Labetalol Pharmacokinetics in Hypertension During Pregnancy

James H. Fischer, Pharm.D., FCCP

May 17, 2011

Pregnancy: Therapeutic Challenges

• Determine:– whether physiologic changes impact PKs of drug– what are consequences for drug administration

• PK changes tend to be dynamic and unpredictable• Conditions requiring continuous therapy become

particularly challenging– diabetes, epilepsy, hypertension

Anderson 2005

Hypertension in Pregnancy

• Hypertension complicates 10% of pregnancies• Important cause of maternal and fetal morbidity • 3% of pregnant women receive antihypertensive• Lack of evidence for benefit of drug therapy on:

– development of pre-eclampsia– adverse perinatal events

Podymow & August 2008; Andrade et al 2008

Hypertension in Pregnancy

• Antihypertensive treatment targeted to: – Minimize fetus drug exposure– By administering lowest dose to control of blood

pressure/prevent severe hypertension in mother

Abalos et al 2007

Labetalol Treatment of Hypertension During Pregnancy

• α-1 and β adrenergic receptor antagonist • First/ second line agent for treating

hypertension during pregnancy• PK properties:

– Systemic availability: approximately 20-50%– Widely distributes into tissues– 50-60% bound to plasma proteins– Eliminated mainly by hepatic metabolism

• Glucuronidation via UGT 1A1 and 2B7

Goa 1989; Jeong et al 2008

Effect of Pregnancy on Labetalol Pharmacokinetics

• Four earlier studies examined labetalol in pregnancy– increased CL/F in pregnant women (1) – No difference in PK during pregnancy (3)

• Limitations of earlier studies:– Small number of subjects (<10)– Reliance on historical controls

Rubin e al 1983; Nylund et al 1984; Rogers et al 1990; Saotome et al 1993

Objectives

• Compare pharmacokinetics of oral labetalol during and after pregnancy in women being treated for hypertension

• Identify any demographic or clinical factors influencing the variability in labetalol disposition in pregnancy

Rationale for Population PK Approach

• Less restrictive design components– unbalanced designs– sparse sampling

• Obtain informative PK information – population representative of patients– reduces impact of research on medical care

Research Team• Co-Principal Investigator

Gloria Sarto, M.D., Ph.D.

• UIC Co-InvestigatorsLoraine Endres, M.D.

Patricia Fischer, R.N.

Stacie Geller, Ph.D.

Jennifer Hardman, Pharm.D.

Hyunyoung Jeong, Pharm.D., Ph.D.

Sarah Kilpatrick, M.D.

Keith Rodvold, Pharm.D.

• UW Co-InvestigatorsThomas Jenkins, M.D.

Lori Wollett, R.N.

• FDAMargaret Miller, Ph.D.

Methods: Subjects

• Women at least 18 years old, • between 12th week of pregnancy and 3 months

postpartum, and• receiving labetalol for the treatment of chronic or

gestational hypertension.• Provide written informed consent

Methods: Study Design

• Prospective, open-label, longitudinal design• Subjects entered study at any time from 12th

week of pregnancy through 3 months postpartum

• Routine clinical data, drug administration records and plasma concentrations collected at regularly scheduled perinatal or postnatal visits

• Treatment of hypertension occurred independent of study

Methods: Study Design

• Sparse sampling strategy – Sampling occurring within 1 of 5 sampling windows

constructed from the D-optimal sampling times– Single plasma samples were collected at each clinic

visit– 3 plasma samples collected at 2 visits within each

study period (i.e., 2nd trimester, 3rd trimester, postpartum)

• Drug intake was recorded by electronic monitoring (EDEM®) at UIC or diary at UWM

Methods: Laboratory Analysis

• Labetalol Plasma Concentrations:– HPLC with fluorescence detection– linear: 10 – 1020 ng/ml– LLOQ: 10 ng/ml– inter-assay precision: 1.7% to 7.5%

• Fraction unbound to plasma proteins– equilibrium dialysis at RT for 24 hours– recovery: 99.3%– binding independent of concentration: 50-400 ng/ml

Methods: Pharmacokinetic Analysis• Nonlinear mixed effects modeling (NONMEM)

with FOCE method • Subjects with at least one evaluable labetalol

plasma concentration• Step 1: Identify structural (base) model

– PK compartment model– Expressions for interindividual and residual error– Model selection

• Diagnostic plots• SE for parameter estimates• minimum value of objective function (MOF)

– difference between competing models: χ2 distributed

Methods: Pharmacokinetic Analysis

• Step 2: Covariate Analysis– Graphical/GAM screening (S-Plus)– Added alone to structural model– Stepwise forward addition (p<0.05) - backward

deletion (p<0.005)

Covariates• Body Size Measures

total body weightlean body weight

(Janmahasatian et al 2005)

body mass indexbody surface area

• Categorical Variablespregnancy statusethnicitystudy sitetype of hypertensionconcurrent medicationsrenal/hepatic diseasecompliance monitoring

• Continuous Variablesagegestational agecreatinine clearanceserum albuminα-1 acid glycoproteinASTtotal bilirubin labetalol dose

Methods: Pharmacokinetic Analysis

• Step 3: Model validation– Bootstrap analysis:

• 1000 datasets constructed by resampling with replacement• Fit to final PK model• Bootstrap medians compared to population PK parameter

estimates

– Visual predictive check• 250 datasets for labetalol regimen of 300 mg q12h for 6

doses from population model• Median and 80% prediction intervals compared to observed

labetalol plasma concentrations (normalized)

DemographicsDemographics

Number 57Age (y) 30 (18-41)Gestational Age (wk) 20 (11-39)Total Body Weight (kg) 90 (49-161)BMI (kg/m2) 32 (21-62)Ethnicity African American 34 Caucasian 15 Other 8Hypertension Chronic 37 Gestational 20

Pharmacokinetic Data

Study Period

2nd or 3rd + PP 30

2nd + 3rd + PP 17

Labetalol Doses 50 - 2400 mg/day

Labetalol Plasma Concentrations <10 - 1380 ng/ml

Number of Concentrations 11.4 /subject

Structural Model

• Two-Compartment PK model

• Inter-individual variability (IIV)– exponential error– full variance-covariance matrix

• Residual variability– proportional error

Vcka

VpCLD

CL

One- versus Two-Compartment

Predicted Labetalol Plasma Concentration (ng/ml)

0 200 400 600 800 1000 1200 1400Observ

ed L

abeta

lol P

lasm

a C

on

centr

ation (

ng/m

l)

0

200

400

600

800

1000

1200

1400

Predicted Labetalol Plasma Concentration (ng/ml)

0 200 400 600 800 1000 1200 1400Observ

ed L

abeta

lol P

lasm

a C

on

centr

ation (

ng/m

l)

0

200

400

600

800

1000

1200

1400

One-Compartment

Two-Compartment

Covariate Analysis: Oral Clearance (CL/F)• Body Size Measures

total body weightlean body weightbody mass indexbody surface area

• Categorical Variablespregnancy statusethnicitystudy sitetype of hypertensionconcurrent medicationsrenal/hepatic diseasecompliance monitoring

• Continuous Variablesagegestational agecreatinine clearanceserum albuminα-1 acid glycoproteinASTtotal bilirubin labetalol dose

Covariate Analysis: Apparent Central (Vc/F) and Steady-State (Vss/F) Distribution Volumes

• Body Size Measurestotal body weightlean body weightbody mass indexbody surface area

• Categorical Variablespregnancy statusethnicitystudy sitetype of hypertensionconcurrent medicationsrenal/hepatic diseasecompliance monitoring

• Continuous Variablesagegestational agecreatinine clearanceserum albuminα-1 acid glycoproteinASTtotal bilirubin labetalol dose

Covariate Models

• Oral Clearance (CL/F)

CL/F = 188 L/h + (IND × (1+GA/40) × 55 L/h) × LBW/50

• Distribution Volumes (Vc/F and Vss/F)

Vc/F = 197 l × (Preg + 0.9) × TBW/70

Vss/F = 691 l × (Preg + 0.9) × TBW/70

IND=indicator variable

Model Predicted Vc/F and Vss/F for 70-kg Total Body Weight (TBW) Woman

Postpartum Pregnancy

Vc/F (l/70 kg TBW) 197 374

Vss/F (l/70 kg TBW) 691 1313

Model Predicted CL/F for a 50-kg Lean Body Weight (LBW) Woman

Gestational Age (weeks)

0 12 24 36

Lab

etal

ol O

ral C

lear

ance

(l/h

)

100

200

300

400

Post-Partum Pregnancy

188 l/h

258 l/h

296 l/h

Post-Partum

CL/F: Individual Bayesian Estimates

Gestational Age (weeks)

0 12 24 36

La

be

talo

l O

ral C

lea

ran

ce

(l/h

)

0

100

200

300

400

500

600

700

800

Post-Partum Pregnancy

Post-Partum

CL/F during Pregnancy Standardized by Postpartum CL/F

Gestational Age (weeks)

0 10 20 30 40

Pre

gnan

cy t

o P

ostp

artu

m R

atio

of

Labe

talo

l Ora

l Cle

aran

ce

0.0

1.0

1.5

2.0

Population PK Parameters: Model vs. Bootstrap Estimates

Parameter Final Model Bootstrap (n=1000)

Estimate Median 2.5th - 97.5th Percentiles

ka (h-1) 1 --- ---

CL/F (l/h/50 kg LBW) 188 190 161 – 235Effect of gestational age 54 52 35 – 72

CLD/F (l/h) 422 420 323 – 519

Vc/F (l/70 kg TBW) 197 189 110 – 316

Vss/F (l/70 kg TBW) 691 687 617 – 1080

Effect of pregnancy 1.90 1.89 0.3 – 1.6Inter-Individual Variability (CV, %)

CL/F38 38 30 – 45

Vc/F 84 89 62 – 124

Vss/F 40 41 25 – 59

Residual error (%) 36 36 31 - 42

Visual Predictive Check

Time from First Dose (hours)

0 36 48 60 72 84

Labe

talo

l Pla

sma

Con

cent

ratio

ns (

ng/m

l)

1

10

100

1000

Time From First Dose (hours)

0 36 48 60 72 84

Labe

talo

l Pla

sma

Con

cent

ratio

ns (

ng/m

l)

1

10

100

1000

Time From First Dose (hours)

0 36 48 60 72 84

Labe

talo

l Pla

sma

Con

cent

ratio

ns (

ng/m

l)

1

10

100

1000

Second trimester

Third trimester

Postpartum

Relationship: CL/F vs Lean Body Weight

Lean Body Weight (kg)

0 30 40 50 60 70 80

La

be

talo

l Ora

l Cle

ara

nc

e (

l/h)

0

100

200

300

400

500

600

700

800

Relationship: CL/F vs Total Body Weight

Total Body Weight (kg)

0 40 60 80 100 120 140 160 180

Lab

etal

ol O

ral C

lear

ance

(l/h

)

0

100

200

300

400

500

600

700

800

Implications of Different Relationships between CL/F and LBW or TBW

• Lean body weight (LBW) provides more clinically useful indicator of differences in dose requirements among women of varying body sizes

• Excessive labetalol exposure may be reduced by adjusting labetalol doses based on LBW, or without regard to body size, rather than TBW

Mechanism for Pregnancy-Induced Change in CL/F

• Labetalol– high extraction ratio– hepatic metabolism

• Explanation for higher CL/F– reduced absorption from GI tract– decreased plasma protein binding– increased hepatic intrinsic clearance

Effect of Pregnancy on Labetalol Plasma Protein Binding

Pregnancy Status

Serum Albumin (g/dl)

Serum α-1 Acid Glycoprotein (mg/100 ml)

Labetalol Free Fraction (%)

Lipoproteins(% of non-pregnant value)

Globulins(% of non-pregnant value)

2nd Trimester 3.1 69 38% 118%* 110%*

3rd Trimester 2.9 58 42% 135%* 124%*

Post-partum 3.6 120 41% --- ---

Fischer et al 2011 * Literature values

Mechanism for Pregnancy-Induced Change in CL/F

• Labetalol– high extraction ratio– hepatic metabolism

• Explanation for higher CL/F– reduced absorption from GI tract– decreased plasma protein binding– increased hepatic intrinsic clearance

• Explanation for greater Vc/F and Vss/F– increased hepatic intrinsic clearance

Pathway for Sex Hormone Regulation of Expression of UGT 1A1 and CYP 3A4

XREM Promoter Region

Progesterone

PXR

PXR

PXR

RXR

RXR

CYP 3A4UGT 1A1

Jeong et al 2008

Conclusion

• Population PK analysis allowed successful characterization of labetalol pharmacokinetics during pregnancy

• Pregnancy significantly influenced labetalol PK– higher CL/F and greater Vc/F and Vss/F– increased hepatic intrinsic CL likely mechanism

• Wide individual variability for CL/F precludes providing specific dosage recommendations

• Lean body weight provides a more useful guide for adjusting labetalol doses in pregnant women than total body weight