Nantes 2009 1

Prise en compte de la pharmacocinétique dans la

prescription des médicaments anticancéreux

Pr étienne ChatelutInstitut Claudius-RegaudUniversité de Toulouse

Nantes 2009 2

IntroductionAdaptation individuelle des doses

limite de la surface corporellevariabilité pharmacocinétique interindividuelle

« More is better »“more drug” pour plus d’effet thérapeutique“more information” pour mieux adapter la dose

Cytotoxiques – thérapeutiques ciblées

Prise en compte des caractéristiques pharmacodynamiques

Nantes 2009 3

Response rates in phase I

Von Hoff and Turner, Investigational New Drugs 1991

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Dose or Concentrations ?

• There are correlated: AUC = Dose/CL(AUC= area under the curve of plasma versus time concentration =

global exposure of a patient to a drug ; CL = clearance of elimination of the drug)

• Is there a benefit to control plasma drug concentrations ? Or Dose is enough ?

• Response: it is largely dependant of the inter-individual variability (IIV) on CL

Nantes 2009 5

6-MP et LAL: survie et AUC plasmatique

AUC moyenne de 100 (A), 200 (B) et 400 (C) ng de 6-MP/mL/h [Koren et al, New Engl J Med 1990]

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Carboplatine et cancer ovarien [Jodrell et al, J Clin Oncol 1992]

Toxicity: grade ≥3 thrombocytopenia ( )Efficacy: Likelihood of response( )

=> Individual dosing of Carboplatin :Dose (mg) = predicted CL x target AUC

Nantes 2009 7

AUC better than Dose:Proof of concept: Evans et al

New Engl J Med 1998

Childhood Acute Lymphoblastic LeukemiaHigh-dose methotrexate – Teniposide – Cytarabine

individualized: AUC corresponding to 50th to 90th percentile of conventional dose (per m²)

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Low IIV: expected in Phase 1 study(F) x Dose Clearance

0

10

20

30

40

50

60

0 2 4 6 8 10 12

Time

Plas

ma

Con

cent

ratio

ns

CL = 8CL = 10

AUCAUC

R²=0.58

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Large IIV: observed in clinical practice(F) x Dose Clearance

0

10

20

30

40

50

60

70

80

0 2 4 6 8 10 12

Time

Plas

ma

Con

cent

ratio

ns

CL = 3CL = 10

R = 0.50

0

1

2

3

4

5

6

7

8

9

10

0 100 200 300 400 500 600 700

Carboplatin Dose (mg/m²)

AU

C

R²=0.25

AUCAUC

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Méthodes d’adapation individuelle des doses

• Surface corporelle• Prescription en AUC pour le

carboplatine• Exploration phénotypique ou

génotypique pour le 5-fluoro-uracile• Suivi des concentrations plasmatiques

et hautes doses ; les « inibs »

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Dose en mg/m²

• Avantages– Individualisation de la dose– Onco-pédiatrie: capacités d’élimination

(clairance, CL) corrélées morphologie– Reproductible: équation de Dubois

• Inconvénients– Patients adultes: CL n’est que rarement

corrélée à surface corporelle

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Exemple: topotécan

0

5

10

15

20

25

30

35

40

45

50

1.3 1.5 1.7 1.9 2.1 2.3 2.5Body Surface Area (m²)

CL

(L/h

r)

dutch patientsfrench patients

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variabilité inter-individuelle

• élimination rénale– fonction rénale (filtration glomérulaire)– sécrétion tubulaire (transport actif)

• élimination non rénale– métabolisme hépatique– transport au niveau biliaire et digestif: ABC

transporteurs (glycoprotéine P)

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Expression de la P-gp (ABCB1)[Thomas et al, Curr Top Med Chem 2004]

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Sécrétion tubulaire rénale

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Élimination rénale: méthodes de prédictions de CL

• Exemple (extrême) du carboplatine– Prédiction de CL par équations (Calvert,

Cockcroft-Gault, Chatelut)– Créatinine sérique, poids, âge, sexe– Choix de l’AUC

Nantes 2009 17

Carboplatin PK studiesas an example in term of methodology comparison

Calvert equation (CLcarbo = GFR + 25 mL/min) was developed by a 2-stage approach [J Clin Oncol 1989] :

1) successive determinations of carboplatin CL (from AUC determined by trapezoidal rule)

2) linear regression between CL and GFR (Glomerular Filtration Rate determined by 51Cr-EDTA clearance)

We applied the population PK method [J Natl Cancer Inst 1995]:

simultaneous analysis of PK data (conc vs. time) and covariates of 34 patients (using a two-compartment model and proportional inter-individual variability)

• 218.weight (1 - 0.00457.age).(1 - 0.314.sex)serum creatinine level (µM)

CLcarbo = 0.134.weight +

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Two main limits• Serum creatinine is also dependent of its

production (muscular mass), and nutrition status ; obese, and underweight patients

• Scr: bias between assay methods (up to 40% of difference)

• Clin Cancer Res 2006:

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Facteurs d’hétérogénéité des pratiquesexemple: Patient (femme, 82 kg, 1.8 m², 63 years)

Creatinine assay 126 µM (non compensated

Jaffé)

91 µM (enzymatic

assay)Equation to predict CL

Calvert equation Chatelut equation

(no correction for obesity)

Target AUC 4 5

310 mg 540 mg +74%

+25%

+10%

+38%

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More information:Cystatin C plasma level

• Small Protein (120 amino-acids) expressed in all nucleated cells

• Marker of Glomerular Filtration Rate (GFR)– filtered– not secreted– completely reabsorbed and catabolised within the

tubular cells

• Nephrology: conflicting results about cystatin’s performance compared to creatinine

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Mono-center study ; 45 patients

[Clin Pharmacokinet 2005]

Carboplatin CL (mL/min) =

110. (SCr/75)-0.512.(cysC/1)-0.327.(BW/65)0.474.(AGE/56)-0.387. 0.850SEX

with SEX = 0 if male, =1 if female, SCr in µmol/L, cysC in mg/L, BW in kg and AGE in years

Nantes 2009 22

prospective validation [Clin Cancer Res 2009]

of a first monocenter study (45 patients, Clin Pharmacokinet 2005)

• Multi-center study: 10 centres• 357 patients, standard carboplatin treatment• 3 blood samples per patient• Population pharmacokinetic analysis

– NONMEM program – Simultaneous analysis of data from all patients– Relationships between patients’ characteristics

(=covariates) and PK parameters

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0

10

20

30

40

50

60

70

80

0 1 2 3 4 5 6 7 8

time (h)

carb

opla

tin u

f con

cent

ratio

n (m

g/L)

Carboplatin plasma concentrations vs. Time

Nantes 2009 24

Carboplatin plasma concentrations vs. Time

0

10

20

30

40

50

60

70

80

0 1 2 3 4 5 6 7 8

time (h)

carb

opla

tin c

once

ntra

tion

(mg/

L)

Patient 1:CL = 48ml/min, Cys C 1.73mg/L

Mean PK parameters: CL = 118ml/min, mean Cys C 1.0mg/L

Patient 2: CL = 236ml/min, Cys C 0.75mg/L

Nantes 2009 25

Carboplatin CL versus each characteristic

0

50

100

150

200

250

130 140 150 160 170 180 190 200 210BSA

carb

opla

tin C

L (m

l/min

)

0

50

100

150

200

250

30 50 70 90 110 130

body weight (kg)ca

rbop

latin

CL

(ml/m

in)

0

50

100

150

200

250

-1 -0.5 0 0.5 1 1.5

sex (=0 for male, =1 for female)

carb

opla

tin C

L (m

l/min

)

0

50

100

150

200

250

20 30 40 50 60 70 80 90

age (years)

carb

opla

tin C

L (m

l/min

)

0

50

100

150

200

250

30 50 70 90 110 130 150 170 190

serum creatinine (µmol/L)

carb

opla

tin C

L (m

l/min

)

0

50

100

150

200

250

0 0.5 1 1.5 2 2.5 3

serum cystatin C (mg/L)ca

rbop

latin

CL

(ml/m

in)

Nantes 2009 26

Best covariate equation to predict carboplatin CL

CL (mL/min) =

357 patients, multicentric study (modified Thomas formula):

118. (SCr/75)-0.450.(cysC/1)-0.385.(BW/65)0.504.(AGE/56)-0.366. 0.85SEX

45 patients, monocentric study (original Thomas formula, Clin Pharmacokinet 2005):

110. (SCr/75)-0.512.(cysC/1)-0.327.(BW/65)0.474.(AGE/56)-0.387. 0.85SEX

Evaluation of predictive performance in subgroups of patients defined according to their Body Mass Index:

Normal, Underweight (BMI<18.5), Obese (BMI>30)percent error: (CLpred – CLobs)/CLobserved (x 100)

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UnderweightThomas

012345678

-55 -45 -35 -25 -15 -5 5 15 25 35 45 55 65 75 >80

Normal weightThomas

0

10

20

30

40

50

60

70

-55-45-35-25-15 -5 5 15 25 35 45 55 65 75>80

ObeseThomas

02468

1012141618

-55-45-35-25-15 -5 5 15 25 35 45 55 65 75>80

UnderweightCalvert

012345678

-55 -45 -35 -25 -15 -5 5 15 25 35 45 55 65 75 >80

Normal weightCalvert

0

10

20

30

40

50

60

70

-55-45-35-25-15 -5 5 15 25 35 45 55 65 75 >80

ObeseCalvert

02468

1012141618

-55-45-35-25-15 -5 5 15 25 35 45 55 65 75>80

25%

23%

45%

39%

30%

28%

Nantes 2009 28

Médicaments à élimination rénale importante

• Étoposide, topotécan, pemetrexed• Valeur seuil de clairance de la

créatinine– Pour contre-indiquer le médicament:

pemetrexed (40 mL/min)– Pour adapter la posologie: topotecan

(demi-dose si 20-40 mL/min)

Nantes 2009 29

Médicaments à élimination hépatique

• Docétaxel: fonctions hépatiques et CYP3A4 (ALAT, ASAT, PAL)

• Irinotécan: SN-38 et UDP-glucuronosyl-transférase UGT1A1 (*1 vs. *28): (TA)6TAA vs. (TA)7TAA

• 5-fluoro-uracile et Dihydropyrimidine déshydrogénase (DPD)

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ITKs: e.g., Imatinib• Inhibitor of tyrosine kinase of Bcr-Abl (CML) and c-Kit

(GIST)

• PK ; and corresponding variability– metabolized by CYP3A4 ; high IIV– substrat of ABCB1 (P-gp) ; additional PK variability– largely bound to α1-acid glycoprotein in plasma ;

inflammatory protein, free fraction (fu) highly variable

• Dose is an issue: CML, GIST [reviewed by Jan Judson, J Clin Oncol 2008]

Nantes 2009 31

Imatinib and daily Dose (400mg, 600 mg), 2002

Confirmed for 400 mg vs. 800 mg [Rankin et al, ASCO 2004]

Nantes 2009 32

0%0%

20%20%

40%40%

60%60%

80%80%

100%100%

00 11 22 33 44 55Years After RegistrationYears After Registration

Imatinib 400mgImatinib 800mg800mgChemotherapyChemotherapy

At RiskAt Risk352353

82

DeathsDeaths1061061137373

EstimateEstimate76%76%72%72%26%26%

Imatinib & Overall Survival in metastatic GIST

TwoTwo--YearYear

PrePre--ImatinibImatinib

Survival ImprovedWith Imatinib

Rankin et alS0033 StudyProc ASCO 2004, #9005

Nantes 2009 33

Efficacy is highly dependent of Kit genotype

J Clin Oncol 2003

Nantes 2009 34

Eur J Cancer 2006

Dose is (in fact) an issue ; what about the concentrations ?

Nantes 2009 35

Clin Cancer Res 2006

Trough=residual concentrations

Nantes 2009 36

Relationship between daily AUC and hematopietic toxicity

Total plasma imatinib concentrations (AUC)

Free plasma imatinib concentrations (unbound AUC estimated from α1-glycoprotein acid

R²=0.10

R²=0.32

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Blood 2007

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BJC 2008

Unbound AUC

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Exon 11

Exon 9

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J Clin Oncol 2009

Nantes 2009 41

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Historic of Imatinib and GIST

1996 20082002 2003 2006 200?-20??

drug PK-PD*genotypeGIST TDM**dose

*PK-PD relationships

** Therapeutic Drug monitoring

Nantes 2009 43

TDM et Hautes DosesTICE: taxol, ifosfamide, carboplatin, etoposide[Motzer et al, J Clin Oncol 2000]

phase I: niveau d’AUC de carboplatine de 12 à 32 mg/mL x min (AUC totale correspondant à 3 perfusion quodienne par cycle)

phase II: AUC optimale de 24 mg/mL x min

Dose = (DFG + 25) x 24Où DFG prédit par l’équation de Calvert-Jelliffe

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Limite de la méthode d’adaptation a priori

Nantes 2009 45

0

10

20

30

40

50

60

70

80

0 8 16 24 32 40 48 56 64 72Time (hours)

Car

bopl

atin

con

cent

ratio

ns (m

g/L) Bayesian adjusted concentrations

Observed concentrations

E.g., Observed AUC 24.8 (vs. 30.9 sans adaptation de dose)

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J Clin Oncol 2005

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À tout instant t:

E drug = Ksens x Conc plasma du cytotoxique

Modèle PK-PD[Friberg et al, J Clin Oncol 2002]

Nantes 2009 48

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

0 5 10 15 20 25 30Time (days)

ANC (x106 /L)

observed valuespredicted values

Docétaxel et neutropénie[Puisset et al, Br J Cancer 2007]

Nantes 2009 49

Neutropénie vs. Pré-traitement

0

500

1000

1500

2000

2500

3000

3500

0 5 10 15 20 25 30Time (days)

model predicted ANC (x106 /L)

PTT=0PTT=1

Nantes 2009 50

Conclusion• More drug is better even of targeted therapy

• More individual information is needed to perform optimal treatment: e.g. inib– disease (is any TK receptor involved ?)– genotype (tumour of the patient)– PK (patient): trough concentrations, AUC, AUCu

(free AUC)

• Standardisation des Protocole d’adaptation individuelle des doses

Nantes 2009 515151

EORTC-PAMM meetingToulouse January 28-30 2010

main topic: Treatment individualizationhttp://www.eortc-pamm2010-toulouse.fr/accueil.htm