1. Drug Transfer into Milk: Clinical Methods & Issues Patrick J. McNamara University of Kentucky College of Pharmacy College of Pharmacy

2. Outline Clinical Study Design Issues Clinical Study Design Issues Models Models Active Transport Issues Active Transport Issues Neonatal Exposure Issues Neonatal Exposure Issues Conclusions Conclusions

3. Neonate Exposure via Milk SS serum conc. SS serum conc. in the neonate Neonatal factors Neonatal factors bioavailability (F), volume of milk consumed (V), nursing interval (  and systemic clearance (Cl) bioavailability (F), volume of milk consumed (V), nursing interval (  and systemic clearance (Cl) Maternal factors Maternal factors bioavailability (F), dosing rate, milk to serum ratio (M/S) and systemic clearance (Cl) bioavailability (F), dosing rate, milk to serum ratio (M/S) and systemic clearance (Cl)

4. Clinical Study Design Issues Single Time Point vs AUC Approach Single Time Point vs AUC Approach Milk Concentration vs M/S Milk Concentration vs M/S M/S & Neonate Concentrations M/S & Neonate Concentrations

5. Single Time Point vs AUC Approach Time dependence in M/S (Wilson, 1985) Time dependence in M/S (Wilson, 1985) Hydrochlorothiazide, single dose Hydrochlorothiazide, single dose Nadolol, multiple dose Nadolol, multiple dose Observation of cimetidine in rabbits Observation of cimetidine in rabbits 4003002001000.1 1 10 100 Serum Milk Time (min) Conc (ug/ml) 3002001000 0 5 10 15 20 Time (min) M/S AUCm/AUCs

6. Clinical Study Design Issues Milk Concentration vs M/S Milk Concentration vs M/S Milk concentrations sufficient for exposure est. Milk concentrations sufficient for exposure est. M/S provides greater societal/scientific value M/S provides greater societal/scientific value PK estimate in lactating mother PK estimate in lactating mother Insight into mechanism (passive vs active) Insight into mechanism (passive vs active) Overall modeling of drugs (& chemicals) into milk Overall modeling of drugs (& chemicals) into milk M/S & Neonate Concentrations M/S & Neonate Concentrations Neonatal concentrations - very valuable Neonatal concentrations - very valuable Logistical and ethical issues make these studies difficult to carry out Logistical and ethical issues make these studies difficult to carry out

7. Models Physiochemical Model Predictions Physiochemical Model Predictions Animal Models Animal Models Cell Culture Models Cell Culture Models

8. Physiochemical Predictive Models Unbound distribution model [Rasmussen, 1958 & 1959; Sisodia and Stowe, 1964] Unbound distribution model [Rasmussen, 1958 & 1959; Sisodia and Stowe, 1964] pH partition hypothesis pH partition hypothesis Membrane diffusion model [Meakin, 1985] Membrane diffusion model [Meakin, 1985] molecular weight, log P, degree of dissociation molecular weight, log P, degree of dissociation Phase distribution model [Fleishaker, 1987] Phase distribution model [Fleishaker, 1987] physicochemical factors & distribution into milk components physicochemical factors & distribution into milk components log-transformed distribution model [Atkinson and Begg, 1990] log-transformed distribution model [Atkinson and Begg, 1990] stepwise multiple linear regression stepwise multiple linear regression Genetic neural network model [Agatonovic- Kustrin, 2000] Genetic neural network model [Agatonovic- Kustrin, 2000] 60 drug compounds - 61 est. structural features 60 drug compounds - 61 est. structural features

9. Factors Influencing M/S

10. Physiochemical Model Prediction Agatonovic-Kustrin, Analytica Chimica Acta 418:181 (2000) Good overall prediction Good overall prediction Obtained with no experimental parameters (e.g., binding, partitioning, etc) Obtained with no experimental parameters (e.g., binding, partitioning, etc) Data analysis still only as good as the data sets used to generate the relationships Data analysis still only as good as the data sets used to generate the relationships

11. Cell Culture Models Nitrofurantoin Flux across CIT 3 Cells Nitrofurantoin Flux across CIT 3 Cells

12. 100 10 1 0.1 0100 200 300 Concentration, ug/ml Time, min Animal Models Nitrofurantoin M/S in Rats [Kari, 1997] Nitrofurantoin M/S in Rats [Kari, 1997] Nitrofurantoin in milk and plasma of 10-day lactating rats gavage-fed 50mg/kg nitrofurantoin Nitrofurantoin in milk and plasma of 10-day lactating rats gavage-fed 50mg/kg nitrofurantoin M/P predicted = 0.31 M/P observed = 23.1

13. M/S Prediction Rabbit 0.010.1110 0.01 0.1 1 10 M/S Pred M/S Obs Rat 0.010.1110100 0.01 0.1 1 10 100 NF CM RN AC M/S Pred Human 0.1110 0.1 1 10 NF CM M/S Pred

14. Active Transport Issues Clinical evidence Clinical evidence Carriers Carriers Substrate / Drug Database Substrate / Drug Database

15. Cimetidine in Human Milk 302520151050.01.1 1 10 100 Time (h) 1200 mg 302520151050.01.1 1 10 100 Serum Milk Time (h) 600 mg 302520151050.01.1 1 10 100 Time (h) CONC (ug/ml) 100 mg (Oo, et al, 1995)

16. ParameterSubject1234MeanSD M/S pred 0.250.270.340.240.280.05 M/S obs 4.345.2510.145.046.192.66 Nitrofurantoin in Human Milk (Gerk, et al, 2001)

17. Transporters C Candidate genes expressed (RT-PCR) in cells isolated from human milk (Ito and McNamara Labs) Protein Expression – Structural studies Functional studies Substrate / Drug Database Substrate / Drug Database

18. Neonatal Exposure Issues Route of Drug Clearance Route of Drug Clearance Nursing vs Dosing Interval Nursing vs Dosing Interval Mechanism of Toxicity Mechanism of Toxicity Lactation vs Developmental Stage Lactation vs Developmental Stage

19. Route of Drug Clearance Developmental patterns vary Developmental patterns vary GFR normalized to body weight appears comparable to adult GFR normalized to body weight appears comparable to adult Metabolic pathways vary Metabolic pathways vary CYP-450 and most Phase II reactions are inefficient at birth CYP-450 and most Phase II reactions are inefficient at birth Sulfate conjugation is the exception Sulfate conjugation is the exception

20. Developmental Expression of Cytochrome P450 110100 0 10 20 30 40 50 1A2 2C 2D6 2E1 3A4 Age, Days % of Adult In Vitro Activity [Vieira, 1996;Treluyer, 1997; Sonnier, 1998]

21. Nursing vs Dosing Interval Chronic vs Acute Dosing Chronic vs Acute Dosing Generalizations Generalizations Longer t 1/2 longer  Longer t 1/2 longer  Longer  less able to “control” exposure Longer  less able to “control” exposure 04812162024 Time, h Conc 04812162024 Time, h Conc

22. Neonatal Exposure Higher exposure Higher exposure Higher M/S Higher M/S Lower Cls Lower Cls Maternal Maternal Neonate Neonate Lower First Pass? Lower First Pass?

23. Conclusions Diffusion accounts for appearance of most drugs in milk Diffusion accounts for appearance of most drugs in milk M/S can be predicted M/S can be predicted unbound, cationic lipophilic drugs favor higher M/S unbound, cationic lipophilic drugs favor higher M/S Transporter gene expression in lactating mammary epithelial cells – limited number of drugs Transporter gene expression in lactating mammary epithelial cells – limited number of drugs Neonate exposure assessment should include: Neonate exposure assessment should include: Maternal clearance: higher clearance less exposure Maternal clearance: higher clearance less exposure Neonatal clearance: lower clearance more exposure Neonatal clearance: lower clearance more exposure Active metabolites should be considered Active metabolites should be considered