associated 

with the DNA analysis. As these analyses are completed and data returned to DFS, the 

eleven DFS examiners will be review and verify the results. Certificates of Analysis will 

be issued for all case in which DNA analysis is performed. In addition, letters of 

notification will be sent to the parties as required by Virginia Legislation. 

2008 FY 2008 Using DNA Technology to Identify the Missing, 2008-DN-BX-K154, 

$443,682

Funding provided for DFS and the Office of the Chief Medical Examiner (OCME) to 

initiate a joint effort to conduct DNA analysis and profiling of human remains currently in 

OCME storage. Depending on the condition of the evidence, short tandem repeat (STR) 

DNA testing and/or mitochondrial DNA testing will be conducted. DFS will use funds 

from this grant to pay the salaries and benefits for a mitochondrial DNA examiner and a 

wage Forensic Laboratory Specialist.

The OCME will use funds from this grant to pay the salaries of a wage Forensic 

Pathologist and a wage Medicolegal Death Investigator, and will contract with an 

Anthropologist for case file review and pre-DNA examination of all unidentified remains 

to determine suitability for testing. DFS will conduct mitochondrial DNA tests of all 

samples submitted. When DFS completes the DNA testing, the DNA profiles will be 

entered into the CODIS+mito database. 

2009 FY 2009 Forensic DNA Backlog Reduction Program, 2009-DN-BX-K080, $ 950,167

Funding provided for the salaries and fringe benefits for five “restricted position” full-time 

personnel. One full time forensic laboratory specialist to contact Virginia’s law 

enforcement agencies to determine the status of the backlogged cases and to assist the 

DNA examiners with laboratory support functions. Four Forensic Scientists to conduct 

scientific exams on items of evidence and reference samples. Additional funds provided 

for purchasing supplies associated with screening and conducting DNA analysis on the 

backlogged cases, new robotic systems, and the statewide DNA annual mandatory training 

in accordance with the FBI Quality Assurance Standards.

2009 FY 2009 Convicted Offender/Arrestee DNA Backlog Reduction Program, 2009-DNBX-K020, $171,579

Funding provided for overtime salaries and FICA benefits for five DNA Data Bank 
Page 6 of 8

analysts, who will analyze offender and arrestee samples and perform technical review of 

the data, as well as two full-time staff to perform Data Bank sample analysis support 

functions. Funding also provided to purchase the chemistries necessary to analyze the 

backlogged samples and associated controls.

2009 Solving Cold Cases with DNA, 2009-DN-BX-K046, $490,960

Funding provided for two Forensic Scientists and the necessary supplies and equipment to 

conduct DNA analyses on active cold cases meeting the specified crime category. Eligible 

DNA profiles will be searched and uploaded into the Combined DNA Index System 

(CODIS).

2009 Paul Coverdell Forensic Science Improvement Program, 2009-CD-BX-0043, $164,951

Funding provided for renovation of the Central Laboratory to accommodate new Forensic 

Scientists in the Firearm and Toolmarks Section, to expand office space for examiners, to 

expand/relocate the Digital & Multimedia Evidence Section, and to relocate the 

Administrative Office and forensic case files. Funding provided covers general 

construction costs and materials/labor associated with the renovation efforts.

2010 FY 2010 Paul Coverdell Forensic Science Improvement Program, 2010-CD-BX-0038, 

$311,246 

Funding provided to DFS to conduct training in the Physical Evidence and Chemical 

Analysis Services program areas. Funding also provided to purchase balances for the 

Controlled Substances Section and three Gas Chromatograph-Mass Spectrometers for the 

Trace Evidence Section. 

2010 FY 2010 Forensic DNA Backlog Reduction Program, 2010-DN-BX-K120, $920,520

Funding provided to enhance the capacity and to reduce the current backlog in the Forensic 

Biology Section. Three Forensic Scientists to conduct scientific exams on items of 

evidence and reference samples and one Forensic Laboratory Specialist to contact 

Virginia’s law enforcement agencies to determine the status of the backlogged cases and to 

assist the DNA examiners with laboratory support functions. Additional funds provided for 

purchasing supplies associated with screening and conducting DNA analysis on the 

backlogged cases and the statewide DNA annual mandatory training in accordance with 

the FBI Quality Assurance Standards.

2010 FY 2010 Using DNA Technology to Identify the Missing, 2010-DN-BX-K130, 

$468,640

Funding provided to continue joint effort by DFS and the OCME to identify human 

remains located in Virginia. DFS to conduct DNA analysis and profiling of human 

remains submitted to the laboratory by OCME and law enforcement agencies and upload 

resulting DNA profiles into the CODIS+mito database. The OCME to perform an 
Page 7 of 8

anthropological pre-DNA examination of all unidentified human remains to determine 

suitability for DNA testing and to enter each unidentified human remains case into the 

NamUs database. The OCME Medicolegal Death Investigators to review potential hits 

and liaison with the local law enforcement agencies. Contract Odontologists to assist in 

examining unidentified dental remains and make comparisons with dental x-rays of 

potential matches. Funding also provided for the purchase of necessary supplies and 

equipment.

2011 FY 2011 Forensic DNA Backlog Reduction Program, 2011-DN-BX-K421, $1,447,358

Funding provided to enhance the capacity and to reduce the current backlog in the Forensic 

Biology Section. Four Forensic Scientists to conduct scientific exams on items of evidence 

and reference samples and one Forensic Laboratory Specialist to assist the DNA examiners 

with laboratory support functions. Additional funds provided for purchasing supplies

associated with screening and conducting DNA analysis on the backlogged cases and the 

statewide DNA annual mandatory training in accordance with the FBI Quality Assurance 

Standards.

2011 FY 2011 Paul Coverdell Forensic Science Improvement Program, 2011-CD-BX-0051, 

$230,825 

Funding provided for training related travel and registration fees. Funding also provided to 

enhance the capacity of the Latent Prints Section with the purchase of software for latent 

print comparisons. 

2012 FY 2012 DNA Backlog Reduction Program, 2012-DN-BX-0021, $1,165,649

Funding provided to enhance capacity in the Forensic Biology Section. Four Forensic 

Scientists to conduct scientific exams on items of evidence and reference samples and one 

Forensic Laboratory Specialist to assist the DNA examiners with laboratory support 

functions. Funding also provided to purchase three 3500 genetic analyzers for validation 

and protocol development for future use in the section. Training for DNA scientists was 

provided with funds under this award.

2012 FY 2012 Paul Coverdell Forensic Science Improvement Program, 2012-CD-BX-0022, 

Total award for VA = $ 185,297. DFS portion = $103,891

Funding provided to DFS for training related travel and registration fees for scientists in 

the Chemical Analysis and Physical Evidence program areas. Funding also provided for 

equipment items for the Firearms and Toxicology sections.

2013 FY 2013 DNA Backlog Reduction Program, 2013-DN-BX-0079, $990,871

Funding provided to enhance capacity in the Forensic Biology Section. Four Forensic 

Scientists to conduct scientific exams on items of evidence and reference samples and one 

Forensic Laboratory Specialist to assist the DNA examiners with laboratory support 
Page 8 of 8

functions. Funding also provided to purchase one 3500 Genetic Analyzer. Training for 

DNA scientists will be provided with funds under this award.

2013 FY 2013 Paul Coverdell Forensic Science Improvement Program, 2013-CD-BX-0055, 

Total award for VA = $170,371. DFS portion = $83,582. Funding provided for training 

and continuing education of DFS Forensic Scientists in various scientific disciplines.

2014 FY 2014 DNA Capacity Enhancement and Backlog Reduction Program, 2014-DNBX-0044, $906,457. Funding provided to enhance capacity in the Forensic Biology 

Section. Five Forensic Scientists to conduct scientific exams on items of evidence and 

reference samples and one Forensic Laboratory Specialist to assist the DNA examiners 

with laboratory support functions. Funding also provided to purchase two 3500 Genetic 

Analyzers and one Qiagility Robot. Training for DNA scientists will also be provided with 

funds under this award.

2014 FY 2014 Paul Coverdell Forensic Science Improvement Program, 2014-CD-BX-0055. 

Total award for VA = $184,994. DFS portion = $92,496. Funding provided for training 

and continuing education of DFS Forensic Scientists in various scientific disciplines.