Evaluation of Antemortem Ethanol Concentration PBPK Modeling Approaches and Postmortem Ethanol Generation and Transport ConsiderationsCowan, DM, JR Maskrey, ES Fung, T Woods, LM Stabryla, PK ScottCardno ChemRisk • 415-896-2400 • www.cardnochemrisk.com

ABSTRACT

Ethanol concentrations in biological matrices offer crucial information regarding the level of intoxication of an individual at the time of death.

The antemortem levels of ethanol are typically calculated retrospectively using a modeling approach from postmortem measured concentration with

little consideration regarding the change in ethanol concentration with time after death. However, uncertainties such as body conditions, environmental

conditions surrounding the body, biological matrices, storage and analytical methodology are associated with retrospective calculations. Therefore, the

objective of this study was to: 1) evaluate the typical relationships between ethanol concentrations in various biological matrices, 2) compare and contrast

existing PBPK modeling approaches for determining ethanol concentrations under normal living physiological conditions, 3) present an empirical modeling

approach for correlating postmortem ethanol concentrations with PBPK modeled antemortem concentrations up until the time of death, and 4) describe best

practices for determining antemortem and postmortem ethanol concentrations with a focus on potential sources of error. In order to generate an empirical modeling

approach, we evaluated existing PBPK model parameters including ADME, body type, the Widmark Factor as well as novel factors including ethanol tolerance and

ethanol dehydrogenase level. The PBPK modeling approach also includes a novel method for superimposition of multiple doses of ethanol consumed at various times,

and suggestions for adjusting the elimination rate based on body weight. We analyzed available data on postmortem ethanol production and identified conditions and potential markers for ethanol production through decomposition and putrefaction. Case studies are provided to highlight changes in ethanol concentration in biological matrices. These data indicate that this novel empirical model provided an accurate estimation of ethanol concentration while minimizing potential sources of error. This study provides further data to help standardize the process of determining ethanol concentration in the field of forensic toxicology while minimizing uncertainties in real world cases.

INTRODUCTION

> Although ethanol use is prevalent in society and ethanol metabolism has been studied by scientists for more than 100 years, it remains a challenge to precisely determine blood ethanol concentration (BAC) following ethanol consumption due individual variability in body and metabolism characteristics (e.g., age, weight, height, body mass index, liver health, state of nourishment, state of hydration and basal metabolic rate), variability in mass of ethanol present in beverages (beer, wine, spirits), and the biological matrices sampled to determine the blood ethanol concentration (e.g., blood analysis, breath analysis, etc.).

> The physiological effects of ethanol ingestion follow a dose-response relationship (Figure 1). Ethanol is a small, polar molecule, and therefore tends to accumulate in water-rich areas of the body and does not significantly diffuse into fatty tissues. Ethanol is eliminated from the human body by a specific metabolic pathway (Figure 2).

> The Widmark Equation was first proposed by E.M.P. Widmark in 1932, and is a common approach used to retrospectively estimate blood ethanol concentrations in persons who have consumed a known mass of ethanol. This equation is an empirically based formula that takes into account both the metabolic absorption rate constant, the elimination rate for ethanol in human bodies, and the “Widmark Factor.”

> In this evaluation, a modification to the Widmark Equation was proposed to ensure the accurate prediction of blood ethanol concentration after the consumption of multiple drinks over time. Specifically, superimposition of multiple Widmark Equations was used to more accurately reflect BAC with multiple drinks.

> Precise determination of BAC at the time of death can also be challenging because many variables must be considered (e.g., presence of a preservative, sample storage condition, variation in sampling sites, putrefaction and postmortem ethanol neoformation).

> Furthermore, a key variable in the determination of BAC at the time of death for postmortem blood samples is the level of contamination. Blood and other biological matrices can be potentially contaminated with bacteria and other agents capable of generating ethanol (mostly from glucose) through the process of putrefaction. This contamination and neoformation of ethanol can confound identification of BAC at time of death.

> In this evaluation, a novel antemortem ethanol modeling approach is combined with postmortem ethanol concentration analysis to generate accurate predictions of blood ethanol concentration at time of death, thereby optimizing and standardizing forensic approaches in real world cases.

Figure 1: Dose-dependent Responses to Ingestion of Alcohol

Figure 2: Metabolic Pathway for Elimination of Ethanol in Humans

𝐵𝐵𝐵𝐵𝐵𝐵 =𝐵𝐵𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖(1 − 𝑒𝑒−𝑘𝑘𝑖𝑖)

𝑟𝑟𝑟𝑟− (𝛽𝛽𝛽𝛽)

> We propose superimposition of multiple Widmark Curves as an approach for determining BAC, when variable consumption patterns over time make the standard single time point modeling approach prone to overestimation of BAC.

> Therefore, an adjustment can be made to the Widmark Equation to accurately estimate the BAC from multiple drinks. Typical drinking doses of ethanol are often insufficient to saturate the enzymes responsible for ethanol elimination. Assuming that the elimination rate is zero-order with respect to the blood ethanol concentration, simple superimposition of multiple Widmark Curves can accurately account for multiple ethanol-containing beverages consumed at different times throughout a specific time period.

where,

BACn = Blood ethanol concentration from the nth drink (g/L)tn = Time of the nth drink (hr)

The following case studies are designed to compare and contrast the standard and modified Widmark Approaches:

𝐵𝐵𝐵𝐵𝐵𝐵𝑛𝑛 =𝐵𝐵𝑖𝑖𝑛𝑛𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖(1 − 𝑒𝑒−𝑘𝑘𝑖𝑖𝑛𝑛)

𝑟𝑟𝑟𝑟− (𝛽𝛽𝑡𝑡𝑛𝑛)

Comparison of Approaches> In the second case study, the traditional Widmark Approach predicted a maximum BAC that

was 1.5 times larger than the maximum BAC predicted by the modified approach that accounts for drinks consumed at various times.

> Also, the time required to reach the maximum BAC is 22% shorter in the original approach.> In forensic investigations, the difference between the maxima can be very significant if the

traditional Widmark Approach predicts a maximum BAC above legal limits while the modified superimposition approach predicts a maximum BAC below legal limits.

> The Widmark Approach is used in many forensic ethanol-related investigations. It is therefore important to combine an understanding of the differences in blood ethanol concentration that are achieved due to gender, weight, height, age, BMI and other body factors, which are well-described in the literature, with a modified modeling approach based on variable drinking patterns as illustrated by Figure 4.

Postmortem Ethanol Generation > A number of biological matrices including blood, vitreous humor, hair, muscle, urine and

internal organs are sampled forensically to determine level of ethanol intoxication and cause of death. Blood, vitreous humor and urine are the three most common biological matrices for determination of BAC.

> Of these three matrices, the vitreous humor is often cited as the least prone to microbial contamination because of its biological remoteness in the human body. However, microbial contamination of the VH may result from significant head/eye trauma. The vitreous ethanol concentration (VAC) to BAC ratio generated provides valuable information regarding the ethanol metabolic state in the individual, especially in forensic-related cases.

> A VAC:BAC ratio of less than one implies that the individual was in the absorption phase prior to equilibrium; a ratio greater than one implies that the elimination phase is reached. Deviation from typical VAC:BAC ratios may suggest ethanol consumption or production by microorganisms.

> However, authors of some studies have concluded that the VAC:BAC ratio is unreliable for determination of the source of ethanol. A literature survey of postmortem VAC:BAC ratios presented in Table 2 provide a frame of reference for the ethanol metabolic state.

> Postmortem neoformation of ethanol by microorganisms often complicates findings from biological matrices. At least 58 species of bacteria, 17 species of yeast and 24 species of molds is capable of producing ethanol from glucose. Information on 19 species relevant to postmortem ethanol generation in human bodies is presented in Table 3.

> Presence of microorganisms in samples with detectable ethanol concentration but no evidence of ethanol consumption suggests postmortem production as the potential source of ethanol. Findings from this table suggest that sample handling, storage conditions and time between death and analysis contribute to the potential for postmortem neoformation of ethanol production. Additionally, various biological indicators of putrefaction were identified, including other short-chain ethanols such as n-propanol, methanol and isopropanol.

> The combination of these indicators can be used to quantitatively determine the ethanol concentration generated by microbes with considerable reliability.

DISCUSSION

> The Widmark Approach is a relatively accurate approach for determination of BAC as a function of time for an individual, provided that adjustments are made for ethnicity, body mass index, age and individual metabolic rate. Adjustments for these factors are well described in the literature, yet few forensic investigators have used all of them together. Lastly, superimposition of multiple Widmark BAC curves is a reasonable method for estimation of BAC over time for a person who consumed multiple ethanol-containing beverages at different times, and this approach results in a more precise estimate of maximum BAC and the time to maximum BAC than assuming all drinks were consumed at once.

> Understanding the differences between absorption phase versus elimination phase of ethanol metabolism is crucial.

> During the absorption phase, equilibrium is not reached and the blood ethanol concentration may not fully reflect the state of intoxication of the individual. Whereas in the elimination phase, equilibrium is reached, therefore better reflecting the influence of ethanol on the individual.

> When a determined VAC:BAC ratio deviates from the predicted ratios and the general ethanol metabolism timeline, it suggests the potential for postmortem ethanol consumption or production.

> It is commonly assumed that the source of ethanol found in postmortem biological matrices originates from the consumption of ethanol; however, a lesser known phenomenon suggest that ethanol may also be a result of postmortem ethanol production by microorganisms.

> Key indicators or biomarkers of postmortem neoformation of ethanol from the processes of putrefaction include: n-propanol, methanol and isopropanol. Concentration of these indicators can be used to quantitatively estimate the concentration of ethanol produced; however, this may be limited by laboratory techniques. Other biomarkers of postmortem formation of ethanol include: 1-propanol, 2-propanol, sec-butanol, isoamyl alcohol, isobutanol, isopentanol, diethyl ether, acetaldehyde, formaldehyde, phenylethanol and p-hydroxyphenylethanol.

> Taken together, these findings will allow for a more accurate estimation of the ethanol concentration at the time of death.

> Combination of the modified Widmark Approach for estimation of BAC prior to death with modeling considerations for postmortem generation allows for a more accurate estimation of the true BAC at the time of death.

REFERENCES

Available upon request

Table 1: Explanation of Widmark Equation Parameters and Example Values for Each Parameter

Figure 3: Comparison of 6 ft, 70 kg, 30 year old Male with 5.5 ft, 55 kg, 30 year old Female BAC% Responses to One Shot of 80-proof Liquor

Figure 4: Comparison of BAC% for a 6 ft, 70 kg, 30 year old Male Consuming Three Shots of 80 Proof Liquor by Two Different Drinking Patterns

Table 2: Reported vitreous and blood alcohol ratios

Table 3: Ethanol produced by microorganisms in biological matrices

METHODS

A comprehensive literature search was performed using Pubmed, Elsevier and Google scholar to identify published studies that have evaluated:

> Relationships between ethanol concentrations in various biological matrices> PBPK modeling of ethanol concentrations and the dependence of ethanol concentration on

gender, body weight, body mass index (BMI), height, age, ethnicity, elimination rate, absorption rate and dependence on ethanol

> Evidence of putrefaction and postmortem ethanol generation by various species of microorganism

> The reliability of methods used to determine ethanol concentration in postmortem samplesBased on these findings, we propose an adjusted empirical model to accurately estimate the blood ethanol concentration following ethanol consumption and a novel approach to understand the confounding factors that affect postmortem blood ethanol concentration.

RESULTS

Antemortem Ethanol Concentration PBPK Modeling> The standard Widmark Equation for calculating BAC is described below and parameters

affecting the Widmark Equation are presented in Table 1.

Where:

BAC = Blood ethanol concentration resulting from the drink (g/L)Aingested = Mass of ethanol contained in the drink (g)r = Widmark Factor (unitless)W = body weight (kg)k = absorption rate constant (hr-1)t = Time since the drink (hr)ß = Elimination rate [(g/L)/hr]

Case Study #1: The Standard Approach (Figure 3)> To illustrate the differences in blood ethanol concentration (BAC) predicted by the Widmark

Equation between genders, a hypothetical case study was created where a 6 ft, 70 kg male and a 5.5 ft, 55 kg female both drink one shot (1.5 oz) of 80-proof liquor. The Widmark Approach was applied to estimating the BAC of these two individuals over a 90 minute time period. All four Widmark Factor estimation approaches presented in Table 1 were applied, and the values were averaged to determine the Widmark Factor used. The absorption rate constant was set equal to 5 hr-1 for both individuals. Elimination rates were 0.162 g/L/h for the male and 0.179 g/L/h for the female. Figure 3 gives the estimated BAC of the two individuals, which shows that the female reaches a maximum BAC of 0.027% while the male only reaches a maximum BAC of 0.016%, which is only 57% of the female maximum concentration. Also, the male in this case reaches the maximum concentration at 24 minutes, while the female reaches the maximum concentration at 26 minutes, which showcases the gender-specific differences in elimination rates and Widmark Factors.

Case Study #2: The Modified Widmark Approach (Figure 4)> Based on this approach, a second hypothetical case study was created to illustrate the more

precise BAC estimation over time by superimposition of multiple Widmark Curves. In this case study, a 6 ft, 70 kg, 30 year old male consumes three shots (1.5 oz) of 80-proof liquor over a 45 minute period. The man’s BAC was modeled for 90 minutes. One model was run assuming that all three shots were consumed immediately at the start of the drinking period (using the traditional Widmark Approach), and the other model was run assuming that one shot was consumed every 15 minutes (using the modified Widmark Approach). Figure 4 compares the results of the two modeling approaches. The instantaneous drinking approach resulted in a maximum BAC of 0.064% at 36 minutes after the first drink, while the time-spread drinking approach resulted in a maximum of 0.043% at 44 minutes after the first drink. Also note that the spread out approach results in a faster decline of BAC in the 60 – 90 minute time range than the immediate consumption approach does.