Supplement A

1. Introduction/Problem Formulation

In the 2015 Proposed Amendment of the 1994 Tentative Final Monograph for over-the-counter (OTC)

antiseptic drug products1, FDA indicated that their administrative record for the safety of alcohol is

incomplete with respect to the availability of human pharmacokinetic studies under maximal use

conditions when applied topically (MUsT) and regarding data to help define the effect of formulation on

dermal absorption.

The data gap of human pharmacokinetic studies conducted under maximal use conditions when applied

topically can be addressed using a physiologically-based pharmacokinetic (PBPK) model for ethanol. In

addition, a PBPK model can be informative regarding the effect of formulation on the dermal absorption of

ethanol. Specifically, a PBPK model can be used to simulate maximal use conditions, to perform route-

to-route extrapolation such that dermal animal studies are not needed, and to assess variation in dermal

absorption for different formulations. PBPK modeling has long been recognized as the “gold standard” in

human health risk assessment for performing: (1) interspecies extrapolations; (2) route-to-route

extrapolations; and (3) high-to-low dose extrapolations. In addition, FDA has a strong history of using

PBPK model to support their assessments and decisions, including models developed for methylmercury

(Young et al., 2001), acrylamide (Doerge et al., 2008), bisphenol A (Fisher et al., 2011; Yang et al., 2013),

formaldehyde (Mitkus et al., 2013), and methylphenidate (Yang et al., 2014). U.S. FDA has also used

PBPK models to evaluate drug interactions (Grillo et al., 2012; Vieira et al., 2012; Wagner et al., 2015),

and metabolism in pregnant women (Ke et al., 2013, 2012). Furthermore, the PBPK program of the

Division of Pharmacometrics at FDA has outlined their mission as follows:

To review the adequacy of submitted PBPK models by drug developers in their ability to support

intended purposes at different stages of drug development;

To facilitate Investigational New Drug (IND) and New Drug Application (NDA) review process

through de novo analyses;

1 Federal Register / Vol. 80, No. 84 / Friday, May 1, 2015 / Proposed Rules.

To support regulatory policy through scientific research and maintenance of a PBPK

knowledgebase; and

To harmonize regulatory recommendations on the use of PBPK with non-US regulatory body and

reach out to scientific community to advance the science of PBPK.

For this reason, a PBPK assessment was conducted for ethanol for submission to U.S. FDA. The text

below describes the methods and results for refining and applying a PBPK model to a human health risk

assessment for ethanol.

2. Methods

A focused literature search was performed on PubMed to identify:

PBPK modeling papers for ethanol; and

Pharmacokinetic studies for ethanol in humans, with emphasis on studies evaluating dermal

exposures and hand sanitizer use. Pharmacokinetic studies for ethanol following other routes of

exposure exposures have also been identified, in case these pathways need to be further

evaluated as well.

The reference lists of key papers and recent reviews were also consulted to identify additional references.

Information from key modeling and pharmacokinetics papers has been tabulated in Table SA1 and Table

SA2, respectively.

2.1. PBPK Model Selection

Key PBPK model papers for ethanol were identified and are summarized in Table SA1. There are

essentially three families of models for ethanol (1) Martin et al. (2015, 2014, 2012), which is based upon

the Pastino et al. (1997) model; (2) Huynh-Delerme et al. (2012) / Dumas-Campagna et al. (2014), which

is also based upon the Pastino et al. (1997) model; and (3) Umulis et al. (2005), which appears to have

been developed independently. The PBPK models of Martin et al. (2015) were chosen to support an

assessment for ethanol. This group of models has been under development by a strong team of modelers

from NHEERL/NCEA/ORD/USEPA, as well as The Hamner Institute, over the past few years. These

models describe the pharmacokinetics of ethanol in pregnant and non-pregnant mice, rats, neonatal rats

and humans, and have been published in respected peer-reviewed journals. Dr. Martin provided the code

for the pregnant and non-pregnant mouse, rat, and human models (Martin, 2014). The structure of the

model, as modified for this assessment, is depicted in Figure SA1.

Gaps were identified in the available models, including:

None of the models describe the absorption of ethanol through human skin.

o This gap was addressed by adding a dermal compartment to the existing PBPK model

None of the models describe the pharmacokinetics of metabolite ethyl glucuronide, which has

been increasingly used as a urinary biomarker of ethanol exposure.

o To address this gap we included metabolism and urinary excretion of ethyl glucuronide

(EtG) to the existing PBPK model.

2.2. Identification of Key Pharmacokinetic Studies for Ethanol

The pharmacokinetics of ethanol has been well studied (Table SA2). A sizeable number of human studies

have examined the dermal absorption of ethanol from hand sanitizers. In addition, a number of in vitro

studies were identified that evaluated the absorption of ethanol through human skin (Table SA3).

Although the majority of the hand sanitizer studies have focused on the dermal absorption pathway,

several recent studies have also included consideration of the inhalation pathway for ethanol that has

volatilized from skin (Ahmed-Lecheheb et al., 2012; Arndt et al., 2014; Bessonneau and Thomas, 2012;

Skipper et al., 2009). To support potential PBPK model refinements, additional studies regarding the

pharmacokinetics of ethanol in pregnant and nonpregnant humans and rodents following other routes of

exposure, as well as studies on urinary biomarkers are also identified in Table SA2.

3. PBPK Modeling Simulations to Support Internal Dose Assessment

The models of Martin et al. (2015, 2014, 2012) have been compiled and quickly evaluated for use in this

assessment. For the sake of consistency, ethanol concentration predictions from the model were

expressed in terms of blood ethanol concentration (mg/dL), which can readily be converted to other units

as follows:

0.01% Blood Alcohol Content (m/v) = 0.01 g/dL = 10 mg/dL = 100 mg/L Eq. 1

The text below describes how the PBPK model of Martin et al. was modified to accommodate dermal

exposures, as well as how the model was applied to support the human health risk assessment.

3.1. Modifications to Martin et al. PBPK Model

Two key changes were made to the PBPK model: (1) inclusion of metabolism and urinary excretion of

ethyl glucuronide (EtG); and (2) inclusion of a skin compartment (Figure SA1). The human model code,

based on Martin et al. (2014), but with added dermal compartment and phase II metabolism is given in

Appendix S1.

3.1.1. Metabolism and Urinary Excretion of Ethyl Glucuronide

The PBPK model was expanded to include the hepatic formation and urinary excretion of EtG, since this

metabolite is frequently used as a biomarker for ethanol exposures. This pathway was parameterized

using data for urinary excretion of EtG following oral exposure to ethanol (Rosano and Lin, 2008). The

authors reported that the percent of ethanol excreted as EtG was small (<0.02% of the administered

dose) and dose-dependent, becoming a larger percentage of administered dose with higher oral doses.

The authors hypothesized that this dependency was due to saturation of oxidative metabolic pathways for

ethanol. The data was reported as percent EtOH, and amount was calculated based on molar-corrected

percentages. Because ethanol exposures following hand sanitizer use are expected to occur at low doses

(<3 g ethanol), the PBPK model was parameterized using the low-dose (3 g ethanol) EtG data of Rosano

and Lin (2008). By fitting the low dose data, the model under predicts the formation/excretion of EtG at

higher doses (6-24 g ethanol) (Figure SA2).

3.1.2. Skin Compartment

A compartment was added to the PBPK model for dosed skin to permit an assessment of dermal

absorption of ethanol following hand sanitizer use. The skin compartment in the PBPK model was

comprised solely of the area of the skin exposure. The remainder of the skin was

included in the slowly perfused compartment. Absorption is based on permeability (Kp) and partitioning

from the skin into the blood. Several sources were identified for defining dermal permeability coefficients:

In Vitro Studies for Kp – Several studies were identified that measured the dermal absorption of

ethanol through human skin in vitro (Table SA3). Kp values from these studies range from

0.0003-0.035 cm/hr.

In Vivo Studies for Kp - Several studies were identified that measured ethanol in blood or urinary

EtG concentrations following controlled dermal exposures (e.g., contributions by indirect

inhalation exposures were minimized or eliminated) (Arndt et al., 2014; Kirschner et al., 2009;

Lang et al., 2011; Skipper et al., 2009). The PBPK model was fit to these data by adjusting the Kp

value and the skin partition coefficient (PSKL) (Figure SA3). Fitted Kp values for these studies

range from 0.017-0.035 cm/hr, using a skin:blood partition coefficient of 0.2.

In Vivo Studies for Apparent Kp - Several studies were identified that measured blood

ethanol/urinary EtG concentrations following uncontrolled dermal exposures (e.g., exposure

reflect a mixture of dermal and inhalation routes) (Arndt et al., 2014; Kramer et al., 2007; Skipper

et al., 2009). For the purposes of simulating these data, the inhalation route was set to zero and

all biomarkers of exposure were attributed to the dermal route. The PBPK model was fit to these

data by adjusting the Kp value (Figure SA4). Fitted Kp values for these studies range from 0.8-5

cm/hr, also using a skin partition coefficient of 0.2. It should be noted that for some data sets, it

was difficult to match the data by only adjusting Kp (i.e., blood ethanol concentrations were higher

than could readily be explained by dermal uptake alone under the conditions described).

A comparison of Kp values for ethanol from these three sources is provided in Figure SA5. The range of

Kp values from in vitro studies is fairly consistent with the range of values from in vivo studies in which

exposures were exclusively via the dermal route. However, the apparent Kp values needed to describe

data from studies with uncontrolled exposures to ethanol in hand sanitizers (i.e., those that may include

inhalation exposures in addition to dermal) were approximately two orders of magnitude higher. The large

difference is best explained by a large contribution of the inhalation route for data sets in which exposures

were not controlled. This hypothesis is confirmed by the results of several studies (Arndt et al., 2014;

Bessonneau and Thomas, 2012; Skipper et al., 2009), in which the authors concluded that the inhalation

route was an important route of exposure for ethanol in subjects using hand sanitizer. Based on the PBPK

model predictions for the data sets of Arndt et al. and Skipper et al. for percent of dose absorbed, the

dermal pathway only contributes 3-24% of the total exposure (dermal and inhalation combined).

3.2. Exposure Assessment

The human PBPK model (Martin et al., 2014) was used to simulate human exposure with the following

assumptions:

All human simulations were conducted for a non-pregnant woman (64 kg) as a surrogate for early

pregnancy conditions. This is expected to be conservative since during the course of pregnancy

the volume of distribution is expected to increase, resulting in lower values for internal dose

measures for a given applied dose.

The PBPK model was used to predict blood levels of ethanol.

For this assessment, the inhalation component of the PBPK model was set to zero, and the

dermal pathway was assessed using an apparent Kp value (5 cm/hr) estimated above for the

study of (Kramer et al., 2007). This value corresponds to a maximum for the flux of ethanol

through human skin (i.e., higher Kp values do not result in higher absorption). By using this Kp

value, it is assumed that any contributions from inhalation pathway (from ethanol that has

volatilized from the skin) are implicitly incorporated into the modeled dermal pathway.

Several exposure scenarios were assessed for healthcare workers using alcohol-based handrubs

(ABHRs):

(1) Average Use Hand Hygiene Scenario – This exposure scenario was defined to consist of 1.3 mL

of 90% ethanol or approximately 1.2 mL ethanol (14.4 mg/kg, assuming a 64 kg body weight),

applied to the front and back of hands. The model was used to simulate this exposure repeated

7x per hour over a 12-hour work shift (Figure 4A).

(2) High Use Hand Hygiene Scenario – This exposure scenario was defined to consist of 1.3 mL of

90% ethanol or approximately 1.2 mL ethanol (14.4 mg/kg, assuming a 64 kg body weight),

applied to the front and back of hands. The model was used to simulate this exposure repeated

22x per hour over a 12-hour work shift (Figure 4A).

(3) Intensive Use Hand Hygiene Scenario – This exposure scenario was defined to consist of 1.3 mL

of 90% ethanol or approximately 1.2 mLethanol (14.4 mg/kg, assuming a 64 kg body weight),

applied to the front and back of hands. The model was used to simulate the same exposure,

repeated every 2 minutes, or 30 times per hour (30x/hour), over a 12-hour work shift (Figure 4A).

(4) Typical Use Surgical Scenario – This exposure scenario was defined to consist of 6 mL of 61%

ethanol (based upon current predominant use) every 4 hours over a 12-hour work shift (Figure

4B), applied to hands and forearms.

(5) Intensive Use Surgical Scenario – This exposure scenario was defined to consist of 20 mL of

90% ethanol every 4 hours over a 12-hour work shift (Figure 4B), applied to hands and forearms.

Details for the exposure scenarios are summarized in Table SA4, and the predicted internal doses are

provided in Table SA5. The Hygiene Scenarios demonstrate that steady state is reached quickly (within

~4 hours) (Figure 4A). Additional simulations for the Hygiene Scenarios assuming a 70% ethanol content

instead of 90% (not shown) indicated that the resulting internal doses are linearly proportionate to ethanol

content. For the Surgical Scenarios, there is little difference between the magnitudes of the peaks after

each exposure event (i.e., no appreciable accumulation of ethanol in blood when exposure events are

spaced 4 hours apart) (Figure 4B). Under these simulated exposure conditions, the PBPK model predicts

that both peak blood concentrations and AUC values are approximately linear with dose.

3.3. Supplemental PBPK Model Simulations

The human PBPK model was also used to simulate additional screening level exposure scenarios to

support the toxicity assessment (internal doses under the exposure conditions of epidemiology and

toxicity studies), and a discussion of comparative risks (internal doses associated with common

exposures to ethanol). These additional scenarios and their corresponding internal dose predictions from

the PBPK model are summarized in Table SA6 for toxicity simulations, and in Table SA7 for comparative

risk simulations. Simulations for comparative risks were run for a single exposure event, and under

assumptions of 2 or 3 exposure events per day (assuming events occur 4 hour apart). Because ethanol is

rapidly cleared from the body, peak blood ethanol levels for multiple exposure events per day are the

same as predicted for a single exposure event (Table SA7). AUC values for multiple exposure events,

when separated by several hours, are simply multiples of those predicted for a single exposure event.

4. Summary and Discussion

PBPK models are tools that can be used to support extrapolations made in human health risk

assessment, including those made across species, from high dose to low doses, and across routes of

exposure. U.S. FDA has embraced the use of PBPK models to support many of its risk-based decisions.

For example, from 2008-2011, the Office of Clinical Pharmacology at the U.S. FDA received 25

applications that included PBPK analyses, including those addressing drug interactions, pediatrics,

pharmacogenomics, hepatic impairment, and absorption (Zhao et al., 2012). The PBPK model of Martin

et al. (Martin et al., 2015, 2014, 2012) was modified to permit an assessment of dermal exposures to

ethanol following hand sanitizer use. The model was defined to include a skin compartment, and

expanded to describe the formation and excretion of ethyl glucuronide. The modified PBPK model was

used to support a human health risk assessment for hand sanitizer use. The model was specifically used

to predict blood ethanol concentrations in: (1) humans for a variety of hand sanitizer use scenarios; (2)

rodents and humans for a variety of oral exposures associated with adverse effects; and (3) in humans for

a variety of common oral and inhalation exposures to ethanol that are not associated with hand sanitizer

use.

The revised PBPK model for ethanol was used to predict internal doses (blood ethanol levels) in humans

under intensive (maximal) use scenarios (Table SA5). These predictions can be used to address the

absence of human pharmacokinetic studies under maximal use conditions when applied topically (MUsT).

There are several sources of uncertainty in this assessment:

Other than the addition of a skin compartment and inclusion of ethyl glucuronide excretion, the

model of Martin et al. (2015, 2014, 2012) is essentially unchanged. Ethanol is rapidly metabolized

by the aldehyde dehydrogenases, which are saturated at levels associated with typical human

alcohol consumption. According to the current version of the model, this saturation occurs in

humans at oral doses of approximately 50 mg/kg (~3.2 g), which is consistent with known effects

of drinking alcohol. In mice, this saturation is predicted to occur at a slightly lower oral dose

(approximately 10 mg/kg). This model is considered to be validated. Thus, no additional efforts

were made to critically review some of the decisions and data sets applied in its development.

No changes were made to the model parameters for describing ethanol metabolism, despite

identifying some data sets that might be useful for characterizing nonlinear pharmacokinetics

[e.g., nonlinear data for EtG excretion of Rosano and Lin (2008) may be useful for refining model

parameters that describe the saturable oxidative metabolism of ethanol].

Inhalation exposures to ethanol in air, after volatilizing from skin, were not explicitly evaluated in

this assessment. Instead, any contributions from the inhalation pathway were implicitly included in

the dermal pathway with an “apparent” Kp value derived from data that reflect both inhalation and

dermal exposures (Kramer et al., 2007). Data from the published literature (Arndt et al., 2014;

Skipper et al., 2009) suggest that the inhalation route is the primary route of exposure responsible

for detectable levels in blood and urine. Use of an “apparent” Kp value forces all exposures

evaluated in this assessment to become more episodic (i.e., assuming all ethanol detected in

blood and urine is absorbed in the short time prior to volatilization), whereas inhalation exposures

to ethanol are expected to be more prolonged in duration. This assumption may impact the

predictions of the PBPK model for peak blood levels of ethanol following dermal exposure. It may

be possible to incorporate a quantitative evaluation of the inhalation pathway within the PBPK

model for ethanol. The inhalation pathway is already parameterized for the Martin et al. model,

and there are data that may be used to estimate air concentrations. There are several ways to

incorporate the inhalation pathway:

1. Rely upon published environmental monitoring studies. For example, Bessonneau et al.

(2013) measured ethanol concentrations in hospital air over a three-day period. Ethanol

was frequently detected with concentrations ranging from 0.0003-3.956 mg/m3, with an

arithmetic mean of 0.928 mg/m3.

2. Rely upon empirical relationships between hand sanitizer use and air concentrations.

Hautemanière et al. (2013) reported a good correlation between the amount of hand

sanitizer used and the concentrations of ethanol detected in air (Figure S7). Preliminary

evaluations suggest that this relationship could be extended to other data sets.

3. Rely upon modeled air concentrations that explicitly account for volatilization rates, room

size, and room ventilation rates.

Background levels of ethanol are detectable in blood. Efforts were made in this assessment to

focus on modeling “added” ethanol in blood, by subtracting out background levels present prior to

exposure. For some data sets, the levels of ethanol detected following exposure are only slightly

above background levels, and therefore values for “added” ethanol are very sensitive to the value

used for background (i.e., signal-to-noise problem), which is itself variable.

Some of the pharmacokinetic data sets for ethanol are limited, and required a number of

assumptions for use in the model. For example, data for EtG present in spot urine samples

requires assumptions for urine volume and time since last void.

For some of the dermal studies, data are presented for individuals. No attempts were made to fit

the PBPK model to individual data. Instead arithmetic means were calculated for the group of

exposed individuals, and then the model was fit to the mean values. In addition, no attempts were

made at this point to characterize variation in model parameters to assess their impact on

predicted blood ethanol levels, or to address the potential impacts of sensitive subpopulations

(e.g., genetic polymorphisms in metabolizing enzyme systems).

Despite these sources of uncertainty, the PBPK model predictions in this assessment are expected to be

conservative. The apparent Kp value used to characterize exposure (5 cm/hr) is expected to overestimate

the true contribution of the dermal pathway by more than an order of magnitude. Because contributions of

the inhalation pathway were implicitly included in the dermal pathway characterized with an apparent Kp,

exposures for the inhalation pathway were modelled to be more episodic (i.e., uptake of ethanol forced to

occur during the short time period prior to volatilization from skin, in terms of seconds) rather than

prolonged (e.g., remaining in room air for an extended period of time, in terms of minutes to hours).

Because of this assumption, the peak concentrations of ethanol in blood predicted by the PBPK model

may overestimate the actual peaks. In addition, the magnitude of the inhalation component of exposure is

going to depend upon the number of individuals present in a room who are using hand sanitizer at a given

time. The number of hand sanitizer users per room tested under experimental conditions may not

accurately reflect the number of users anticipated under actual use conditions. For example, Ali et al.

(2013) assessed hand sanitizer use in groups of 25 individuals. For this reason, any future quantification

of the inhalation pathway needs to consider to what degree experimental conditions might result in an

overestimation of this pathway under actual use conditions due to experimental design.

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6. Tables and Figures

Table SA1. Summary of Key PBPK models for ethanol

Study Species Route Notes

Umulis et al. (2005) Human OralEmphasized metabolism, attempts to describe

acetaldehyde.

Huynh-Delerme et al.

(2012)Human Inhalation

Case study, nurse with pancreatitis. Based on calculated

inhaled EtOH.

Dumas-Campagna et al.

(2014)Human Inhalation

Whole body exposure chamber, and ventilation rates,

though not clear how rates measured or optimized.

Pastino et al. (1997) 1 Rats, mice, humans Inhalation The foundation model for the future Martin et al. models.

Martin et al. (2012) 1Updates: pregnant and

neonatal rat

Updates:

oral, iv, and

inhalation

Simplified neonatal rat compartments with polynomials

to fit early growth.

Martin et al. (2014) 1Updates: nulliparous rat

and GD 12Inhalation Adds ability for repeat inhalation dosing.

Martin et al. (2015) 1

Updates:

Mouse and human

separate nulliparous and

pregnant models

Intravenous and

Oral

This is the final model from this series. Rat model scaled

to mouse, rat not included.

1. The following publications describe inter-related models developed by Hamner (CIIT)/USEPA. Publications outline progression of suite of models.

Table SA2. Summary of key pharmacokinetic studies for ethanol

Study Species Route Notes

General Human (oral and inhalation)

Caballeria et al. (1989) Human Oral

Halter et al. (2008) Human Oral White wine

Jacobi et al. (2005) Human Oral EtOH loss through skin

Jones et al. (1988) Human Oral Tablet, measured acetaldehyde, used ALDH inhibitor

Lester and Greenberg (1951) Human Oral Oral - Reported in Pastino et al. (1997)

Roine et al. (1993) Human Oral Volunteers drank different beverages

Roine et al. (1991) Human Oral

Marshall et al. (1983) Human Oral

Wilkinson et al. (1977) Human Oral

General Rodent (oral, inhalation, iv, ip)

Brand et al. (2006) Rat Oral Plasma and skin levels measured. EtOH not purpose of study.

Caballeria et al. (1987) Rat Oral Oral

Eriksson and Sippel (1977) Rat Oral Multiple tissues

Kozawa et al. (2007) Rat iv

Lim et al. (1993) Rat Oral Multiple routes - iv, oral, intraportal, intraduodenal infusions

Livy et al. (2003) Mouse Oral, IP

Pastino et al. (1997) Rats, Mice Inhalation

Quertemont et al. (2003) Rat Oral

Roine et al. (1991) Rat Oral

Urinary Biomarker

Helander et al. (2009)Humans

(Alcoholics)Oral Biomonitoring of urinary ethyl glucuronide and sulfate

Helander and Beck (2005) HumansOral – controlled

exposureUrinary sulfate and glucuronide,

Høiseth et al. (2008) HumansOral – controlled

exposure

EtG highest biomarker, EtS and 5-hydroxyindole-3-acetic acid

(HIAA) all detected

Sarkola et al. (2003) HumansOral – controlled

exposureUrinary Ethyl gluc and 5-HIAA

Hand Sanitizer

Ahmed-Lecheheb et al. (2012) Human Dermal Biomonitoring. Acetaldehyde and alcohol blood and breath.

Blood and urine levels were generally non-detected. Exhaled

breath contained detectable levels. Hand sanitizer use data

collected (~30 g/hr)

Ali et al. (2013) Human Dermal

3 groups of 25 volunteers. Volunteers exposed to 1.5-3 g of

hand sanitizer. Dose-dependent increase in exhaled breath

readings for BAC

Arndt et al. (2014) HumanDermal,

Inhalation

Volunteers were exposed to hand sanitizer through inhalation-

only, dermal-only, and inhalation and dermal exposure. Time-

course data for urinary Et-G showed EtOH was primarily

absorbed via inhalation.

Bessonneau and Thomas (2012) HumanDermal,

Inhalation

Inhaled dose during hand disinfectant - air sampler

measurements, reported peak. Time-course data for EtOH in

air up to 100 sec post application, found very low level of

dermal absorption.

Bessonneau et al. (2010) Human Review. No PK data

Brown et al. (2007) HumanDermal,

Inhalation

Biomonitoring. Alcohol blood and breath. Limited time-course

data for EtOH in serum and exhaled breath up to 13 min post

exposure

Jones et al. (2006) Human Dermal Urinary EtG data for up to 20 hours after hand sanitizer use in

two individuals and 2 application rates. Indicates EtG is a

sensitive marker of EtOH exposure.

Kirschner et al. (2009) Human Dermal

Serum ethanol levels in individuals exposed to ethanol

solution or ethanol in product (Softasept). Slight increase in

concentration at 15 min but not at 60 minutes.

Kramer et al. (2007) Human

Dermal

(inhalation) –

controlled

exposure

Volunteers washed hands using 3 different preparations with

55-95% w/w EtOH at 2 volumes –blood EtOH and

acetaldehyde time course up to 120 min post application

(hygiene & surgical scenarios).

Lang et al. (2011) Human

Dermal –

controlled

exposure

Exposures on gauze - no real dermal absorption. EtOH levels

present at pre-exposure times (~0.3 mg/L) & showed no

significant increase post exposure (insufficient data to model).

Miller et al. (2006) Human

Dermal

(inhalation) –

controlled

exposure

Volunteers applied 5 ml of hand rub product containing 62%

EtOH, 50 times in 4 hr. Blood levels were non-detect (<5

mg/dL)

Reisfield et al. (2011) HumanDermal

(inhalation)

Urine measured in volunteers using hand-sanitizers constantly

for 3 days - spot samples, not total. Urinary EtG & EtS

Rosano and Lin (2008) Human Dermal Volunteers applied hand sanitizer 20x per day for 5 days; the

followed 7 days post exposure. Urinary EtG each day for each

individual. Dose-response was not as clear as observed

following oral exposures.

Rohrig et al. (2006) Human Dermal

Urinary EtG was not detected except for 1 individual, last time

points & highest exposure frequency (not enough data to

model). LOQ=0.05 mg/L

Skipper et al. (2009) HumanDermal and

Inhalation

Urinary EtG measured before, 30min after & 6 hours after

exposure in subjects. Time-course BAC data from

breathalyzer also available (crude but shows a decent trend).

Inhalation dominates over dermal

Dermal

Gajjar and Kasting (2014) human in vitro Dermal Effect of evaporation on absorption.

Pendlington et al. (2001)

Pig skin in vitro;

human topical

exposures

Dermal Evaporation compared.

Bonnist et al. (2011) Human in vitro DermalEthanol was used as one of the vehicles. Dermal penetration

measured

Neonatal and Developmental

Burd et al. (2012) Human Biomonitoring Fetal Alcohol Spectrum Disorders - info on metab clearance

variability

Fox et al. (1978) Human Oral GD 266 (late 3rd trimester)

Marek and Kraft (2014) Human Review

Nava-Ocampo et al. (2004) Human Oral GD 119 (2nd trimester)

Blakley and Scott (1984) Mouse ip GD10

Jiang et al. (2007) Mouse Oral GD10, GD15

Randall et al. (1994) Mouse Oral GD1, GD10, GD19 – repeat dosing

Ukita et al. (1993) Mouse ip, inhalation GD7

Badger et al. (2005) Rat Oral GD8, GD13, GD19

Hayashi (1991) Rat Oral GD20

Kelly et al. (1987) Rat Oral PND1, 2,4,6,8,10,15,21

Nelson et al. (1985) Rat Inhalation GD1-19

Zorzano and Herrera (1989) Rat Oral PND5, PND15

Table SA3. Summary of in vitro studies on the dermal absorption of ethanol

ConditionsKp

(cm/hr)Design Notes

Blank (1964)

Dilute in Saline 0.0003 Full-thickness Human skin

Diluted in: Isopropyl Palmitate 0.012 Full-thickness Human skin For diluted solutions of ethanol Kp values varied across

solvents, but were generally within the range reported

by other in vitro studies.

Diluted in: Olive Oil 0.003 Full-thickness Human skin

Diluted in: Mineral Oil 0.0025 Full-thickness Human skin

Scheuplein and Blank (1973)

100 µl EtOH 0.035 Full thickness

Kp increases for full thickness, increases in a water

vehicle.100 µl EtOH 0.0008

Epidermis,

Skin:blood partition coefficient =

0.2

Gajjar and Kasting (2014)

In Excel model code 0.0016 Not clear if used in model, stated as “optional”

5, 10, 20, 40 µl – 1.5 cm x 1.5cm2 0.0004 Split thickness cadaver skin Calculated from flux = 0.02 mg/cm/hr and exposure

(≅ 0.3 mm) – non-occludedconcentration of 5 mg/cm2 x 10 cm2/cm3 = (elsewhere

reported as 5 µl, which would yield a different result)

Kupczewska-Dobecka et al. (2010)

Calculated 0.0071

Range 0.0003 – 0.12*

Mean 0.008**

* Highest in vehicle that is hypothesized to increase absorption (Blank, 1964).

** Mean after removing the lowest and highest Kp estimates.

Table SA4. Exposure scenarios for hand sanitizer use

ParameterHand Hygiene Scenario Use Surgical Scenario Use

Average High Intensive Typical Intensive

Pregnancy Stage 1 Nonpregnant Nonpregnant Nonpregnant Nonpregnant Nonpregnant

Exposure duration (Hours) 12 12 12 12 12

Exposure Frequency 7x/hour 22x/hour 30x/hour 3x/12-hr shift 2 3x/12-hr shift 2

Product volume (mL) 1.3 1.3 1.3 6 20

Ethanol Content (% v/v) 90 90 90 61 90

Body weight 64 64 64 64 64

1. As surrogate for early pregnancy

2. Assume 4-hr interval

Table SA5. PBPK-predicted internal dose measures for hand sanitizer exposure scenarios

Hand Hygiene Scenario Use Surgical Scenario Use

Average High Intensive Typical Intensive

Peak EtOH in blood (mg/dL) 0.39 0.75 0.94 0.22 0.33

AUC (mg/dL*hr) 24hr 2.3 7.4 10.1 0.17 0.24

Table SA6. PBPK simulations for toxicity evaluations

Purpose Species Scenario Name Assumptions

Internal Dose

Peak

(mg/dL)

AUC24

(mg/dL*hr)

Epidemiology

Studies

Human

(Adult

Female)

Kesmodel et al. (2012)

LOAEL is <1

drink/week for

spontaneous abortion

Bolus dose of 12 g ethanol (one

drink)

18.1 34

Polygenis et al. (1998)

NOAEL of 0-2

drinks/week

Bolus dose of 28 g ethanol (two

standard drinks at one time)

53.0 151

Flak et al. (2014)

meta-analysis

41 g/week (assume 1x bolus for

modeling)

83.4 308

Toxicity

Studies

Mouse

(Pregnant

Female)

Blakley and Scott

(1984) NOAEL of 2

g/kg for fetal deaths

and malformations

IP dose of 2 g/kg (2000 mg/kg) to

pregnant mouse on GD 10

22 310

Table SA7. PBPK simulations for comparative risk evaluations in human (adult female)

Scenario Name Assumptions

Per Single Event

(1x per day)

Repeated Exposure

(2x per day)

Repeated Exposure

(3x per day)

Peak

(mg/dL)

AUC24

(mg/dL*hr)

Peak

(mg/dL)

AUC24

(mg/dL*hr)

Peak

(mg/dL)

AUC24

(mg/dL*hr)

Alcoholic beverage

consumption

Bolus dose of 14 g

ethanol (one standard

drink)

22.2 44 22.2 88 22.2 132

Non-alcoholic

beverage

Consumption

Bolus dose of 1.4 g

ethanol (one 12 oz.

non-alcoholic beer,

0.5% v/v ethanol

content)

1.2 1.8 1.20 3.6 1.2 5.3

Orange juice

consumption

Bolus dose of 0.14 g

ethanol (one 8 oz.

glass of orange juice

with 0.6 g/L ethanol

content)

0.10 0.16 0.10 0.3 0.10 0.48

Flavored water Bolus dose of 0.62 g 0.47 0.73 0.47 1.5 0.47 2.2

consumption

ethanol (one 12 oz.

flavored water, 0.22%

v/v ethanol content)

Occupational

(OSHA PEL/NIOSH

REL/ACGIH

TLV/CAL OSHA

PEL)

1,000 ppm (1900

mg/m3) 8-hour TWA0.89 7.97

7. Appendix S1.

!Note – the model is essentially as developed and described by Martin et al (2014). Any changes are !

noted with comments (text following $ with the initials TSP)

PROGRAM: Human pregnancy model

INITIAL

! Human Pulmonary Ventilation Rate

CONSTANT QPC = 24.75

! Human Blood Flows (fraction of cardiac output, m-file has values)

CONSTANT QCC = 16.5 ! Cardiac output

CONSTANT QBrnC = 0.12 ! Brain

CONSTANT QFatC = 0.05 ! Fat

CONSTANT QLivC = 0.25 ! Liver

CONSTANT QMamC = 0.027 ! Mammary tissue

CONSTANT QRapC = 0.39 ! Rapidly perfused

CONSTANT QSkC = 0.058 ! Skin - tsp 12/14

!CONSTANT QSlwC = 0.163 ! Slowly perfused - calculated below - tsp 12/14

! Permeability-Area Product (L/hr)

CONSTANT PAFC = 0.1 ! Diffusion on fetal side of placenta

!Gentry et al had PAFC=0.01 not sure where this paramter comes from or

!Correct value

! Human Tissue Volumes (fraction of body weight, m-file has values)

CONSTANT BWInit = 62.5! ! Pre-pregnancy body weight (kg)

CONSTANT VBrnC = 0.02 ! Brain

CONSTANT VFatC = 0.213 ! Fat

CONSTANT VLivC = 0.0257 ! Liver

CONSTANT VMamC = 0.0062 ! Mammary tissue

CONSTANT VRapC = 0.09 ! Rapidly perfused

!CONSTANT VSlwC = 0.82 ! Slowly perfused - replaced with equation below and added vskc -

tsp 12/14

CONSTANT DS = 0.15 ! Dead space volume (fraction)

CONSTANT VSKC=0.19

! Human Pregnancy Parameters

CONSTANT NumFet = 1! ! Number of fetuses

CONSTANT PupBW = 3600000.0! ! Birth weight

! Molecular Weights

CONSTANT MW = 46.07 ! Ethanol

! Human Ethanol Tissue/Blood Partition Coefficients

CONSTANT PB = 1265 ! Blood/air

CONSTANT PMuc = 2140 ! Mucous/air

CONSTANT PBrn = 0.87 ! Brain

CONSTANT PFat = 0.11 ! Fat

CONSTANT PLiv = 0.81 ! Liver

CONSTANT PMam = 0.8 ! Mammary tissue

CONSTANT PPla = 0.8 ! Placenta

CONSTANT PRap = 0.81 ! Rapidly perfused tissue

CONSTANT PSlw = 0.8 ! Slowly perfused tissue

CONSTANT PSKL = 0.8 !SKIN= SLOW

! Human Ethanol Metabolism Parameters

CONSTANT VMaxlC = 359.5 ! Maximum reaction rate liver

CONSTANT KMl = 82.1 ! Michaelis-Menten liver (mg/L)

CONSTANT VMaxgC = 43.3 ! Maximum reaction rate gut

CONSTANT KMg = 96286 ! Michaelis-Menten gut (mg/L)

CONSTANT VMAXGLUCC=0.006 !MG/hR TO GLUC - 0.006 IS FOR TCE

CONSTANT KMGLUC=0.06 !0.06 IS FOR TCE

CONSTANT KELG=1 !CLEARANCE OF GLUTATHION CONJUGATE

! Dosing Parameters

CONSTANT IVDose = 1000! ! IV dose (mg/kg)

CONSTANT PDose = 0! ! Oral dose (mg/kg)

CONSTANT DaysWk = 7.0 ! Number of exposure days per week

CONSTANT CONC = 0. ! Chamber concentration (ppm)

CONSTANT TChng = 0.083! ! End of daily inhalation exposure (hrs)

CONSTANT DCHNG = 0.00 !DERMAL

CONSTANT Tmax = 0.083! ! Turn off dosing at specified time, continue sim (hrs)

CONSTANT Tinf = 0.083! ! Length of dosing (hrs)

CONSTANT IDays = 5.5 ! No. days exposure each week (Days)

Day = 0.5 ! Initialize Day Inhalation Exposure

constant vslc = 0.02! ! Volume of stomach lumen (l)

constant kac = 5.4!. ! First order oral uptake rate (1/hr)

constant kaip=1

constant pee=0.75 !ml/hr/kg -Heffernan et al., 2012

! Human Dermal Exposure Parameters

CONSTANT KP = 0.0016 ! Permeability constant (Kp) (cm/hr) - tsp 12/14

!FOR PARENT MODEL, SKIN COMPARTMENT IS ONLY DEFINED AS DOSED SKIN - tsp 12/14

CONSTANT SAlC = 0.01 !SURFACE AREA EXPOSED to liquid, SQ.CM

CONSTANTHT=170.0 !height (or length) of reference man

TSA = 71.81*(BWinit**0.425)*(HT**0.725) !for humans, DuBois and DuBois, 1916, as reported in

Reference Man

SAl = SAlC*TSA ! SURFACE AREA EXPOSED , SQ.CM

VSKlC = VSKC*SAlC

QSKlC = QSKC*SAlC

CONSTANT KPL=7.1E-3 !kUPCSEWSKA-DOBECKA ET AL., 2010: CALCULATED (cm/hr) -- -in vitro

Gajjar and Kastings (2014) ~0.004 cm/hr calculated from flux

CONSTANT DLAY=0.25 !APPROX DELAY BEFORE DERMAL ABSORPTION - APPROXIMATES

LOADING OF DERMIS

CONSTANT kevap=7.87E-02 !cm/h - from Kasting's model

!tsp - new mass-balance volumens

VSlwC = 0.91 - ( VFatC + VLivC + VMamC + VRapC + VSKlC)

! NOTE: 0.91 IS APPROX WHOLE BODY LESS BONE

VSLwC5=0.91 - (VFatC + VLivC + VRapC+VSKL) !

QSlwC = 1.0 - (QFatC + QLivC + QMamC + QRapC + QSKlC)

QSlwC5 = 1.0 - (QFatC + QLivC + QRapC)!

!Mucous Definition

CONSTANT kUrtC = 12.0 ! URT uptake (L/hr)

CONSTANT VMucC = 0.0001 ! Mucous

CONSTANT VAlvC = 0.007 ! Alveolar blood

! Simulation Control Parameters

CONSTANT TSTART = 0! ! Time first dose is given (hrs)

CONSTANT TStop = 0.083! ! Run simulation for hrs

CONSTANT DStop = 0.083! ! Stop Dosing

CONSTANT GDSTART =119! ! Gestation Day at start of simulation

! Conversion Factors

CONSTANT mgkg = 1.0e6 ! Conversion factor from mg to kg

! Pulmonary Ventilation Rate (L/hr)

QP = QPC * (BWInit**0.75) ! Pulmonary ventilation

QAlv = 0.67 * QP ! Alveolar ventilation

! Human Blood Flows (L/hr)

QCInit = QCC * (BWInit**0.75) ! Cardiac output

QBrn = QBrnC * QCInit ! Brain

QFatI = QFatC * QCInit ! Fat

QLiv = QLivC * QCInit ! Liver

QMamI = QMamC * QCInit ! Mammary

QRap = QRapC * QCInit ! Rapidly perfused tissues

QSlw = QSlwC * QCInit ! Slowly perfused tissues

QSkl = QSKlC * QCInit !exposed dermal compartment - tsp 12/14

! Human Tissue Volumes (L)

VSl = VSLC * BWInit ! Stomach lumen

VAlv = VAlvC * BWInit ! Alveolar

VBrn = VBrnC * BWInit ! Brain

VFatI = VFatC * BWInit ! Fat

VMamI = VMamC * BWInit! ! Mammary

VMuc = VMucC * BWInit ! Respiratory mucous

VSlw = VSlwC * BWInit !- VFatI - VmamI ! Slowly perfused tissues

VLiv = VLivC * BWINIT ! Liver

VRap = VRapC * BWInit !- VLiv - VBrn ! Rapidly perfused tissues

VSKl = VSKlC * BWinit !exposed dermal compartment - tsp 12/14

! Initialize Starting Values

BW = BWInit ! Initial bodyweight

IVx = 0.0 ! Intravenous

MR = 0.0 ! Oral

ODX = 0.0 ! Oral dose

DDNX=0.0 !DERMAL

DDN=0.0

!IPx = 0. !

!IPMR=0!

CSTL = 0.0

DayExp = 1.0

CI = 0.0

TotDose = 0.0

CFet = 0.0

CFet1 = 0.0

CPla = 0.0

CPla1 = 0.0

PerEnd = 0.0

PerMix = 0.0

VPLA = 0.0

Vfet = 0.0

QPla = 0.0

QC = 0.0

QDEC = 0.0

QCAP = 0.0

INHON = 0.0

CONSTANT P1=3.0

!CONSTANT P2=24

CONSTANT P3=3.0

CONSTANT S3=24

CONSTANT ON3=1.0

CONSTANT TIME1=0.0

SCHEDULE DOSE1 .AT. TIME1

DZONE = 1.0 ! Start with exposure on

p2=P1+DLAY

schedule offd.at.p2

schedule OND2.at.24.0

if (ON3) schedule OND3.at.s3

END ! End of Initial

DYNAMIC

ALGORITHM IALG = 2

NSTEPS NSTP = 10

MAXTERVAL MAXT = 1.0e6

MINTERVAL MINT = 1.0e-6

CINTERVAL CINT = 0.01

discrete OND2

DZONE=1.0

SCHEDULE OND2.AT.(T+24.0)

SCHEDULE OFFD.AT.(T+P2)

END

discrete OND3

DZONE=1.0

SCHEDULE OND3.AT.(T+24.0)

SCHEDULE OFFD.AT.(T+P3)

END

!EXPOSURE CONTROL

DISCRETE OFFD

DZONE=0.0 !TURN OFF DERMAL

END

END ! End of Dynamic

DERIVATIVE

!...........................................................

!.....................Dosing Control........................

!...........................................................

!IV Dosing

DISCRETE Doson

SORT

INTERVAL C2 = 24.0

IF ((ivdose.gt.0.0)) ivx = (ivdose*bw)

!Oral Dosing

IF ((PDOSE.GT.0.0).AND.(T.GE.TSTART).AND.(T.LE.DSTOP)) THEN

!IF ((PDOSE.GT.0.0).AND.(T.GE.TSTART).AND.(T.LE.DSTOP).AND.(T.LE.TMAX).AND.

(Day.LE.IDays)) THEN

ODx = PDOSE * BW

!ODing=1

ENDIF

SCHEDULE ODoseOff .AT. T+tinf

DISCRETE Doson

SORT

INTERVAL D2 = 24.0

IF ((concl.gt.0.0)) ddnx = (concl*vliq)

!IP dosing

! IF ((IPDOSE.GT.0.0).AND.(T.GE.TSTART).AND.(T.LE.DSTOP)) THEN

! IPx = IPDOSE * BW

! ENDIF

! SCHEDULE IPOff .AT. T+tinf

END

END

!-----------------------------------------------------------

!DERMAL

CONSTANT CONCL = 1.0E-99 !CONC OF NMP IN LIQUID, MG/L

CONSTANT VLIQ = 1.0E-99 !INITIAL VOLUME APPLIED, L

CONSTANT DENSITY=1.03

CONSTANT FAD=1.0 !USE TO APPROXIMATE LOSS IF NECESSARY

DISCRETE ODoseOff

ODx = 0.

IVx = 0.

ddnx=0

!ODing=1

end

!Discrete IPOff !

!IPx = 0. !

!END

!Inhalation Exposure

DISCRETE DoseOn

SORT

INTERVAL DoseInt = 24.0 ! Dosing interval (hrs)

IF ((CONC.GT.0.0).AND.(T.LE.TMAX).AND.(Day.LE.IDays)) THEN

Inhon = 1.0

ENDIF

SCHEDULE DoseOff .AT. T + TChng +DLAY

Day = Day + 1.0

IF (Day.GT.7.0) THEN

Day = 0.5

ENDIF

END

DISCRETE DoseOff

Inhon = 0.0

! dzone = 0.0

END

IV = (IVx/tinf)!*KP ! IV dose !

OD = (ODx /tinf)!*ODing ! PDOSE*BW ! rate of dosing mg/hr

!DDN=DELAY(DDNX,0,DLAY,2,10)*FAD

DDN=DDNX*FAD

!ip = ipx /tinf !

CI = (conc*Inhon*MW/24450)

Hours = T

Minutes = T * 60.0

Days = T / 24.0

GD = GDStart + Days

gesthours=gd*24!

!Human volume of fat tissue

!GestHours Eqn

VFAT = bwinit *(Vfatc +(0.09*exp(-12.90995862*exp(-0.000797*gesthours)))) ! Human

!Human volume of fetus

VFet = 3.50 * (exp(-16.081*exp(-5.67E-4*gesthours))+exp(-140.178*exp(-7.01E-4*gesthours))) ! Human

!human volume of mammary tissues

VMam = bwinit*(Vmamc + (0.0065 * exp(-7.444868477*exp(-0.000678*gesthours)))) ! Human

! Human volume placenta (L/hr)

!GestHours Eqn instead of only hours

VPla = 0.85 * exp(-9.434 * exp(-5.23E-4 * gesthours)) ! Human

! Body weight (kg)

BW = ((VRap + VSlw + Vliv + VFat + VMam + VBrn+VSKL)/0.91) + VPla + VFet

! Metabolism Parameters

VMaxl = VMaxlC * (BW**0.75) ! Vmax Liver

VMaxG = VMaxGC * (BW**0.75) ! Vmax Gastric

KA = KAC/BW**0.25 ! Gastric uptake

VMAXGLUC=VMAXGLUCC* (BW**0.75) ! Vmax Liver - CONJUGATION, ~1% OF

METABOLISM

! Alveolar ventilation (L/hr)

kUrt = (min(kUrtC, QPC)) * (BW**0.75) ! Wash-in/wash-out for upper respiratory tract

! Blood flows (L/hr)

QFat = QFatI * (VFat / VFatI) ! Blood flow to fat tissue

QMam = QMamI * (VMam / VMamI) ! Blood flow to mammary tissue

! Human Blood flow to placenta

QPla = 58.5 * VPla ! Human

! Cardiac output (L/hr)

QC = QLiv + QBrn + QFat + QMam + QSlw + QRap + QPla

! Permeability-area product

PAF = PAFC * (VFet**0.75)

! ------------------- GESTATION MODEL --------------------------

! Amount in Mucous

RAMucI = kUrt * (CI - (CMuc/PMuc)) ! Equation for amount in respiratory mucous from inhale

RAMucX = kUrt * ((CMuc/PMuc) - CAlv) ! Equation for amount in respiratory mucous from exhale

RAMuc = RAMucI - RAMucX ! Difference between amount in respiratory mucous from inhale and

exhale

AMuc = INTEG(RAMuc, 0.0) ! Amount in respiratory mucous (mg)

CMuc = AMuc / VMuc ! Concentration in respiratory mucous (mg/L)

! Amount Exhaled (mg)

RAExh = (QAlv * CAlv) + RAMucX ! Equation for amount in exhaled breath

AExh = INTEG(RAExh, 0.0) ! Amount in exhaled breath

! Concentration in End-Exhaled Air (mg/L)

CEnd = RAExh / QAlv ! Concentration in end-exhaled breath

CEndPPM = CEnd * (24450.0 / MW) ! Conversion to ppm, for exhaled breath data fit

IF (Conc.GT.0.0) THEN

PerEnd = (CEnd / ((Conc*MW)/24450.0)) * 100.0

ENDIF

! Concentration in Mixed Exhaled Air (mg/L)

CMix = ((1-DS)*CEnd) + (DS*CI) ! Concentration in mixed-exhaled breath

CMixPPM = CMix * (24450.0 / MW) ! Conversion to ppm, for exhaled breath data fit

IF (Conc.GT.0.0) THEN

PerMix = (CMix / ((Conc*MW)/24450.0)) * 100.0

ENDIF

rain = (ci*qp) ! Equation for amount inhaled

ain = integ(rain,0.) ! Amount inhaled (mg)

! Amount in Arterial Blood (mg)

RABld = (QAlv*CI) - RAMucI - (QAlv*CAlv) + (QC*(CVen-CArt)) ! Equation for concentration in arterial

blood

ABld = INTEG(RABld, 0.0) ! Amount in arterial blood

CArt = ABld / VAlv ! Concentration in arterial blood (mg/L)

CAlv = CArt / PB ! Concentration in alveolar blood (mg/L)

CAlvPPM = CAlv * (24450.0 / MW) ! Concentration in alveolar blood (ppm)

AUCCBld = INTEG(CArt, 0.0) ! Area under the curve of arterial blood

!ORAL DOSE - GASTRIC ADH

dstl = OD - ka*mr - rmst

mr = INTEG(dstl,0.0)

rao = ka*mr ! Equation for amount absorbed from stomach oral dose

absrb = INTEG(rao,0.) ! Amount absorbed from stomach oral dose

cstl = mr/vsl ! Concentration in stomach (mg/L)

rmst = (VMAXG*cstl)/(KMG+cstl) ! Equation for amount metabolized in stomach

ama = INTEG(rmst,0.) ! Amount metabolized in stomach

! Concentration in Mixed Venous Blood (mg/L)

CVen = (QBrn*CVBrn + QLiv*CVLiv + QMam*CVMam &

+ QPla*CVPla + QRap*CVRap + QSlw*CVSlw &

+ QFat*CVFat + QSKl*CVSKL+ IV) / QC ! Equation for concentration in venous blood

(mg/L)

cvdl = cven/10 ! Concentration in blood as mg/dL

cvm = cven/mw ! Concentration in blood as mM

AUCVen = INTEG(Cven, 0.0)

! Area under the curve of venous blood (mg/L)

!ASKl = AMOUNT NMP IN liquid-exposed SKIN TISSUES (MG) TSP 12/14

! Liquid exposure when czone = 1, otherwise czone = 0. CI = air concentration

!czone = pulse(0.0,fullweek,hrsweek)*DZONE !

!for a 5 day/wk exposure, use fullweek=7*24, hrsweek=5*24 (Dayswk=5)

! for a single day, fullweek=1e16, hrsweek=24 (Dayswk=1)

RADL = (KPL*(SAL/100))*(CSURF - (CSKL/PSKL))*DZONE!*DZONEDAY

! Net rate of delivery to "L" skin from liquid, when liquid is there

ADLL = INTEG(RADL, 0.0)

ASURF=INTEG(-RADL,DDN) ! Aount in liquid. DDN is the initial amount.

!CSURF=DELAY(DDN/VLIQ,0,DLAY,10,999)

CSURF = DDN/VLIQ

RASKL = QSKL*(CArt - CvSKL) + RADL ! Rate of change in "L" skin compartment

ASKL = INTEG(RASKL, 0.0) ! Amount in "L" skin

CSKL = ASKL/VSKL ! Concentration in "L" skin

CvSKL = CSKL/PSKL ! Concentration in venous blood exiting "L" skin

! Amount in Brain (mg)

RABrn = QBrn * (CArt - CVBrn) ! Equation for amount in brain compartment

ABrn = INTEG(RABrn, 0.0) ! Amount in brain

CBrn = ABrn / VBrn ! Concentration in brain

CVBrn = CBrn / PBrn ! Concentration in brain blood

cbrndg=cbrn/10

! Concentration in brain in mg/dL

! Amount in Fat (mg)

RAFat = QFat * (CArt - CVFat) ! Equation for amount in fat compartment

AFat = INTEG(RAFat, 0.0) ! Amount in fat

CFat = AFat / VFat ! Concentration in fat

CVFat = CFat / PFat ! Concentration in fat blood

! Amount in Liver (mg)

RALiv = QLiv * (CArt - CVLiv) + RAO - RAM - RAGLUC !+ IPRA ! Equation for amount in liver

compartment

ALiv = INTEG(RALiv, 0.0) ! Amount in liver tissue

CLiv = ALiv / VLiv ! Concentration in liver

CVLiv = CLiv / PLiv ! Concentration in liver blood

clivdg=cliv/10 ! Concentration in liver in mg/dL

! Amount Metabolised in Liver -- Saturable (mg)

RAM = (VMaxl * CVLiv) / (KMl + CVLiv) ! Equation for saturable metabolism in liver

AM = INTEG(RAM, 0.0) ! Amount metabolized in liver

RAGLUC = (VMaxGLUC * CVLiv) / (KMGLUC + CVLiv) ! Equation for saturable metabolism in liver

AMGLUC = (INTEG(RAGLUC, 0.0))*222.2/46.1! Amount metabolized in liver - ASSUME ALL CLEARED

(mw etoh=46.1, ethyl GLUC=222.2)

AMGLUCMAS = INTEG(RAGLUC, 0.0) !USED FOR MASSBALANCE

RAMam = QMam * (CArt - CVMam) !! ! Equation for amount in mammary compartment

AMam = INTEG(RAMam, 0.0) ! Amount in mammary tissue

CMam = AMam / VMam ! Concentration in mammary

CVMam = CMam / PMam ! Concentration in mammary blood

cmamdl=cmam/10

! Amount in Rapidly Perfused Tissue (mg)

RARap = QRap * (CArt - CVRap) ! Equation for amount in RPT compartment

ARap = INTEG(RARap, 0.0) ! Amount in RPT

CRap = ARap / VRap ! Concentration in RPT

CVRap = CRap / PRap ! Concentration in RPT blood

! Amount in Slowly Perfused Tissue (mg)

RASlw = QSlw * (CArt - CVSlw) ! Equation for amount in SPT compartment

ASlw = INTEG(RASlw, 0.0) ! Amount in SPT

CSlw = ASlw / VSlw ! Concentration in SPT

CVSlw = CSlw / PSlw ! Concentration in SPT blood

! Amount in Fetuses (mg)

RAFet = PAF * (CPla - CFet) ! Equation for amount in embryo/fetus compartment

AFet = INTEG(RAFet, 0.0) ! ! Amount in embryo/fetus

CFet = AFet / (VFet + 1.0E-23) ! Concentration in fetus

CFetm = CFet/MW ! Millimolar concentration in placenta

AUCCFet = INTEG(CFet, 0.0) ! Area under the curve for embryo/fetus

compartment

cfetdg=cfet/10 ! Concentration in embryo/fetus in mg/dL

!Amount in Placenta (mg)

RAPla = (QPla * (CArt - CVPla)) + (PAF * (CFet - CPla)) ! Equation for amount in placenta

APla = INTEG(RAPla, 0.0) ! Amount in placenta

CPla = APla / (VPla + 1.0E-23) ! Concentration in placenta

CVPla = CPla / PPla ! Concentration in placental blood

! ----------------- MASS BALANCE ------------------------------

ODose = INTEG(OD,0.0)!

IVD = INTEG(IV,0.0)!

INHD = INTEG((QALV*CI),0.0)!

TDose = INHD + IVD + ODose + ADLL ! !

TMASS = MR + AMuc + ABld + ABrn + ALiv + AMam + APla &

+ ARap + ASlw + AFat + AExh + AM + AMA+ AFet+ASKL+AMGLUCMAS

TMASS_d_f= MR + AMuc + ABld + ABrn + ALiv + AMam + APla &

+ ARap + ASlw + AFat + AExh + AM + AMA+ASKL+AMGLUCMAS !

MassBal = TDose/(TMASS+1E-19) !

QBAL = QC/(QBrn + QLiv + QMam + QPla + QRap + QSlw + QFat + QSKL+1E-19)

BWBAL = BW /(((VMam + VFat + VLiv + VRap + VSlw + VBrn+VSKL)/0.91) + VPla + VFet)

TERMT(T.GT.TStop, 'Simulation Finished')

END

END

! End of Derivative

TERMINAL

END ! End of Terminal

END ! End of Program