# Predicting Maternal and Infant Tetrahydrocannabinol Exposure in Lactating Cannabis Users: A Physiologically Based Pharmacokinetic Modeling Approach

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## Abstract

**:**

_{max}) and area under the concentration–time curve (AUC

_{(0–24 h)}) for breastmilk were higher than in plasma (C

_{max}: 155 vs. 69.9 ng/mL; AUC

_{(0–24 h)}: 924.9 vs. 273.4 ng·hr/mL) with a milk-to-plasma AUC ratio of 3.3. The predicted relative infant dose ranged from 0.34% to 0.88% for infants consuming THC-containing breastmilk between birth and 12 months. However, the mother-to-infant plasma AUC

_{(0–24 h)}ratio increased up to three-fold (3.4–3.6) with increased maternal cannabis smoking up to six times. Our study demonstrated the successful development and application of a lactation and infant PBPK model for exploring THC exposure in infants, and the results can potentially inform breastfeeding recommendations.

## 1. Introduction

## 2. Materials and Methods

#### 2.1. PBPK Model Development Workflow

#### 2.2. PBPK Model Development

#### 2.2.1. General Model Structure

#### 2.2.2. Base Model: Intravenous PBPK Model

#### 2.2.3. Base Model Expansion: Inhalation PBPK Model

_{2}, BB, and bb were assigned two filters each. However, AL was assigned a single filter because the airway is closed at the alveolar end (Figure 3a). The fraction of smoke particles deposited at each filter relied on the tidal airflow through each airway region, as well as the aerodynamic and thermodynamic properties of the particles. Within a particular filter, the transit of particles from prior filters contributed to the addition or depletion of particles in that filter, which affected the overall particles available for dissolution in the epithelial fluid. The dissolved particles were further affected by mucociliary clearance, which facilitated the movement of particles to and away from each airway region. All these processes collectively determined the amount of particles that eventually permeated the lung epithelial cells. A comprehensive depiction of this mechanism is shown in Figure 3b.

#### 2.2.4. Base Model Expansion: Lactation PBPK Model

#### 2.2.5. Base Model Reduction: Infant Oral PBPK Model

#### 2.2.6. Model Training, Verification, and Simulation

_{max}. An acceptance criterion of AAFE between 1 and 2 was set to establish model validation [80,81].

^{®}(version 2.3.2, Pumas-AI, Inc., Centreville, VA, USA).

#### 2.2.7. Sensitivity Analysis

_{(0–t)}).

## 3. Results

#### 3.1. Observed Data for PBPK Model Development

#### 3.2. PBPK Model Training and Verification

#### 3.2.1. Intravenous PBPK Model

#### 3.2.2. Inhalation PBPK Model

_{2}, BB, bb, and AL airway regions were 0.76%, 1.4%, 37%, and 24%, respectively. Although there were no prior in vivo THC deposition studies for comparison, these values were similar to those reported previously for nicotine [52].

#### 3.2.3. Lactation PBPK Model

#### 3.2.4. Infant Oral PBPK Model

^{®}software (version 2.3.2, Pumas-AI, Inc., Centreville, VA, USA). By reproducing the results from the Klumpers et al. study, we successfully established an adult oral pharmacokinetic model for THC.

#### 3.2.5. Simulations

#### 3.2.6. Sensitivity Analysis

## 4. Discussion

_{(0–24 h)}of 0.22, 0.18, 0.18, and 0.10%, respectively, for a mother who smoked cannabis once daily and exclusively breastfed a one-month-old infant. Notably, this value increased with an increase in daily cannabis use, showing up to a threefold rise when the daily use increased to six joints. Furthermore, we simulated relative infant doses of 0.59, 0.71, 0.60, and 0.39% for infants up to 1 month, 3 months, 6 months, and 12 months old, respectively. While some studies have reported maternal weight-adjusted relative infant doses of 0.8–8.7%, our model accounted for the dynamics of milk intake per feed, resulting in lower infant exposure to THC through lactation. In our worst-case scenario of maternal cannabis use six times daily during lactation, the maximum infant plasma concentration ranged between 0.084 and 0.167 ng/mL for infants between one month and twelve months, with one-month-old infants showing higher levels. These concentrations are orders of magnitude lower than maternal plasma levels, and the clinical implications of this finding are unclear. Additional data would be needed to interpret THC levels in infants.

## 5. Conclusions

## Supplementary Materials

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

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**Figure 1.**Workflow of model development for the maternal lactation and infant PBPK model. IV, intravenous; PBPK, physiologically based pharmacokinetic model.

**Figure 2.**Schematics of the maternal and infant PBPK model structure, highlighting modes of drug input, distribution, and elimination. ET

_{2}, extrathoracic (excluding the nose); BB, bronchial; bb, bronchiolar; and AL, alveolar region; CL

_{H}, hepatic clearance; Q

_{bt}, blood flow to the breast; CL

_{btmk}, drug clearance from the breast into milk; CL

_{mkbt}, drug clearance from milk into the breast.

**Figure 3.**Schematics of particle deposition following (

**a**) inhalation and exhalation and (

**b**) absorption of deposited particles through the bronchial region. fDE, fraction deposited; ${\mathrm{k}}_{{\mathrm{t}\mathrm{r}}_{\mathrm{B}\mathrm{B}}}$, ${\mathrm{k}}_{{\mathrm{t}\mathrm{r}}_{\mathrm{b}\mathrm{b}}}$, transit rate constant at bronchial and bronchiolar regions (1/h), respectively; ${\mathrm{k}}_{{\mathrm{d}}_{\mathrm{B}\mathrm{B}}}$, dissolution rate constant at bronchial region (1/h); ${\mathrm{k}}_{{\mathrm{m}\mathrm{c}\mathrm{c}}_{\mathrm{B}\mathrm{B}}}$, ${\mathrm{k}}_{{\mathrm{m}\mathrm{c}\mathrm{c}}_{\mathrm{B}\mathrm{B}}}$, mucociliary transit rate constant at bronchial and bronchiolar regions (1/h), respectively; ${\mathrm{P}\mathrm{S}}_{\mathrm{B}\mathrm{B}}$, permeability surface area product of bronchial epithelium (L/h); ${\mathrm{Q}}_{\mathrm{l}\mathrm{u}}$, blood flow to the lungs.

**Figure 4.**Plasma concentration profiles following a short intravenous infusion. The open blue circle represents the observed data. The solid line depicts the median PBPK predicted concentrations, while the shaded area (5th to 95th percentile) indicates the 90% prediction interval. The purple and blue profiles display the overlay of PBPK simulated values with the observed values in the training and verification datasets, respectively [85,86,87,88,89,90,91].

**Figure 5.**Median (interquartile range) predicted/observed ratios for AUC and Cmax following intravenous administration of THC. The purple median (IQR) corresponds to the results from the training datasets, while the blue median (IQR) represents the results from the verification datasets. Each median (IQR) on the plot is accompanied by the absolute average fold errors (AAFE), which provide an overall measure of the deviation between simulated and observed values. The acceptance criterion for the ratio is set between 0.5 and 1, while the criterion for the AAFE is set between 1 and 2. Multiple datasets were included from certain studies where both chronic (a) and casual (b) cannabis use scenarios were investigated within the same study [85,86,87,88,89,90,91].

**Figure 6.**(

**a**) Plasma concentration profiles following THC inhalation after smoking cannabis. The open blue circle represents the observed data. The solid line depicts the median PBPK predicted concentrations, while the shaded area (5th to 95th percentile) indicates the 90% prediction interval. The purple and blue profiles display the overlay of PBPK simulated values with the observed values in the training and verification datasets, respectively. (

**b**) Plasma concentration profiles following THC inhalation after smoking cannabis. The open blue circle represents the observed data. The solid line depicts the median PBPK predicted concentrations, while the shaded area (5th to 95th percentile) indicates the 90% prediction interval. The blue profile displays the overlay of PBPK simulated values with the observed values in the verification datasets [85,86,92,93,94,95,96,97].

**Figure 7.**Median (interquartile range) predicted/observed ratios for AUC following inhalation of cannabis smoke. The purple median (IQR) corresponds to the results from the training datasets, while the blue median (IQR) represents the results from the verification datasets. Each median (IQR) on the plot is accompanied by the absolute average fold errors (AAFE). The acceptance criterion for the ratio is set between 0.5 and 1, while the criterion for the AAFE is set between 1 and 2. Multiple datasets were included from certain studies that examined a range of scenarios, including chronic (a) and casual (b) cannabis use, as well as variations in THC content such as low (l), medium (m), and high (h) THC content in cannabis joints within the same study [85,86,92,93,94,95,96,97].

**Figure 8.**Breastmilk concentration profiles following THC inhalation after smoking cannabis. The open blue circle represents the observed data. The solid line depicts the median PBPK predicted concentrations, while the shaded area (5th to 95th percentile) indicates the 90% prediction interval. Eight lactating mothers participated in the Baker et al. study, and their profile is shown on the graph. However, in the Bertrand et al. study, 50 mothers who reported recent marijuana use contributed one breastmilk sample at different times [13,98].

**Figure 9.**The predicted median (IQR) plasma (Purple) and breastmilk (blue) concentration of mothers who smoked one, two, three, four, five, or six times per day. Multiple smoking sessions were spaced evenly within a 24 h period.

**Figure 10.**Simulated plasma concentration profile from the infant PBPK model and scaled Klumpers et al. [108] population pharmacokinetic model.

**Figure 11.**Simulated plasma concentration profile for infants up to one year of age. It was assumed baby feeds every three hours, and the breast milk concentration at the time of feeding depends on the number of times the lactating mother smoked. One to six times smoking frequency per day was tested and represented by different colors, as shown in the legend.

**Figure 12.**Sensitivity analysis of exposure metrics to variations in fixed model input parameters. The viscosity and hygroscopicity of THC smoke were assessed in relation to the fraction deposited, while solubility was evaluated against the plasma area under the curve (AUC). Additionally, the breast partition coefficient was examined in correlation with breast milk AUC.

Organ | Weight (g) ^{a} | ρ | Q ^{b} | fVwt | fVnl | fVph | fVew | fViw | Reference |
---|---|---|---|---|---|---|---|---|---|

LBM | $0.252\cdot \mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}+0.473\cdot \mathrm{H}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}-48.3$ | [25] | |||||||

Adipose | $17.4+0.65\cdot \mathrm{A}\mathrm{g}\mathrm{e}-0.01\cdot {\mathrm{A}\mathrm{g}\mathrm{e}}^{2}+9\times {10}^{-5}\cdot {\mathrm{A}\mathrm{g}\mathrm{e}}^{3}$ | 0.9196 | 0.085 | 0.286 | 0.609 | 0.005 | 0.135 | 0.017 | [26,27,28,29,30,31] |

Bone | $0.21\cdot \mathrm{L}\mathrm{B}\mathrm{M}$ | 1.176 | 0.05 | 0.45 | 0.074 | 0.0011 | 0.1 | 0.346 | [26,31,32] |

Brain | $653+95.4\cdot \mathrm{A}\mathrm{g}\mathrm{e}-4.32\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{2}+0.0729\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{3}-0.000413\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{4}$ | 1.04 | 0.12 | 0.78 | 0.051 | 0.0565 | 0.162 | 0.62 | [26,31] |

Gut | 1100 | 1.045 | 0.17 | 0.76 | 0.0487 | 0.0163 | 0.282 | 0.475 | [26,31] |

Muscle | $0.29\cdot \mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}$ | 1.06 | 0.12 | 0.71 | 0.022 | 0.0072 | 0.118 | 0.63 | [26,27,31] |

Heart | $25.39+15.70\cdot \mathrm{A}\mathrm{g}\mathrm{e}-0.3603\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{2}+0.004\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{3}-1.75\times {10}^{-5}\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{4}$ | 1.055 | 0.05 | 0.78 | 0.0115 | 0.0166 | 0.32 | 0.456 | [26,31] |

Spleen | $8.99+10.13\cdot \mathrm{A}\mathrm{g}\mathrm{e}-0.24\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{2}+0.0018\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{3}-2.95\times {10}^{-6}\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{4}$ | 1.06 | 0.03 | 0.79 | 0.0201 | 0.0198 | 0.207 | 0.579 | [26,31] |

Kidney | $20.4+18.7\cdot \mathrm{A}\mathrm{g}\mathrm{e}-0.511\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{2}+0.0054\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{3}-1.88\times {10}^{-5}\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{4}$ | 1.035 | 0.17 | 0.76 | 0.0207 | 0.0162 | 0.273 | 0.483 | [26,31] |

Lungs | $115+36.8\cdot \mathrm{A}\mathrm{g}\mathrm{e}-0.4\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{2}$ | 1.05 | 1.0 | 0.78 | 0.003 | 0.009 | 0.336 | 0.446 | [26,31] |

Liver | $145+104\cdot \mathrm{A}\mathrm{g}\mathrm{e}-3.2\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{2}+0.043\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{3}-0.0002134\cdot \mathrm{A}\mathrm{g}{\mathrm{e}}^{4}$ | 1.054 | 0.27 | 0.73 | 0.0348 | 0.0252 | 0.161 | 0.573 | [26,31] |

Rest | $\mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}-\sum {\mathrm{W}}_{\mathrm{t}\mathrm{i}\mathrm{s}\mathrm{s}\mathrm{u}\mathrm{e}\mathrm{s}}$ | 0.065 | 0.70 ^{ca} | 0.02 ^{c} | 0.01 ^{c} | 0.652 | 1.581 | [31] | |

Blood | $0.36\cdot \mathrm{H}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}{\mathrm{t}}^{3}+0.03\cdot \mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}+0.1833$ | [33,34] | |||||||

Plasma | $0.6\cdot {\mathrm{W}}_{\mathrm{B}\mathrm{l}\mathrm{o}\mathrm{o}\mathrm{d}}$ | 0.95 | 0.0032 | 0.0021 | [34] | ||||

Venous | $0.7\cdot {\mathrm{W}}_{\mathrm{B}\mathrm{l}\mathrm{o}\mathrm{o}\mathrm{d}}$ | [35] | |||||||

Artery | ${\mathrm{W}}_{\mathrm{B}\mathrm{l}\mathrm{o}\mathrm{o}\mathrm{d}}-{\mathrm{W}}_{\mathrm{V}\mathrm{e}\mathrm{n}\mathrm{o}\mathrm{u}\mathrm{s}}$ |

^{a}Equations were either reported or generated from the digitized plot;

^{b}values were reported as fractions;

^{c}Values were assumed. ρ, specific gravity (g/cm

^{3}); Q, organ blood flow; fV, fractional volume; wt, nl, ph, ew, iw, water, neutral lipids, extracellular water, and intracellular water, respectively; ${\mathrm{W}}_{\mathrm{t}\mathrm{i}\mathrm{s}\mathrm{s}\mathrm{u}\mathrm{e}\mathrm{s}}$, ${\mathrm{W}}_{\mathrm{B}\mathrm{l}\mathrm{o}\mathrm{o}\mathrm{d}}$, ${\mathrm{W}}_{\mathrm{V}\mathrm{e}\mathrm{n}\mathrm{o}\mathrm{u}\mathrm{s}}$ weight of tissues, blood, and venous blood, respectively. The volume of each organ was calculated by multiplying the organ weight and specific gravity.

Parameter | Definition | Value | Reference |
---|---|---|---|

Dose (mg) | Standard joint weighing 0.32 g containing 14.14% THC | 45.2 | [37,38] |

MW (g) | Molecular weight (C_{21}H_{30}O_{2}) | 314.5 | [39] |

Log P | Octanol-water partition coefficient | 6.97 | [40] |

BP | Blood-to-plasma ratio | 0.667 | [41] |

pKa | Dissociation constant | 10.6 | [42] |

fu_{p} | Unbound fraction in plasma | 0.0022 | [43] |

fu_{mic} | Unbound fraction in liver microsomes | 0.04 | [44] |

Vmax_{CYP2C9} (pmol/min/mg) | CYP2C9 maximum reaction rate | 624 | [44] |

Km_{CYP2C9} (μmol/L) | CYP2C9 concentration at half maximum reaction rate | 0.07 | [44] |

Vmax_{CYP3A4} (pmol/min/mg) | CYP3A4 maximum reaction rate | 4905 | [44] |

Km_{CYP3A4} (μmol/L) | CYP3A4 concentration at half maximum reaction rate | 5.48 | [44] |

Vmax_{PGP,BR} (μmol/h) | PGP brain maximum reaction rate | 0.0123 | [45] |

Km_{PGP,BR} (μmol/L) | PGP brain concentration at half maximum reaction rate | 49.1 | [45] |

S_{THC} (mg/L) | THC Solubility | 2.8 | [39] |

PSA (Å^{2}) | THC Polar Surface Area | 29.5 | [39] |

HBD | THC Hydrogen Bond Donor | 1 | [39] |

d_{ae} (μm) | Aerodynamic diameter of THC smoke particle | 0.39 | [46] |

ρ (g/cm^{3}) | Density of THC smoke particle | 3 | [26] |

χ | Dynamic shape factor of smoke particle | 1.5 | [26] |

f_{hyg} | Hygroscopic growth rate factor | 1.5 ^{a} | [47] |

^{a}Assumed based on the hygroscopic growth of particles from a Kentucky 3R4F reference cigarette. CYP, Cytochrome P450; PGP, P-glycoprotein; THC, Tetrahydrocannabinol.

Dose | Study Description | Subjects | Age (year) | Weight (kg) | Purpose | Reference |
---|---|---|---|---|---|---|

Intravenous | ||||||

5 mg/2 min | RD, XO | 11 (100% male) | 18–35 | - | Verification | [85] |

5 mg/2 min | PC, XO | 9 (89% male) | 29.2 (5.2) | 73.7 (10.3) | Verification | [86] |

5 mg/2 min | PC, XO | 9 (89% male) | 25.3 (4.9) | 68.3 (9.6) | Verification | [86] |

5 mg/2 min | - | 8 (100% male) | 24–45 | 64–87 | Verification | [87] |

0.053 mg/kg/2 min | RD, DB, XO | 8 (50% male) | 26–35 | 60 (8)–80 (5) | Training | [88] |

2.5 mg/5 min | DB, PC | 22 (100% male) | 28 (6) | - | Training | [89] |

2.5 mg/5 min | RD, DB, PC | 11 (100% male) | 26.3 (4.2) | - | Training | [90] |

1.6 mg/5 min | P1, SC, OL, 2-periods | 11 (55% male) | 18–40 | 74 | Verification | [91] |

Inhalation (Smoking) * | ||||||

13 mg/6 min | RD, XO | 11 (100% male) | 18–35 | - | Verification | [85] |

12.7 mg/3 min | PC, XO | 9 (89% male) | 29.2 (5.2) | 73.7 (10.3) | Verification | [86] |

13.4 mg/3 min | PC, XO | 9 (89% male) | 25.3 (4.9) | 68.3 (9.6) | Verification | [86] |

15.8 mg, 33.8 mg/11.2 min | RD, DB, LS | 6 (100% male) | 31.3 (29–36) | 77.6 (65–93) | Verification | [92] |

15.3 mg, 30.6 mg, 61.2 mg/6 puffs | RD, CT, PS | 18 (83% male) | 21–45 | - | Verification | [93] |

33 mg/10 min | Two-way, DB, PC | 12 (67% male) | 22 (20–31) | 66 (55–84) | Verification | [94] |

29.3 mg, 49.1 mg, 69.4 mg/22 min | Four-way, RD, DB, PC, XO | 24 (100% male) | 24 (4) | 74 (5) | Training | [95] |

25.6 mg/15 min | DB, XO, PC | 19 (74% male) | 23 (19–38) | 61.5 | Training | [96] |

29.3 mg, 49.1 mg, 69.4 mg/22 min | RD, DB, PC, XO | 24 (100% male) | 24 (4) | - | Training | [97] |

Smoking and lactation * | ||||||

23.18 mg/15 min | Pilot 2–5 mo Postpartum PK study | 8 (100% female) | 18–45 | - | Training and verification | [13] |

45.25 mg/8.7 min | Mommy’s milk study | 50 (100% female) | 22–41 | - | verification | [98] |

Median (Range) | ||||
---|---|---|---|---|

Parameter (Units) | Observed | Predicted | Ratio | AAFE |

AUC (ng$\cdot $h/mL) | 110.5 (33.9–744.4) | 194 (99.2–301.8) | 1.76 | 1.67 |

C_{avg} (ng/mL) | 27.6 (8.4–186.1) | 48.5 (24.8–75.5) | 1.76 | 1.67 |

C_{max} (ng/mL) | 44.7 (12.2–420.3) | 88.7 (55.6–121.1) | 1.98 | 1.93 |

T_{max} (h) | 1 (1–2) | 0.8 | 0.8 | |

Infant dose (mcg/kg/d) | 4.1 (1.3–27.9) | 7.3 (3.7–11.3) | 1.78 | 1.68 |

RID (%) | 1.3 (0.4–8.7) | 2.2 (1.1–3.4) | 0.59 | 1.61 |

_{avg}, average concentration; C

_{max}, maximum concentration; T

_{max}, time to maximum concentration; RID, relative infant dose in percentage; AAFE, absolute average fold error.

Breastmilk | Plasma | Infant AUC_{(0–24 h)} (RID) | ||||||||
---|---|---|---|---|---|---|---|---|---|---|

Joints | C_{max} | AUC_{(0–24 h)} | C_{avg} | C_{max} | AUC_{(0–24 h)} | MP Ratio | 1 mo | 2 mo | 6 mo | 12 mo |

/day | ng/mL | ng·hr/mL | ng/mL | ng/mL | ng·hr/mL | ng·hr/mL (%) | ng·hr/mL (%) | ng·hr/mL (%) | ng·hr/mL (%) | |

1 | 155 | 924.9 | 38.5 | 69.9 | 273.4 | 3.4 | 0.59 (0.74) | 0.49 (0.88) | 0.49 (0.74) | 0.26 (0.48) |

2 | 184 | 1554 | 64.8 | 78.6 | 444.6 | 3.5 | 0.98 (0.63) | 0.81 (0.74) | 0.80 (0.63) | 0.48 (0.41) |

3 | 212 | 2144 | 89.3 | 89.1 | 636.4 | 3.4 | 1.02 (0.57) | 0.84 (0.68) | 0.84 (0.57) | 0.54 (0.37) |

4 | 253 | 2876 | 119.8 | 97.5 | 806.5 | 3.6 | 1.75 (0.58) | 1.49 (0.67) | 1.49 (0.58) | 0.77 (0.38) |

5 | 268 | 3223 | 134.3 | 110 | 968.5 | 3.3 | 1.57 (0.52) | 1.26 (0.62) | 1.32 (0.52) | 0.74 (0.34) |

6 | 309 | 3996 | 166.5 | 120 | 1181 | 3.4 | 1.85 (0.54) | 1.50 (0.64) | 1.41 (0.54) | 0.92 (0.35) |

_{max}, maximum concentration; AUC

_{(0–24 h)}; Area-under-the-curve from 0 to 24 h; C

_{avg}, average concentration; MP, mother-to-plasma; RID, relative infant dose in percentage.

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Shenkoya, B.; Yellepeddi, V.; Mark, K.; Gopalakrishnan, M.
Predicting Maternal and Infant Tetrahydrocannabinol Exposure in Lactating Cannabis Users: A Physiologically Based Pharmacokinetic Modeling Approach. *Pharmaceutics* **2023**, *15*, 2467.
https://doi.org/10.3390/pharmaceutics15102467

**AMA Style**

Shenkoya B, Yellepeddi V, Mark K, Gopalakrishnan M.
Predicting Maternal and Infant Tetrahydrocannabinol Exposure in Lactating Cannabis Users: A Physiologically Based Pharmacokinetic Modeling Approach. *Pharmaceutics*. 2023; 15(10):2467.
https://doi.org/10.3390/pharmaceutics15102467

**Chicago/Turabian Style**

Shenkoya, Babajide, Venkata Yellepeddi, Katrina Mark, and Mathangi Gopalakrishnan.
2023. "Predicting Maternal and Infant Tetrahydrocannabinol Exposure in Lactating Cannabis Users: A Physiologically Based Pharmacokinetic Modeling Approach" *Pharmaceutics* 15, no. 10: 2467.
https://doi.org/10.3390/pharmaceutics15102467