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cpms predict and confi Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December 2008 Monica Simeoni PAGE, 23 rd June 2009 Defining clinical relevance: model-based update of the label

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Page 1: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

cpmspredict and confirm

Prediction of clinically active doses of anticancer candidates based on preclinical data

Monica Simeoni & Italo Poggesi9th December 2008Monica Simeoni

PAGE, 23rd June 2009

Defining clinical relevance: model-based update of the

label

Page 2: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

cpmspredict and confirm

Remifentanil hydrochloride (ULTIVA™)

selective -opioid receptor agonist

for injection during the induction and maintenance of general anaesthesia.

has a short effective biological half-life of less than 10 minutes.

administered for long periods of time and at high doses without risk of significant accumulation.

Intensive care unit (ICU) subjects have varying degrees of organ dysfunction, so the organ independent metabolism of remifentanil makes it a very useful agent in this setting

metabolised to remifentanil acid (RA) which has been shown to be 1/4600 times less potent than remifentanil. RA is therefore thought not to result in any clinically relevant effects at concentrations below 900 ng/ml.

Remifentanil acid is eliminated via the kidney and in subjects with severe renal impairment its elimination is prolonged.

Page 3: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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The label

The current GDS statement quotes: “The

clearance of the carboxylic acid metabolite is

reduced in patients with renal impairment. In

intensive care patients with moderate/severe

renal impairment, the concentration of the

carboxylic acid metabolite is expected to reach

approximately 100 fold the level of remifentanil

at steady-state.”

Page 4: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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Issue

This statement follows the analysis of a up to 3 day treatment study (3d study) where the concentrations did not reach the steady state (SS) and the metabolic ratio (MR) defined as:

MR=(Concmetabolite/Concparent)SS

was approximated as:

MRAUC_lastmetabolite/AUC_lastparent

Questions:

can we have a more precise measurement of MR in non-steady state conditions?

after an up-to 10 days treatment study (10d study), is this statement still valid?

Page 5: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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Data

Both studies contained subjects with normal renal function and subjects with mild, moderate and severe renal impairment.

Arterial remifentanil and remifentanil acid concentrations in the 10d study were very limited, given they were based on a particularly sparse sampling regimen, while concentration-time data from the 3d study were more extensive, following a serial sampling regimen

Page 6: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

cpmspredict and confirm

Data

Subject 17413

Time After Start of Infusion (h)

0 20 40 60 80 100 120 140

Infu

sio

n R

ate

(u

g/k

g/h

)

0

5

10

15

20

Co

nc

en

tratio

n (n

g/m

L)

0

5

10

15

20

25

Infusion Rate

Remifentanil Concentration

Remifentanil Acid Concentration

Subj from 10d study. Sparse sampling(N=53, samples=198)

The system was not in steady state conditions. The infusion rate is rapidly varying within the study time interval.

In 3d study each subject received a different infusion rate in order to maintain a Sedation-Agitation Scale (SAS) score 2-4 with no, or only mild pain.

Subject 16141

Time After Start of Infusion (h)

0 12 24 36 48 60 72

Infu

sio

n ra

te (u

g/k

g/h

)

0

5

10

15

20

Co

nc

en

tra

tio

n (

ng

/mL

)

0

50

100

150

200

250

300

Infusion Rate

Remifentanil Concentration

Remifentanil Acid Concentration

Subj from 3d study. Extensive sampling (N=40, samples=1689)

Page 7: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

cpmspredict and confirm

Data

moderate / severe renal impairmentnormal / mild renal impairment

Pitsiu et al., British Journal of Anesthesia, 2004

Page 8: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

cpmspredict and confirm

Two-compartment model: moderate / severe renal impairment

Three-compartment model: normal / mild renal impairment

221

2

110

1

V

CLMM

V

CLR

dt

dM

V

CLRtuk

dt

dR

33

22

3

22

33

22

11

2

110

1

V

QM

V

QM

dt

dM

V

CLMM

V

QM

V

QM

V

CLR

dt

dM

V

CLRtuk

dt

dR

where R= remifentanil, M metabolite

The original Model

Page 9: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

cpmspredict and confirm

In our analysis the clearance of metabolite has been modelled as a function of creatinine clearance (CRCL) and the regression parameters directly estimated from the overall model:

At steady state the ratio of the metabolite versus the parent (metabolic ratio) was calculated in Pitsiu et al as the ratio of their AUClast. In our analysis the metabolic ratio is calculated from the general model at steady state and is equal to the ratio of the inverse of the two clearances:

CRCLBACLM exp

CLM

CL

V

RV

M

MR

1

1

2

2

The Model: novel parameter description

Page 10: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

cpmspredict and confirm

Methods

Pitsiu et al were limited to modelling the concentration data for each individual separately

Non-Linear Mixed-Effect approach was employed in the current analysis and an update of the structural model presented by Pitsui et al. was implemented

Population analysis of the combined dataset was not successful likely for the heterogeneity of the two.

Population analysis of 3d study and with the estimated parameters posthoc analysis (MAXEVAL=0) of 3d and 10d studies

Page 11: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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Methods

Model validation: given the different infusion profile for each subject it was not possible to perform the standard visual predictive check (VPC) considering all the subjects together, instead the VPC of 300 simulated parent and metabolite profiles for each subject and the VPC of the corresponding 300 estimates of the metabolic ratio for each subject were performed

Page 12: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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Results: VPC

Page 13: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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Results: PPC

Moderate/severe renal impaired subjects normal, mild renal impaired subjects

Page 14: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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Results: posthoc analysis

3d Study 10d Study

Page 15: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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Results: posthoc analysis

5.23 PRED v DV REMI ACID

DV

0.01 0.1 1 10 100 1000 10000

PR

ED

0.01

0.1

1

10

100

1000

10000

5.23 IPRED v DV REMI ACID

DV

0.01 0.1 1 10 100 1000 10000

IPR

ED

0.01

0.1

1

10

100

1000

10000

5.23 PRED v DV REMI

DV

0.001 0.01 0.1 1 10 100

PR

ED

0.001

0.01

0.1

1

10

100

5.23 IPRED v DV REMI

DV

0.001 0.01 0.1 1 10 100

IPR

ED

0.001

0.01

0.1

1

10

100

parent

metabolite

Open circles = 3d study, red circles = 10d study (n

g/m

l)

(ng

/ml)

(ng

/ml)

(ng

/ml)

(ng/ml)

(ng/ml)

(ng/ml)

(ng/ml)

Page 16: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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Normal/Mild (N=51) Moderate/Severe (N=42)

Remifentanil CL (mL/h/kg)

Remifentanil Acid CL (mL/h/kg) MR

Remifentanil CL (mL/h/kg)

Remifentanil Acid CL (mL/h/kg) MR

2900(681- 13785)

233(5.09 - 11753)

12.46

(0.23 - 243)

3019(1607 - 10859)

42.8(7.34 - 464)

70.6

(5.86 - 352)

Normal/Mild (N=12) Moderate/Severe (N=28)

Remifentanil CL (mL/h/kg)

Remifentanil Acid CL (mL/h/kg) MR

Remifentanil CL (mL/h/kg)

Remifentanil Acid CL (mL/h/kg) MR

2650(1231 – 10013)

169.6(113 – 270)

15.6

(7.50 – 41.5)

2743(1607 – 10885)

36.3(7.34 – 151)

75.6

(19.5– 352)

Summary (geometric mean & range) of individual predictions of remifentanil and remifentanil acid clearance along with predicted MR in 3d study

Summary (geometric mean & range) of individual predictions of remifentanil and remifentanil acid clearance along with predicted MR in combine dataset of 3d and 10d study

Results: posthoc analysis

Page 17: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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Predicted typical and individual values of remifentanil acid clearance (CLM) (left, upper panel) and metabolic ratio (MR) (left, lower panel); p values (i.e. 1-cpf) of the lognormal distributions of MR in the typical subject of group 1 and group 2 (right panel).

Results: MR estimate from the mixed effect model

Page 18: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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Conclusions

The model-based approach allowed us to estimate the MR, defined as a steady state parameter, in non-steady state conditions

MR was estimated to exceed 200 in approximately 12% of ICU patients with moderate/severe renal impairment.

Following this findings, the label is in the process to be updated. The current proposed text is: “The clearance of the carboxylic acid metabolite is reduced in patients with renal impairment. In intensive care patients with moderate/severe renal impairment, the mean concentration of the carboxylic acid metabolite is not expected to exceed 100 fold the level of remifentanil at steady-state. ... ”

Page 19: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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Acknowledgments

Chao Chen and Jonathan BullmanRemifentanil project team

Page 20: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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Back-up

Page 21: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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Studies-USA30212 & USA30226

USA30212 was an open label, non-comparator multi-centre study to assess the safety, efficacy and pharmacokinetics of Remifentanil in intensive care unit patients with varying degrees of renal dysfunction requiring analgesia and sedation in association with mechanical ventilation. Study treatment was permanently discontinued after a maximum of 72h, by reducing the Remifentanil infusion rate by 25% at 10 min intervals.Remifentanil and remifentanil acid concentrations were determined following extensive blood sampling study USA30212

USA30226 was a randomised, open-label, multicentre, parallel group study comparing the safety and efficacy of an ULTIVA™ (Remifentanil Hydrochloride) based analgesia/sedation regimen with a conventional sedative based regimen in long-term ICU subjects requiring analgesia and sedation for up to 10 days.Remifentanil and remifentanil acid concentrations were determined following sparse sampling in study USA30226.

Page 22: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

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Back-up

Page 23: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

cpmspredict and confirm

THETA/Parameter/Units EstimatePrecision of the

Estimate (%)

1, V1 (Remifentanil), L/kg 0.513 15.1

2, CL (Remifentanil), mL/min/kg 45.5 8.3

3, A (see Equation. 3) (Remifentanil Acid), mL/h/kg 25.3 14.4

4, V2 (Remifentanil Acid), L/kg 0.77 4.6

5, V3 (Remifentanil Acid), L/kg 0.378 27.2

6, Q (Remifentanil Acid), mL/h/kg 30.6 31.2

7, B (see Equation. 3) (Remifentanil Acid), mL/h/kg 2.4 10.5

IIV, V1, %CV 66.0 46.7

IIV, CL, %CV 48.3 34.0

IIV, CLM, %CV 47.9 27.5

IIV, V2, %CV 30.7 26.3

RUV, proportional, %CV (Remifentanil) 21.7 33.7

RUV, proportional, %CV (Remifentanil Acid) 18.8 20.4

RUV, additive, SD, ng/mL (Remifentanil) 0.45 35.0

RUV, additive, SD, ng/mL (Remifentanil Acid) 0.61 50.1

Summary of estimates of population pharmacokinetic parameters and associated variability from study USA30212

Results

Page 24: Cpms predict and confirm Prediction of clinically active doses of anticancer candidates based on preclinical data Monica Simeoni & Italo Poggesi 9 th December

cpmspredict and confirm

Ultiva renewal is needed for Mexico. Ultiva FREP is for Peru, Nigeria, Albania, & Malaysia.Europe is also in progress