1,3,4 forensic chem drugs analysis

1

1. Introduction

3. Multivariate statistics, Calibration, Quality control

4. Sample Preparation, Thin-Layer Chromatography

Suzanne Bell, FORENSIC CHEMISTRY

FORENSIC CHEMISTRY =APPLIED ANALYTICAL CHEMISTRY

• Specificity – skill, art and science of comparison!

• Analytical chemistry: What is it? How much of it is there?

• Forensic chemistry: Where could this come from?

• 3 tasks for a forensic scientist:

– identification (qualitative, sometimes quantitative analysis)

– classification (in which group does it belong?)

– individualization or establishing a common source

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THE FLOW OF FORENSIC ANALYSIS

General unknown

• Visual examination

• Organic chemical analysis

• Inorganic chemical analysis• color tests

• crystal tests

• isolation

• identification

THE FORENSIC MINDSET

Forensic chemists should:• assume nothing

• be resourceful

• think outside the discipline

• be creative

• build a toolbox that never stops growing

• know their limitations

• be flexible

• be persistent

FORENSIC CHEMISTRY TODAY

FORENSIC

TOXYCOLOGY• biological evidence

• following trail of drugs, poisons ingested

• death investigation

FORENSIC

CHEMISTRY• physical evidence

• crime labs

B.Sc. in natural science (preferably chemistry :-)

• emphasis on analytical & instrumental methods

• additional training or experience in toxicology or pharmacology for forensic toxicology

3. Multivariate statistics, Calibration and Quality control


OVERVIEW

• Quality assurance (QA) – system that controls data generation founded on:

(1) analytical data + (2) statistical tools → reliability + uncertainty

• Quality control (QC) - procedures, policies and practices designed to assure data quality

Multivariate statistics and Chemometrics

• Single variables– continuous (% of a drug in white powder sample: from 0.0-100.0 %)

– categorical (fiber: red and nylon; plant material is or isn’t marijuana)

• Multiple variables (white powder: identity, weight, concentration,

cutting agents, their concentration…) → multivariate statistics = application of statistics to data sets with more than one variable!

– descriptive

– predictive

– classification

• Analysis of chemical data + Exploratory data analysis (EDA) + Modeling = Chemometrics

Predictive modeling and calibration

• Univariate modeling = linear regression– y = mx + b continuous (m=slope, b=intercept, y=dependent variable,

x=independent variable)

– linear range, in orders of magnitude

– LOQ, LOD

– least squares method


• Goodness of fit = correlation coefficient or its square R2

-1 < R2 < +1

• At least “two nines: 0.99” ☺

• Visual inspection – second level of control


• One of the points “looks funny”!

• To include or exclude? WHY???

• Chemistry before statistics!!!

Exploratory* data analysis (EDA): Profiling cocaine

• Linear calibration = predictive modeling (single dependent variable)

• Multivariate analysis = studying data and identifying relationships or patterns

• Example: 3 separate cocaine seizures (each containing 10 wrapped exhibits), externally all similar, all contain cocaine diluted with procaine and caffeine in different ratios

– How are the samples related to each other?

– OR: Are there groups or patterns in the data?

– EDA: study of correlations and other relationships!

*Истражувачка

Exploratory data analysis (EDA): Profiling cocaine

Principal Component Analysis (PCA)Карактеристична векторска анализа

• Linear relationships between variables → PCA to find groups and patterns within data by reducing dimensionality of data

• Especially when more than 3 variables are available (graphical data exploration is not feasible)!

• So: variables are combined to reduce the dimensionality of data

• In the example: linear correlation exists between cocaine and procaine conc. and they are combined in one variable!

• Z = principal component = linear combination of all variables (3 here)• Each new variable refers to a new and hidden relationship between original

variables and is also called a factor

Principal Component Analysis (PCA)Карактеристична векторска анализа

• First two components account for 92 % of total variance → dimensionality reduced from 3 to 2!

• The same pattern from 3 to 2 dimensions graphical presentation! Big deal!• Much more useful when dealing with large data sets! Ex.: spectra

Clustering, Cluster Analysis

• Data points = points in a “data space”• Goal: identify like groups by measuring their separation in

space and express the groups in a interpretable graphical form• The most common metrics system for measuring the separation between

data in the “data space” is the Euclidean distance (n=number of variables):

• Data usually normalized or scaled (z-transform: each value within a column is standardized by determining its separation from the mean and dividing by the standard deviation)

Clustering, Cluster Analysis

• Single linkage algorithm: two closest points combined into a cluster (“linked”), distance recorded, their distances recomputed, for the new cluster – the distance with another cluster is considered…

• Dendrogram (tree diagram)

Quality Assurance and Quality Control, QA/QC

• International Standardization Organization (ISO):

• the organization = forensic laboratory• the products = services and analytical data• the customer = the justice system

• Total Quality Management (TQM) – practices and procedures used within an organization - forensic laboratory - by everyone from bench analyst to management

• External standardization and quality assurance entities: ISO, ANSI (AmericanNational Standardization Institute), ASQ (American Society of Quality)…

• In the analytical and forensic community: ASTM (American Society for Testing and Materials) involving AOAC International (Association of Official Analytical Chemists) AAFS (American Academy of Forensic Sciences), SOFT (Society of Forensic Toxicology), ENFSI (European Network of Forensic Science Institutes), EN standards



Standardization:• Assured comparability of analytical measurements (Example: NIST mass

spectral library applicable for standardized instrumental conditions, “tunning” of the mass spectrometer with PFTBA-perfluorotributylamine)

• Optimized and validated methods – checked method characteristics and limitations → comparable and reliable data

• Measure performance of analyst and laboratory

Standard Reference Materials (SRMs), Certified SRMs (CRMs)–obtained by either

• A definitive (primary) method using specialized instrumentation capable of high accuracy and precision and thoroughly investigated and corrected errors

• Two or more independent methods at NIST using commercial instruments (calibrated)with differing sources of errors

• Interlaboratory data from selected laboratories using multiple methods and NIST SRMs standards as controls

NIST – National Institutes of Standards and Technology – non-regulatory body – to promote standardization of weights and measures


Q: How do we know that a peak obtained at 1700 cm-1 in the IR spectrum is at that wavenumber and not at 1650 cm-1?

• Traceability (следливост) – linkage of measurements through CRMs back to NIST

Within the forensic community: organization of forensic laboratories and professionals is important for agreeing and publishing laboratory guidelines, procedures, standards, organizing trainings, interlaboratory tests…

TQM + QA + statistics → key terms:¾ Accuracy = точност (closeness of measured to accepted reference value)¾ Bias = грешка (Difference between expected and measured result, total systematic error)¾ Control chart = контр. графици (graphical record of replicate measurements: reagents, equipment)

¾ Interlabor. comparisons = меѓулабор. споредби (several labs analyzing the same sample)

¾ Precision = прецизност (reproducibility of a series of replicate measurements, comparable cond.)

¾ Random error = случајна грешка (inescapable, unpredictable, characterized by %RSD)¾ Systematic error = систематска грешка (minimized in validated method, sometimes same

as bias)¾ Uncertainty = неодреденост (measure of variability associated with measurement taking

into account bias and random errors, expressed as value ± uncertainty in %RSD)



• Traceability (следливост) – chain of custody for quality– Linking analytical results to unassailable original source (ex. NIST SRM)– Including calibration of instruments and equipment (Example: analytical balance

is calibrated with certified weights traceable to NIST standard weights)

Traceability – long, but unbroken, documented chain of relationships and dependencies (analytical balance, spectrophotometer, pH-meter…) - linking a measured value to NIST or other standard

Instrument tests = calibration– if obtained value within uncertainty value specified on the Certificate of Analysis – test

passed i.e. instrument OK– if obtained value outside… – test failed – instrument needs recalibration or repair

Instrument OK ⇒ results OK?

– Not exactly!– instrument calibration-validation is just one step (a prerequisite) in the long and

complex analytical process!⇒traceability is a foundation of method validation!


Validated method –properly applied will produce reliable and trustworthy data with known performances and limitations

– Can be used for various samples, but the protocol is the same– Validation is key component of a total quality management in a laboratory!

Validated method produces best possible data for a given analyte/s such that the data are acceptably:

→ accurate = точни,→ precise = прецизни,→ quantifiable = мерливи,→ timely = навремени,→ reliable = веродостојни.

The details of method validation are usually dictated or recommended by professional associations or accreditation bodies, which publish guidelines for the validation (Ex.: SOFT-Society of Forensic Toxicology publishes guidelines for validation of toxicology methods)


Steps in method validation involve determination of the following quantities:→ instrument reproducibility (Ex.: %RSD of peak areas obtained by GC-MS? Comparison of manual and autosampler injection)

→ interfering substances i.e specificity or selectivity of the method,→ minimal error,→ accuracy and reproducibility (precision),→ analyst variation,→ characteristics of calibration curves (later),→ stability over time,→ limit of detection (LOD),→ limit of quantification (LOQ),→ linear dynamic range (LDR).

Analyst and laboratory “validation”Analysts s h ould be certified, laboratories accredited!In USA, certification by professional organization (AAFS, ABC, SOFT) by General

Knowledge Examination (GKE) and specialty examinations. In MK?Accreditation by AACLD/LAB – a multi-step and thorough process examining from

physical plant through analysts to management structure. In MK – IARM!

e, equipment, instrumentation are free etect systematic errors (contamination)

ци, познати) – samples with known d; provides a measure of accuracy,

непознати) – samples with true value alyst; for proficiency testing of forensic

true value; may be disguised as a case

calibration has a lifetime and should be e, daily) by calibration solution prepared


Quality control procedures – every analysis accompanied by a multitude of quality assurance steps

→ quality control samples always accompany a sample run giving a collection i.e. batch (серија) containing at least the sample and controls (positive and negative) depending on the type of sample and data required (quantitative, qualitative or both)

Ex.: Simple color test must be performed with positive control (control sample that gives positive result) and negative control (blank, no result). Blood on dark blue bedsheet!

→ If quantitative information is required: bigger number of control samples is necessary!

Balance between the need for QA/QC and limitations of time and money!- Replicates not done on known samples! It is done on unknowns and if done on knowns it would

give comparable results!- Replicates not done on blanks! Useful information but for much time and reagents and with more

generated waste!

⇒ Compromise = QA/QC provide necessary information without being excessive!


Quality control samples:• Blank samples (слепи проби) – check if glasswar

from the analyte and potential interferences; help to d

• Open controls or knowns (контролни примеро reliable values; may be prepared from analyte standar valuable for detecting and diagnosing systematic errors

• Blinds or blind controls (контролни примероци, known to someone in or outside the lab, not to the an chemists; “double blind” – nobody in the lab knows the sample

• Calibration checks (проверки на калибрација) – regularly checked (in each batch or on a time schedul independently of calibration standards

• Replicates – subsample or aliquot – performing 3 replicates → simple statistics mean, %RSD;because of time constraints – only some samples are done in replicate

• Duplicates – a separate sample from a separate source taken in the field

• Spikes (стандардни додатоци) – compounds purposely added at known levels to gauge the recovery of an analyte from a specific matrix and sample, to make quantitative assessment of the effect of the matrix


Goal of TQM and QC = reduction of errors to minimum, leaving only random errors treated with statistics

Sources of errors

Types of errors:• From the analyst – poor execution• From the method – inherent problem with the method

Minimization of errors:• Education and training, peer supervision and review, honest self-evaluation• Method validation designed to minimize and characterize the error

Another characterization of errors:• Systematic (систематски грешки) – predictable and impart a bias to results;

detected by use of blanks, calibration checks, controls.• Random (случајни грешки) – equally positive and negative, small – can not be

eliminated, due to uncertainties

Quality Control and Calibration

Calibration process – linking an instrumental response to performance using a trustworthy, traceable standard, procedure or comparison

Labs calibrate: balances, pipets, instruments at intervals defined by standard operating procedures (SOPs): balances checked weekly, GC calibration curves every 12 hours ⇒ calibration and calibration checks ensure reliable output, more complex the device – more checking must be done!

If the equipment is used for measurement related to generating data ⇒ it must be calibrated!• Balances, pipets, syringes, pH-meters, refrigerators, thermometers…

• Balance – calibration is a simple process of obtaining traceable weights, recording the displayed and certified weight and seeing if the difference is in the expected range based on uncertainty and significant figures. If not: service!

• Control charts are used to identify failures and predict and diagnose the failure.

Ex.: pipet of 200 µL ± 2 µL (1 %) is checked by measuring the weight of water at given temperature (calibrated balance, calibrated thermometer) and converted to volume. Two series of measurements are made for establishing upper and lower warning limits (UWL, LWL) and action limits (UAL, LAL)


Concentration and Response

valid and trustworthy calibration

etime! UV-Vis calibration each day, modern GC-MSable calibration curves for few days.btained from a traceable standard independent of the

calibration standards – ideal for detection of a problem in t be analyzed regularly to ensure that equipment is not

f a calibration curve: correlation coefficient (R2), nk, time elapsed since the initial calibration or update, ndent calibration-check sample.

ncentration versus response plot fit to a linear equation;solvent (methanol, 1 % acid…); works well when matrix


Calibration of Instruments: A good regression line ⇒ Calibration curve has a lif

instruments can produce st

Calibration checks (CC) – o solutions used to prepare the the stock solution. Blanks mus contaminated.

⇒ 4 factors for validation o absence of a response to a bla and performance on an indepe

⇒ Most common:• External standard – simple co standards prepared in a generic effects are minimal;

⇒Most common (cont.):• Internal standard – for complex or variable matrices (blood) ⇒ matrix mismatch – a calibration curve generated in organic solvent differs from the one in the blood matrix!

– similar chemical behaviour as the analyte, but not present in the sample

⇒Most common (cont.):• Standard additions – not much used in forensic chemistry but → perfect matrix match!

- Sample divided in 4-5 portions, nothing added to first portion, minute volumes of concentrated analyte added to other portions in increasing increments and results plotted → x-axis intercept corresponds to negative equivalent of concentration

- Disadvantages: large amount of sample, difficulties for routine analysis

- Used in unusual cases with difficult matrices

• Isotope dilution – occasionally used in specialized forensic applications because the limited availability of suitable standards,- Ex.: deuterated internal standards, 13C enriched standards

- The enriched standard (spike) added to sample and then analyzed by MS – the spike is chemically identical to the analyte → good matrix correction

4. Sample Preparation, Thin-Layer Chromatography

(and Immunoassay)


OVERVIEW• Sample preparation purpose: to isolate analytes from a matrix

i.e. “sample cleanup”• Range

- simple “dilute and shoot”- complex acid-base-neutral extractions

• The heart of cleanup methods is partitioning between phases:analytep1 ↔ analytep2

p1 and p2: two insoluble liquids (water and hexane), or solid and liquid, or liquid and gas

• Partitioning is based on greater affinity of the analyte for one phase over the other due to charges, polarity and other chemical properties

• Le Chatelier’s principle drives the equilibrium to one side or another, the more complete this process → the more efficient the separation

Manipulation of equilibrium conditions-crucial for extraction & partitioning!

• Partitioning = heart of chromatography, as well!

• Thin-la yer chromatograph y

General

• Organic analytes: drugs, poisons, polymers

• Inorganic analytes and metals: gunshot residue, glass, heavy-metal poisons

• Sample preparation:

− for inorganic analysis: acid digestion for isolating elemental components and destroying organic and biological components

− for organic analysis: organic extraction to pluck the analytes from the sample without destroying it

• For qualitative analysis only – simple preparation and cleanup

• For quantitative analysis – more rigorous techniques – quantitative extractions and standardization required with goal: to isolate an analyte from the matrix and transfer it quantitatively to the final analytical solution

− quality control procedures to monitor efficiency of extraction

− internal standards, surrogate spikes, matrix spikes…

The Special K’s

Equilibrium constants – crucial importance in partition and separation processes

aA + bB ↔ cC + dD

- General equilibrium constant – Keq applies to any equilibrium

- Relative value of K describes the balance of products to reactants i.e determines whether products or reactants predominate when the system is at equilibrium

pK = -logK

?! -1

The Special K’s

Solubility equilibrium constant, Ksp

– solubility S of drugs and other solids – a critical consideration because of correlation to bioavailability and toxicology, on one side, and sample preparation and cleanup on the other

- solubility of salts, ionic character of drugs and larger molecules important because of possibility to manipulate it by changing pH, converting from insoluble to soluble salts…

- water soluble compounds = hydrophilic - lipophobic

The Special K’s

Octanol-Water Partition Coefficient, Kow (logP)– for drugs – solubility in fats as important as solubility in water – drugs

must cross a lipid membrane to enter a cell

- solubility in octanol is used for estimation fat solubility (lipophilicity)

for other lipophilic solvents:a,b-table values

- compounds with significant solubility in fats = lipophilic or hydrophobic

The Special K’s

Partition Coefficient (KD) – established between two phases and an analyte that does not undergo any chemical changes when moving between phases

Example: water-octanol extraction is a liquid-liquid partitioning – analyte moves between phases without chemical changes

Originally – equilibrium constant for partitioning = KD coef. of distribution

The value of KD depends on relative affinity of the analyte for each phase i.e.:

- Polarity (“like dissolves like”)

- Hydrogen-bonding interactions

- Ion-ion interactions

- Ion-dipole interactions

- Dipole-dipole interactions

Also of central importance to chromatography & chromatographic separations!

The Special K’s

Ka/Kb/Kw

Acid-base chemistry – central role in drug chemistry → drug analysis, toxicology, sample preparation → drugs classification: acidic, basic, neutral

Functional groups define classes:− amino groups → bases;− phenolic and carboxyl groups → acids,

− but weak bases and acids!

More than one acid or base group = ionizable center

− ionized drug molecule is soluble in water,

− un-ionized drug molecule is soluble in non-polar solvents

↔ acid-base character closely related to solubility!

Design of extraction: equilibrium is considered to be completely on one side if the concentration of the product substance is at least100 times > than the reactant or vice versa!

Example

In general:− un-ionized form = lipophilic→ prefers the organic phase

Partitioning with liquid phases:Solvent and Liquid-Liquid extraction

Solubility – function of relative polarities and basis of separation techniques

Sometimes: clean and simple separation (Ex.: cocaine hydrochloride, water soluble, diluted with insoluble cornstarch) but a rare situation in a forensic lab!

Simple or complex: “like dissolves like” is usually exploited:

− dry extraction – extraction of white powder with organic solvent (CHCl3) for selective extraction of drugs from diluents (sugars)

− liquid-liquid extraction (LLE) – analyte separated from one liquid and transferred into the other by partitioning

− suitable solvent chosen from the table;

− water ideal for ionic or polar analytes,

− non-polar (hexane or pentane) for nonionic or non-polar solvents.

Partitioning with liquid phases:Solvent and Liquid-Liquid extraction

Safety and exposure concerns

– Benzene, CCl4, C2H3Cl3 rarely used due to safety concerns.

– Use of CHCl3 and CH2Cl2 also reduced

– Cost of disposal

– Cost of solvents, purity proportional with price, use water whenever possible!

Finally: miscibility!– Usually used for LLE organic solvents immiscible with water: hexane, methylene

chloride or chloroform – may be a component in the sample

– If an analyte is more soluble in one liquid than in another (100 x or more), partitioning using LLE can be successful!

– Relative densities of solvents → which phase is which in the separatory funnel!

f

Water solubility and Partitioning

Water solubility of the analytes (drugs) – major concern for sample preparation and extraction

Also for toxicology: how, where and how quickly is a drug absorbed?

Again “like dissolves like” including acid-base character and solubility of salts!

Target analytes: ionic compounds, molecular compounds or salts:− neutral molecules soluble in organic solvents based on polarity, like dissolves like

− salts (cocaine HCl) soluble in water according to Ksp

Generally, therapeutic reagents designed to be water soluble under physiological conditions in order to facilitate their absorption into bloodstream.

Ionization Centers

Ionizable groups in drugs and metabolites:

− carboxylic acids (COOH)

− phenolic protons (Ar-OH)

− hydroxyls (R-OH)

− amino groups

− meprobamate – water insoluble, soluble in organic solvents according to polarity

− amphetamine in water:

amphet-NH2 + H2O ↔ amphet-NH3+ + OH-

− aspirin – acidic drug with one ionization center– COOH group, in water

HA ↔ H+ + A-

− more than one ionization center – rel. values o pKa dictate who ionizes first = smaller pKa!

− phenobarbital – non-ionized at pH <5.2; salicylic acid – non-ionized at pH <2.5

Ionization Centers

Amphoteric drugs – extraction and partitioning challenge!

− morphine

Selection of extraction pH?− high pH: basic group OK, acidic group ionized

− low pH: basic group ionized, acidic group OK

− in between: the isoelectric point - zwitterion at

for morphine: (9.85+8.02)/2 = 8.94

Ionization Centers

Different drugs forms depending on ionization state

− cocaine• hydrochloride = protonated cocaine Cl

(water soluble, sparkling, white powder - “snow”)• unprotonated (crack cocaine, freebase, oily,

less water soluble)• nitrate dihydrate, sulfate (water soluble)

− morphine as monohydrate, hydrochloride salt, acetate trihydrate, tartarate trihydrate, sulfate salt, pentahydrate sulfate

– different salts – different solubility in organic solvents

Common situation – use of a series ofacid-base extractions to isolate components based on their acid-base properties

Thin-Layer Chromatography, TLC

Chromatography crucial in forensic science – forensic chemistry

Thin-layer chromatography (TLC) or planar chromatography extensively used as a screening technique with:

−various solvent systems−standards−selective derivative reagents

−even for conclusive identification of many analytes

−for preparative work, as well.

Thin-layer chromatography (TLC) analysis− performed on glass plate or other support (aluminum) covered by solid phase (similar

or identical to ones for SPE)− analogous interactions to SPE (ion-dipole, dipole-dipole)− solvent systems – developed for specific applications, ex: ethyl acetate:

methanol:30%ammonia (17:2:3); cyclohexane:toluene:diethylamine (75:15:10)

− visualization: “fluorescent” plates, fluorescent analytes (LSD), developers (iodoplatinate for alkaloids, amines; Ehrlich’s reagent for LSD, mescaline; Marquis and Mandelin test reagents)

− Retention factor, Rf = (DX-D0)/(DS-D0)

1,3,4 forensic chem drugs analysis

Documents

analytical data

dimensionality of data

data generation

cluster analysis data

exploratory data analysis

data space goal

large data sets

forensic toxicology