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`
`Table 3 Lacosamide Final Population PK Model Parameter Estimate Derived from
`Trial SP640
`
`Parametersm RSE * [%]
`Ka [1/hr]
`Ka = 61
`not applicable
`61
`4.0 Fixed
`not as Iicable
`
`Ke [1/hr]
`65
`
`V/f [L]
`62
`
`03
`
`64
`
`“V on Ka [%]
`IN on Ke [%]
`
`”V on V/f [%]
`
`Proportional
`Residual Error
`
`[%]
`
`0.0449
`
`V/f = 62 + 63 ><(LBW—50.6) + 94 x
`heioht-1.70
`43.4
`
`0.544
`
`29.4
`
`
`
`0 (Fixed)
`13.1
`
`6.25
`
`not applicable
`1.74
`
`not aplicable
`1.36
`
`22.4
`
`34.7
`
`0 (Fixed)
`15.5
`
`35.8
`
`7.76
`
`6.73
`
`Note: * RSE= Relative Standard Error
`
`Figure 6 Goodness-of—fit Plots for Lacosamide Final Population PK Model Derived
`from Trial SP640
`
`/ / 1/
`
`1
`
`/
`
`_
`>
`4
`_
`_
`'
`Data my“; {main 6 _
`Dow "We" resmswn 6nd «1mm 2rd R-mmd). hue of‘dmumwlxd) Imeluded as Imm-
`
`mu mm; Am...“ 6
`Dam Mmxegrnfim (incl, cqwim mill-maxed). 1m al’idmu‘ry (whd) n inchuiedn : tell-twee.
`
`(A)
`
`(B)
`
`

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`Lacosamide PM review
`
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`
`
`
`FRED “WIND
`
`mu mce.‘ Appendix 6
`
`(C)
`
`Note: (A) is observed versus population predicted
`(B) is observed versus individual predicted
`(C) is weighted residual versus population predicted
`(D) is weighted residual versus time
`
`
`
`TJME (hours)
`
`(D)
`
`The population PK dataset was randomly split into two subsets and used for population
`PK model validation. The validation was preformed by re-analyzing overall dataset and
`the two subsets using the final model. The results showed that the population PK
`parameter estimates and the residual variability were comparable for both datasets and
`comparable with the results form analyzing the complete dataset with all subjects.
`
`5.3.1.1.6 CONCLUSIONS:
`
`LCM plasma concentrations were adequately described by a l-compartment
`model with first order absorption and first-order elimination. Overall, the mean
`PK parameter estimates for kc and V/f in healthy subjects of different age and
`gender were comparable with those determined in other Phase 1 trials (by non—
`compartmental PK analysis).
`
`Based on the low IIV of PK parameters of lacosamide (IIV=6.26% for V/f,
`IIV=l 3.1% for ke), it can be concluded that LCM plasma concentrations are
`highly predictable in the currently evaluated population of healthy subjects. As
`IIV of LCM plasma concentrations is a priori low, there is not much variability in
`LCM plasma concentrations that can be explained by possible covariates.
`According to the criteria specified for covariate selection, LBW and height were
`identified as covariates on V/f among the tested covariates (age, sex, body weight,
`height, BMI, LBW, CLcr, AP, GGT, AST, ALT, total bilirubin). No parameter
`was identified as covariate on ke.
`
`LBW and height as covariates on V/f reduced the IIV of V/f from 16.8% to 6.3%.
`The identification of LBW and height as covariates on V/f indicates that the most
`accurate prediction of V/f of subjects can be done based on LBW (and not based
`on body weight or other tested covariates) and height of the subjects. A greater
`LBW or height results in a higher V/f which implicates lower LCM plasma
`concentrations.
`‘
`
`The observed differences in the pharmacokinetics of LCM in trial SP640 are
`based on differences in LBW and height. The evaluated model did not identify
`
`

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`Lacosamide PM review
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`
`sex as a covariate. The impact of sex on the pharmacokinetics of LCM is
`integrated by inclusion of LBW and height, as male subjects show lager values for
`mean LBW and mean height compared to females.
`0 The pharmacokinetics of LCM after multiple administration of high dosages does
`not change compared to the dosages administered in other Phase 1 trials (eg.
`'
`SP620).
`
`o A very good prediction of individual LCM plasma concentration profiles is
`possible using the population PK model evaluated in the current analysis. The
`only parameters necessary for the individual prediction are LBW and height.
`
`APPEARS THIS WAY ‘
`ON ORIGINAL
`
`

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`Lacosamide PM review
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`
`Population Pharmacokinetics of Lacosamide in Healthy
`3.2.1.2
`Subjects with Different Age and Gender, Trial Number: SP- 620
`
`5.3.1.2.1 OBJECTIVES:
`
`The objectives of this population PK analysis were:
`1. Characterization of the population pharmacokinetics of LCM in young healthy
`male and elderly healthy male and female subjects, i.e., the estimation of
`population PK parameters for volume of distribution (V/f), rate constant of
`absorption (ka) and rate constant of elimination (kc). These population PK
`parameter estimates characterize the pharmacokinetic (PK) behavior of LCM
`within the population of healthy subjects in SP620.
`Identification of important sources of inter-individual variability (relevant
`demographic or pathophysiologic subject-specific factors, ‘covariates’) of the PK
`parameters V/f, kc and ka within the trial population.
`3. Estimation of the magnitude of residual variability that cannot be described by the
`population PK model in these subjects.
`
`2.
`
`Based on these results, important information about the differences in the
`pharmacokinetics of LCM in young healthy male subjects compared to elderly male and
`female subjects should be gained.
`
`5.3.1.2.2 CLINICAL STUDY OVERVIEW:
`
`The population PK analysis was based on the PK observations from trial SP620.
`
`SP620 was a Phase 1, single-center, double-blind, placebo-controlled, parallel group trial
`to investigate the pharmacokinetics of unchanged LCM and its metabolite SPM 12809 in
`plasma and urine in healthy elderly male and female subjects in comparison to young
`healthy male subjects and to evaluate gender difference in the pharmacokinetics.
`12 subjects of each age and gender group were randomized to receive single doses of
`100mg lacosamide on Days 1 and 8 and 100mg lacosamide twice daily on Days 4 to 7. In
`total, 36 subjects were treated with lacosamide and 14 subjects received placebo in
`SP620. Out of the 36 subjects, 35 completed the trial as planned. Plasma samples were
`taken at the following time points: 0 (pre-dose), 0.5, 1, 1.5, 2, 3, 4, 6, 8, 12, 24, 36, 48,
`72, 96, 120, 132, 144, and 156 hours following the first dose, pre-dose on Day 8 and 0.5,
`1, 1.5, 2, 3, 4, 6, 8, 12, 24, 36, 48 and 72 hours following the last dose on morning ofDay
`8. The sponsor performed non-compartmental analysis to obtain pharmacokinetic
`parameters. In the mean time, they performed population PK analysis by using the same
`PK data.
`
`5.3.1.2.3 DATA FOR ANALYSIS:
`
`Analysis of plasma samples was performed with a validated high performance liquid
`chromatography (HPLC) electrospray tandem mass spectrometry (MS/MS) method with
`the lower limit of quantification (LOQ) of 0.1 ug/mL. All plasma concentrations were
`
`

`

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`included for the population PK analysis. In total, 1169 records from 36 subjects were
`included (with a median of 33 samples per subject).
`
`The following parameters were used in the evaluation of possible covariates: Age, Sex
`(Sex=0 for males, Sex=1 for females), Height (HGT), Body weight (BW), Body surface
`area (BSA), Body mass index (BMI), Fat free mass (FFM), Creatinine clearance (CLcr).
`
`Where body surface area, FFM, and CLcr were calculated by using the following
`equations,
`
`354mg} = Warsaw HGTO'm[cmlx'i’lfié
`10000
`
`_ 9270x331kg]
`.
`.
`EFMQMIQDI’ICE] _ 653:9 + 215 x BM;
`
`_ gatowwlkg]
`y
`,
`_
`,_
`FEngmageflkg] _ 83739 +24% BM!
`
`CL [ML 5min] = Cr'gatinmehmfiimgf1.511% FafztmemeL}
`‘ CR:
`I
`J
`Creatiirmemm {mgf (Eli-11440
`
`5.3.1.2.4 METHODS:
`
`A one—compartment model with first—order absorption and firs-order elimination
`(ADVANZ) was used (chosen from prior knowledge) for the population PK evaluation of
`LCM by using first order method (F0) in NONMEM Version IV (NONMEM Project
`Group, University of California, San Francisco, US)
`
`Model selection was based on a global measure of goodness-of—fit of a model, the
`objective function (OBF) in NONMEM (= - 2 times the log of the likelihood of the data)
`was used. In addition, the goodness—of-flt of the different population models for LCM
`plasma concentrations was assessed by visual inspection of the following diagnostic
`plots:
`0 Observed concentrations vs. individual predicted concentrations (DV vs. IPRE)
`Observed concentrations vs. predicted concentrations (DV vs. PRED)
`Weighted residuals vs. predicted concentrations (WRES vs. PRED)
`Residuals vs. predicted concentrations (RES vs. PRED)
`Residuals vs. time (RES vs. time)
`Predicted concentrations and measured concentrations vs. time (PRED/DV vs.
`time)
`o Weighted residuals vs. time (WRES vs. time)
`0
`Individual predicted concentrations and measured concentrations vs. time
`(IPRE/DV vs. time)
`The following criteria were used as additional criteria:
`0 Reduction of inter- and/or intra—individual (= residual) variability
`0 Reduction of the standard errors with respect to parameter estimates
`
`

`

`Lacosamide PM review
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`p. 28/2
`
`0 Analysis of residuals (random and uniform scatter around zero, no time
`dependency)
`The criteria for accepting NONMEM model estimation were the following:
`o A “suCCessful minimization” statement by the NONMEM program
`0 Number of significant digits 2 3; if the number of significant digits is <3, reasons
`for acceptance of the NONMEM run are given.
`‘
`. Estimates of THETA not close to boundary
`
`Base model evaluation was mainly focus on the selection of residual error model
`(additive error model, proportional error model, and combined error model) and the inter-
`individual random effect (normally distributed or log-normal distributed).
`
`Full model was developed to identify possible covariates. The full model was selected by
`using forward inclusion and backward elimination with the following steps:
`‘ o Graphical evaluation of the correlation between individual parameter estimates
`for ke, Ka and V/f from the base model and potential covariates.
`0 After the graphical evaluation of the parameter-covariate relationships, each
`covariate was tested on each of the model parameters ke, ka and V/f by adding 1
`covariate at a time (and removing it) and recording the resulting NONMEM OBF.
`0 Each of the potential covariates, starting with the “most significant” covariate
`(=largest OBF difference), was added to the model (“forward inclusion”). If the
`addition of a potential covariate caused a >3.841-point—decrease of the OBF
`(p<0.05, likelihood ratio test), the covariate was considered as a potentially
`significant covariate and was added to the model; otherwise, the covariate was
`dropped from the model. This resulted1n building of the “full” model by
`including all potentially significant covariates.
`In the next step, each potentially significant covariate was removed from the full
`model individually to determine if a model with fewer parameters would describe
`the data (“backward stepwise elimination”). If the removal of a potentially
`significant covariate caused an increase in OBF of at least 7.88 points (p<0.005,
`likelihood ratio test), the covariate was retained in the “final” model; otherwise,
`the covariate was dropped from the model. In the last step, the residual error
`model was tested again.
`
`0
`
`After the base model and final model were established, no further model validation was
`performed by the sponsor.
`
`5.3.1.2.5 RESULTS:
`
`The structure model for the final base model was one—compartment model with first-order
`absorption and first-order elimination, including log-normally distributed inter-individual
`variability on Ka, Ke, and V/f. The residual was described as the combined error model
`with a proportional and an additive component. The model parameter estimates were
`summarized in Table 4 and the major goodness-of—fit plots were shown in Figure 7.
`
`

`

`Lacosamide PM review
`
`p. 29/2
`
`Table 4 Lacosamide Base Population PK Model Parameter Estimates Derived from
`Trial SP620
`.
`
`Parameters m Relative Standard Error [%]
`Ka [1/hr]
`3.76
`14.3
`
`Ke [1/hr]
`
`V/f [L]
`
`IN on Ka [%]
`
`”V on Ke [%]
`
`”V on V/f [%]
`
`Proportional Residual
`Error[%]
`Additive Residual Error
`
`0.0451
`
`39.6
`
`112
`
`19.2
`
`21.4
`
`7.91
`
`[u/mL]
`
`0.0639
`
`4.12
`
`3.56
`
`23.5
`
`27.1
`
`22.7
`
`10.8
`
`33.1
`
`Figure 7 Goodness-of—fit Plots for Lacosamide Base Population PK Model Derived
`from Trial SP620
`
`(A)
`
`(B)
`
`.
`3
`.
`3
`
`w
`
`15c-
`
`mama)
`
`. 4
`
`. .
`
`5
`
`v
`:Miitafi
`2o. «:fimm.
`1i
`1 - 2 ~'
`"
`‘8' in.
`2
`:_ g-g, :
`
`~
`
`-
`
`.
`
`2 ix:
`3*!25
`are?“ , .gwwwwwwwww
`1
`Q f
`a
`' :
`3
`
`4i
`flaxamnawn
`
`fiRiDEWW
`
`
`
`:1.
`
`_
`3a;
`
`
`
`
`
`Adogamassediseg
`
`(C)
`Note: (A) is observed versus population predicted
`(B) is observed versus individual predicted
`(C) is weighted residual versus population predicted
`
`(D)
`
`

`

`Lacosamide PM review
`
`p. 30/2
`
`(D) is weighted residual versus time
`
`The final model was selected from the base model chosen with the same inter-individual
`variability and residual error structure. The covariate effect and parameter estimates were
`summarized in Table 5. Goodness-of-fit plots were shown in Figure 8.
`
`Table 5 Lacosamide Final Population PK Model Parameter Estimates Derived from
`Trial SP620
`
`Parameters m RSE*[%1
`Ka [1/hr]
`Ka = 01 + 07xFFM
`not applicable
`01
`2.93 x10 '6
`not applicable
`07
`0.0737
`30.3
`
`'
`
`Ke = 03 + 05xCLcr + 06x(31-BMI)
`0.0225
`
`
`
`
`
`
`
`not applicable
`21.1
`
`30.3
`
`31.1
`
`not applicable
`31.2
`
`8.97
`
`25.1
`18.8
`
`25.4
`
`8.08
`
`34.9
`
`Ke [1/hr]
`03
`
`95
`
`06
`
`V/f [L]
`02
`
`04
`
`”V on Ka [%]
`IN on Ke [%]
`
`”V on V/f [%]
`
`Proportional
`Residual Error [%]
`Additive Residual
`
`Error [u-lmL]
`
`0.000193
`
`000123
`
`V/f = 02 + 04xFFM
`8.18
`
`0.612
`
`121
`13.7
`
`9.6
`
`8.01%
`
`0.054
`
`Note: *: RSE = Relative Standard Error
`
`Figure 8 Goodness-of—fit Plots for Lacosamide Final Population PK Model Derived
`from Trial SP-620
`
`/ / / /
`
`(A)
`
`(B)
`
`

`

`Lacosamide PM review
`
`,
`
`p. 31/2
`
` .
`
`yuwzxsmasou
`12:30am:
`
`~,
`
`
`
`m:that»
`
`(D)
`
`u g,
`.
`
`‘ ‘ '
`
`,
`
`,
`
`PED‘M‘IHL!
`
`(C)
`
`..
`l
`i w .
`
`3!
`
`NOTE: (A) is observed versus population predicted
`(B) is observed versus individual predicted
`(C) is weighted residual versus population predicted
`(D) is weighted residual versus time
`
`5.3.1.2.6 CONCLUSIONS:
`
`LCM plasma concentrations were adequately described by a l-compartment model with
`first order absorption and first-order elimination. Overall, the mean PK parameter
`estimates for ka, ke and V/f in the target population of healthy subjects of different age
`and gender were comparable with those determined in other Phase 1 trials (by non~
`compartmental PK analysis).
`0 Based on the low IIV of PK parameters of lacosamide (IIV=9.6% for V/f,
`IIV=13.7% for ke), it can be concluded that LCM plasma concentrations are
`highly predictable in the currently evaluated population. As inter-individual
`variability of LCM plasma concentrations is a priori low, there is not much
`variability in LCM plasma concentrations that have to be-explained by possible
`covariates.
`
`0 According to the criteria specified for covariate selection, FFM was identified as
`covariate on V/f and ka among the tested covariates (age, sex, body weight, FFM,
`height, CLcr, BMI, BSA). CLcr and BMI were identified as covariates on ke.
`0 FFM as covariate explained approximately half of IIV of V/f (11.8% of 21.4%).
`The identification of FFM as covariate on V/f indicates that the most accurate
`
`prediction of V/f of subjects can be done based on FFM (and not based on body
`weight or other tested covariates) of the subjects. A greater FFM results in a
`higher V/f which implicates lower LCM plasma concentrations. Furthermore,
`FFM was found as a covariate on ka (significant improvement of objective
`function). However, FFM could not explain the IIV of ka more sufficiently.
`0 CLcr and BMI as covariates could only explain a small part (5.5%) of IIV of ke.
`However, the results show that elimination of LCM is influenced by CLcr and
`BMI as a prolonged t1/2 (=slower elimination) of LCM is observed with
`decreasing CLcr and increasing BMI of the subjects; A result of this will be higher
`LCM plasma concentrations in subjects with a decreased renal function and, also
`in subjects with higher BMI values.
`
`

`

`Lacosamide PM review
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`
`0 The observed differences in the pharmacokinetics of subjects with different age
`and sex in trial SP620 could be more adequately described by differences in FFM
`and CLcr.
`
`o A very good prediction of individual LCM plasma concentration profile is
`possible using the population PK model evaluated in the current analysis. The
`only parameters necessary for the individual prediction are body weight, height,
`age, sex and serum creatinine to calculate BMI, FFM and CLcr.
`
`APPEARS mas WAY
`on ORIGINAL
`
`

`

`Lacosamide PM review
`
`p.433/2
`
`3.2.2 Population PK analysis in patients with partial Seizure
`
`The sponsor submitted 2 population PK analyses reports for patients with partial seizure.
`
`Population Pharmacokinetics of Lacosamide in Subjects with
`3.2.2.1
`Partial Seizures with or without Secondary Generalization, Trial Number:
`SP755
`
`5.3.2.1.1 OBJECTIVES:
`
`,
`Objectives of the population PK analysis were the following:
`1. To describe population PK characteristics (i.e., typical mean PK parameters) of LCM
`and to characterize the inter— and intra—individual variability of the PK parameters of
`LCM in subjects with partial seizures with or without secondary generalization.
`2. To quantify the relationship between different subject—specific factors (i.e., possible
`covariates as age, body weight, creatinine clearance, concomitant antiepileptic drugs
`[AEDs]) and PK parameters (apparent volume of distribution [V/f], rate constant of
`elimination [ke]).
`
`5.3.2.1.2 CLINICAL STUDY OVERVIEW:
`
`The Population PK analyses were performed based on clinical data obtained from trial
`SP755 in patients with diabetic neuropathy. Detailed information with regard to the study
`design can be found in section 4.2.1.
`>
`
`A total of 584 subjects were screened for this trial. A total of 546 subjects were enrolled
`in the trial and comprised the ES; 32 subjects were screen failures and 6 subjects denoted
`as Baseline failures did not meet all Screening criteria and were excluded from the count
`of enrolled subjects. Of the 546 enrolled subjects, 485 were randomized. All of the 485
`randomized subjects received at least 1 dose of trial medication and comprise the Safety
`Set, 322 out of these 485 subjects were treated with LCM.
`
`Trial medication was administered orally twice daily (at approximately 12 hour intervals,
`once in the morning and once in the evening). Plasma concentrations of LCM and
`concomitant AEDs were obtained in order to investigate 1) the plasma concentration of
`LCM, 2) whether LCM has any effect on the steady—state plasma concentration of
`concomitant AEDs, and 3) the correlation between LCM plasma concentrations and
`efficacy. In addition, a population PK analysis of LCM plasma concentrations was
`performed.
`
`LCM plasma samples were obtained at the following visits:
`Baseline Phase
`
`- Visit 3 (Week 0, end of Baseline Phase)
`Titration Phase
`
`0 Visit 4 (Week 2, Titration Phase)
`° Visit 5 (Week 4, Titration Phase)
`
`

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`Lacosamide PM review
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`Maintenance Phase
`
`p. 34/2
`
`° Visit 6 (Week 8, Maintenance Phase)
`- Visit 8 (Week 16, Maintenance Phase)
`- Early Withdrawal Visit (For subjects who discontinue from the trial between Visit 3 but
`before completing Visit 8)
`'
`- Unscheduled Visit (At any time during the trial, eg, due to an adverse event requiring
`followup)
`.
`At Visit 3, plasma sampling was planned to be done prior to dosing of trial medication
`(blank sample) along with hematology samples. For the rest of the visits, plasma
`sampling was planned to be done at any time after dosing of trial medication on that day
`along with hematology samples.
`
`5.3.2.1.3 DATA FOR ANALYSIS:
`
`2676 concentration records from 491 subjects were obtained from the study.
`Concentrations from some of the subjects were excluded as described below.
`
`1. The following records were a priori not usable for population PK analysis and had to
`be excluded from the NONMEM analysis file because concentration records were <LOQ,
`samples could not be identified or details on the samples required for analysis were
`missing (e.g., missing sampling/dosing information):
`- Records <LOQ or unexpected concentration records relative to LOQ:
`— All 912 records from 163 placebo subjects were excluded; the majority of
`concentrations (782 out of 912 records) were below the LOQ. Of the 130 records >LOQ,
`125 records were in the Transition Phase of the trial, where the subjects were transitioned
`to LCM, and therefore can be considered as plausible; however, these records were also
`not included in the analysis. 5 out of 130 records >LOQ were between Visit 2 and Visit 8
`of the trial and were expected to be <LOQ.
`- 204 LOQ records from subjects in the verum group were excluded. 154 out of the 204
`records were at Visit 4 in the 200mg/day LCM group were no measurable LCM
`concentrations were expected due to the planned titration scheme. The rest of the records
`(50 records) were records in the 200mg/day and 400mg/day LCM group between Visit 4
`and Visit 8 or during Transition/Taper Phase and the majority of them were expected to
`have measurable LCM concentrations.
`
`- 327 predose (blank) records at Visit 3 were excluded. all were below the LOQ, with
`exception of 3 records in the 400mg/day LCM group that were >LOQ
`- 2 records >LOQ at Visit 4 were excluded in the 200mg/day LCM group, the subjects
`were expected to have measurable LCM concentrations not earlier than Visit 5.
`- Records with no reported concentration results:
`.
`For 43 records in the 200mg/day and 400mg/day LCM group, no concentration results
`were available and therefore,'no concentration records could be included in the analysis.
`- Concentration records excluded due to missing/inadequate documentation of
`sampling details:
`- 4 records with missing information on time alter administration were excluded.
`- 12 records with negative time after administration Were excluded.
`- 21 records with time after administration>24hours were excluded. Per documentation,
`the PK sampling was done >24h after administration of trial medication and the records
`
`

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`Lacosamide PM review
`
`p. 35/2
`
`were deleted because of the probability of errors in the recording of the dosing history or
`the time of sampling.
`- 10 records were excluded because the information on the latest dose prior to PK
`sampling was missing.
`— 97 records were excluded because the correct dosing data (with regard to individual
`morning and evening doses) was not determinable within 3 days prior to PK sampling.
`2. The following records were excluded based on their poor dosing compliance or
`because they were considered as outliers:
`.
`- 16 records of 7 subjects were excluded because of a documented compliance of <75%
`or because of other compliance violations. The records were deleted because of the
`probability of errors in the recording of the dosing history.
`- 20 records were excluded because the measured LCM concentration was less than 1/3
`
`or more than 3-fold higher compared to the expected LCM concentration based on the
`documented dose.
`
`Finally, 1008 concentration records from 292 subjects (out of 322 subjects randomized
`and treated with LCM) were used for the population PK analysis and were part of the
`NONMEM analysis file. This corresponds to a mean of approximately 3.5 concentration
`records per subject.
`
`Following variables were included in the analyses for the selection of covariate effect:
`Age, Sex (Sex=0 for males, Sex=1 for females), Body weight, Height, Body mass index
`(BMI), Lean body weight (LBW), Creatinine clearance (CLcr), Aspartate
`aminotransferase (AST), Alanine aminotransferase (ALT), Gamma-glutamyltransferase
`(GGT), Alkaline phosphatase (ALK), Total bilirubin.
`
`Where CLcr was estimated based on Cockcroft-Gault formula. BMI and LBW were
`
`calculated by using the following formula respectively.
`
`BMI =
`
`30:23} weighfikg }
`.
`(Heighten)?
`
`LBW (kg) in males = 1.1901 - weigfizfikg) — 0.8128- BM? — wefgfzrfiég)
`
`LBW (kg) in fiemai‘es ‘= 1.0? ~ x-Veig11t(§cg)— 9.0148 . 3:111 - weigfirfirg)
`
`Concomitant AEDs and AED combinations were also included as part of covariate
`analyses:
`- conAED No. 1: Carbamazepine alone
`- conAED No. 2: Carbamazepine + topiramate
`- conAED No. 3: Carbamazepine + lamotrigine
`- conAED No. 4: Carbamazepine + valproate
`- conAED No. 5: Oxcarbazepine alone
`- conAED No. 6: Carbamazepine + levetiracetam
`- conAED No. 7: Valproate + topiramate
`- conAED No. 8: Valproate + lamotrigine
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`- conAED No. 9: Carbamazepine alone or in combination with lamotrigine or
`levetiracetam
`
`- conAED No. 10: Oxcarbazepine alone or in combination with 1 or 2 other AEDsl
`- conAED No. 11: Carbamazepine alone or in combinatiOn with 1 or 2 other AEDsl
`- conAED No. 12: Lamotrigine alone or in combination with 1 or 2 other AEDsl
`- conAED No. 13: Levetiracetam alone or in combination with 1 or 2 other AEDsl
`- conAED No. 14: Phenobarbital alone or in combination with 1 or 2 other AEDsl
`
`- conAED No. 15: Phenytoin alone alone or in combination with 1 or 2 other AEDsl
`- conAED No. 16: Topiramate alone or in combination with 1 or 2 other AEDsl
`- conAED No. 17: Valproate alone or in combination with 1 or 2 other AEDsl
`
`1: “1 or 2 other AEDs” includes carbamazepine, topiramate, lamotrigine, valproate, levetiracetam,
`clonazepam, oxcarbazepine, phenobarbital, phenytoin, gabapentin
`
`5.3.2.1.4 METHODS:
`
`As a global measure of the goodness-of—fit of a model, the OBF in NONMEM (i.e., - 2
`times the log of the likelihood of the data) was used. In addition, the goodness-of—flt of
`the different population models for LCM plasma concentrations was assessed by visual
`inspection of the following diagnostic plots:
`- Individual predicted concentrations vs. observed concentrations (IPRE vs. DV)
`- Predicted concentrations vs. observed concentrations (PRED vs. DV)
`- Weighted residuals vs. predicted concentrations (WRES vs. PRED)
`- Residuals vs. predicted concentrations (RES vs. PRED)
`- Residuals vs. time (RES vs. time)
`- Predicted concentrations and observed concentrations vs. time (PRED/DV vs. time)
`- Weighted residuals vs. time (WRES vs. time)
`- Individual predicted concentrations and measured concentrations vs. time (PRED/DV
`vs. time)
`The following criteria were used as additional criteria:
`- Reduction of inter— and/or intra-individual
`
`- Reduction of the standard errors with respect to parameter estimates
`- Analysis of residuals (random and uniform scatter around zero, no time dependency)
`The criteria for accepting NONMEM model estimation were the following:
`- A “successful minimization” statement by the NONMEM program
`- Number of significant digits 23; if the number of significant digits was <3, reasons for
`acceptance of the NONMEM run were given.
`- Estimates of THETA (the fixed effect-parameter in NONMEM) not close to boundary
`
`APPEARS THIS WAY
`ON ORIGENAL
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`5.3.2.1.5 RESULTS:
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`p. 37/2
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`‘ The structure model for the final base model was one-compartment model with first—order
`absorption and first—order elimination, including log—normally distributed inter-individual
`variability on Ka, Ke, and V/f. The residual was described as the combined error model
`with a proportional and an additive component. The major pharmacokinetic parameters
`were summarized in Table 6, with the goodness-of-fit plots were shown in Figure 9.
`
`Table 6 Lacosamide Base Population PK Model Parameter Estimates Derived from
`Trial SP755
`
`w:
`
`
`
`R339}0}: percenE relatiLe atandmfi en's: affix 55131131338 respective Lariance estimate
`for 11V: KR”?fitha—indit‘iéuai Lafiabiiity111 percent: :1a=nm applicable;
`:1 lgoffl#335314 couaapondstoatm 0519.411
`-
`Data source: Appendix 3
`
`Figure 9 Goodness-of—fit Plots for Lacosamide Base Population PK Model Derived
`from Trial SP755
`
`53(4)
`
`/ / //
`
`(A)
`
`(B)
`
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`Adogelqgssodiseg
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`,—s:{u.nchs
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`
`
` m:on
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`Boiled liae=linm REESE“?! (33de W501) and R1}
`Dara saute: Appaxdix 5
`
`Dotted linFIinear regression (including equation and R2).
`Data source: Appmdix 6
`
`(C)
`NOTE: (A) is observed versus population predicted
`(B) is observed versus individual predicted
`(C) is weighted residual versus population predicted
`(D) is weighted residual versus time
`
`(D)
`
`The final model was selected from the base model chosen with the same inter-individual
`
`variability and residual error structure. The covariate effect and parameter estimates were
`summarized in Table 7. Goodness-of—fit plots were shown in Figure 10.
`
`Table 7 Lacosamide Final Population PK Model Parameter Estimates Derived from
`Trial SP755
`
`
`
`
`
`
`
`
`
`— W
`
`was BW— 54 ”
`—___—
`
`
`
`
`
`
`
`RSE(%)=the. percent melative standard war of the estimme twp variance estimate f0: IIV;
`IR‘(‘?n)=1nta-mdividnai variabilityin per-cent; Bl-=typicai mine ofka; BS—t'ypical mine of
`it. without efi‘ect chox’ariate; 62=typical value of ”W?Without effect ofcea-ariate:
`84:51:29: ofthe efi‘ect of mmfiste cmED No. 11 031 fig; 95=siope Bf'the efi‘ect of
`cosmiate LBVJ an “if; fl.a.= not applicable; 1332512311 body weight; canal-ED No. 11
`=coaémims£ered cm’bsmazepine alone or in combination with 1 or ‘2 other AEDS;
`Data sewers: Appendix 3,, Appaldix ?
`
`
`
`
`
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`Figure 10 Goodness-of—fit'Plots for LacosamideFinal Population PK Model Derived
`from Trial SP775
`
`M4)
`
` Pmmy
`
`“‘5In}
`
`Dam-(l lhefiinczzxeptssicn (including «mm and 96).
`Du: sauce: Appendix 6
`
`Dotted erepssiau (Excluding eanjon and 35.
`Dm some: Appendix 5
`
`(C)
`
`(D)
`
`NOTE: (A) is observed versus population predicted
`(B) is observed versus individual predicted
`(C) is weighted residual versus population predicted
`(D) is weighted residual versus time
`
`5.3.2.1.6 CONCLUSIONS:
`
`- LCM plasma concentrations were adequately described by a l-compartment
`model with first -order absorption and first-order elimination.
`
`0 Overall, the mean population PK parameter estimates for ke and V/f in the target
`population of subjects with partial seizures with and without secondary
`generalization were comparable with those determined in Phase 1 trials in healthy
`subjects. Inter-individual variability (IIV) of V/f in the target population (6.6%)
`was determined to be lower compared to the IIV (measured as CV) observed in
`healthy subjects in Phase 1 trials (20%). The IIV of the rate constant of
`elimination (ke) was comparable to the CV observed in Phase 1 trials (IIV of
`19.1% in the examined target population compared to CV of 20% in healthy
`subjects).
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`0 Overall,,based on the observed low IIV of PK parameters of LCM (IIV=6.6% for
`V/f, IIV=19.1% for kc), it can be concluded that LCM plasma concentrations are
`predictable with good precision in the currently evaluated target pOpulation.
`0 According to the criteria specified for covariate selection, lean body weight
`(LBW) was identified as covariate on V/f and coadministration of carbamazepine
`alone or in combination with l or 2 other AEDs (topiramate, lamotrigine,
`valproate, levetiracetam, clonazepam, oxcarbazepine, phenobarbital, phenytoin,
`gabapentin) was identified as covariate on ke.
`0 Based on the final model results, the major determinant for V/f was the subjects’
`LBW. This means that V/f and therefore LCM plasma concentrations can be best
`predicted based on subjects’ LBW. An increase in the fat-free mass by 20% in a
`subject results in an increase in V/f of 10% and therefore in 10% lower LCM
`plasma concentrations.
`1
`0 Based on the final model results, elimination of LCM (characterized by rate
`constant of elimination, ke) is influenced by the coadministration of
`carbamazepine alone or in combination with l or 2 other AEDs. In the presence
`of carbamazepine (alone or in combination with l or 2 other AEDs), elimination
`of LCM was observed to be-faster in the examined population (tl/2 of 16.8h
`compared to t1/2 of 20.8h, ie, ~25%) resulting in approximately 15% lower LCM
`concentrations (Cmax,ss) at steady state. Therefore, based on the final model
`results, it can not be excluded that lower LCM plasma concentrations are
`observed under coadministration with carbamazepine alone or in combination
`with l or 2 other AEDs (topiramate, lamotrigine, valproate, levetiracetam,
`‘
`clonazepam, oxcarbazepine, phenobarbital, phenytoin, gabapentin).
`0 None of the other tested covariates (age, sex, body weight, height, CLcr, BMI,
`AST, ALT, GGT, ALK, total bilirubin, were identified as additional covariates on
`
`V/f or ke based on the specified criteria for covariate testing.
`0 None of the other tested concomitant AEDs or AED combinations (including
`topiramate, lamotrigine, valproate, levetiracetam, oxcarbazepine, phenobarbital,
`and phenytoin) were identfied as covariates on LCM kinetics, ie, these AEDs or
`AED combinations provided no clear signal of an influence on LCM kinetics in
`the current evaluation although an influence Can not be excluded.
`
`APPEARS THlS WAY
`0N ORIGINAL
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`Population Pharmacokinetics of Lacosamide in Subjects with
`3.2.2.2
`Partial Seizures with or without Secondary Generaliz