nonlinear mechanistic models for improving the treatment ... · mechanistic pharmacokinetic models...
TRANSCRIPT
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Nonlinear mechanistic models for
improving the treatment of malaria:
Balancing model complexity
with statistical rigour
A/Prof Julie Simpson
Centre for MEGA Epidemiology
Melbourne School of Population and Global Health
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Overview of presentation
2
• Clinical research question
• Mechanistic pharmacokinetic models
– Structural models
– Statistical modelling
– Design of future pharmacokinetic studies
• Mechanistic within-host pharmacokinetic-• Mechanistic within-host pharmacokinetic-
pharmacodynamic models for malaria
– Parasite age-structured model
– Statistical and data measurement challenges
• Translation to policy
• Future work
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Clinical research question: Malaria current burden
3
216 million cases of malaria in 2010 - 655,000 deaths
World Malaria Report 2011; WHO
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Clinical research question: Malaria control
4
WHO recommendations
• Long lasting insecticidal nets
• Effective treatment
• Indoor residual spraying of insecticide
World Malaria Report 2011; WHO
• Indoor residual spraying of insecticide
• Intermittent preventive treatment in pregnancy
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Clinical research question: Malaria biology
5
The Malaria Life Cycle by Drew Berry –The Walter & Eliza Hall Institute of Medical Research
http://www.wehi.edu.au/education/wehitv/malaria_lifecycle_part_1_human_host/
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Clinical research question: Malaria biology
6
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Clinical research question: Treatment of malaria
7
WHO recommends as first line treatment for uncomplicated
and severe falciparum malaria
Artemisinin-based combination therapy (ACT)
Artemisinin derivative Artemisinin derivative
+ partner drug(s)
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Clinical research question: Treatment of malaria
8
WHO treatment guidelines 2010 – Uncomplicated malaria
Artesunate (ARS) &
Mefloquine (MQ)
Artemether (ART) &
Lumefantrine (LF)
Dihydroartemisinin (DHA) &
Piperaquine (PQ)
Dosing
regimen
(WHO)
ARS 4.0 mg/kg &
MQ 8.3 mg/kg
@ 0, 24, 48 h
ART 80.0 mg/kg &
LF 480.0 mg/kg
@ 0, 8, 24, 36, 48 & 60 h
DHA 4.0 mg/kg &
PQ 18.0 mg/kg
@ 0, 24 & 48 h
Pregnant women
1st trimester – Quinine + clindamycin
2nd & 3rd trimesters - ACT
Children
ACT – same weight adjusted dose recommend for infants, children &
adults
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Clinical research question: Treatment of malaria
9
WHO treatment guidelines 2010 –Severe malaria
(revision 1 – for children)
Pregnant women
IV or IM Artesunate
Dosing regimen (WHO) 2.4 mg/kg @ 0, 12, 24, 48, 72 h followed by oral ACT
Pregnant women
1st trimester – Both artesunate or quinine may be chosen
2nd & 3rd trimesters - Artesunate
Children
IV or IM artesunate – same weight adjusted dose recommend for infants,
children & adults
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Clinical research question: Treatment of malaria
10
Dondorp A et al. N Eng J Med 2009
Fairhurst RM et al. Am J Trop Med 2012
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Clinical research question: Treatment of malaria
11
• Are the current WHO recommended dosing regimens of each
anti-malarial optimal for all patients with malaria?
• With the emergence of resistance to the artemisinin derivatives,
which anti-malarial combination therapies and alternative
dosing regimens should be evaluated in clinical trials? dosing regimens should be evaluated in clinical trials?
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Mechanistic pharmacokinetic models
• Describes how the drug concentration changes over
time using physiological parameters...
• Study design – repeated measures studies
200
00
Adults - Bangkok-Thailand
12
11
01
00
100
02
00
00
DH
A c
on
ce
ntr
ation
nM
0 2 4 6 8 10 12Time hrs
05
00
10
00
150
0M
efloq
uin
e c
once
ntr
atio
n n
g/m
l
0 10 20 30Time (days)
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Mechanistic pharmacokinetic models13
Gut
compartment
Central
compartment
ka ke
0
0.5
1
1.5
2
2.5
3
3.5
0 5 10 15 20 25 30 35
Time (hours)
Co
nc
en
trati
on
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Mechanistic pharmacokinetic models – data collected
Anti-malarial population pharmacokinetic studies
• Often sparse & unbalanced designs for malaria
patients (especially pregnant women and children)
For example:-For example:-
14
Patient population Sampling times for artesunate
Adults 0, 0.167, 0.25, 0.5, 0.75, 1, 1.5, 2, 4, 8 hrs
Children
Group 1
Group 2
Group 3
0, 0.25, 4 hrs
0, 0.5, 2 hrs
0, 0.25, 1 hr
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Mechanistic pharmacokinetic models – statistical modelling
Nonlinear mixed-effects modelling
Need to provide:-
1) Structural pharmacokinetic model
2) Initial values (or prior dsns) for each parameter2) Initial values (or prior dsns) for each parameter
3) Distribution of random effects (often use lognormal dsn
for between-individual variability and combination of
proportional and additive error terms for residual error)
[Software packages used:- NONMEM, MONOLIX, PKBUGs]
15
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Mechanistic pharmacokinetic models – statistical modelling
Structural pharmacokinetic model
• Structural identifiability
– Is there a unique set of parameter values?
Anti-malarial – Artesunate
Gut
compartment
Central
compartment
16
02
00
40
06
00
800
100
0D
HA
Co
nce
ntr
atio
n (
ng
/mL
)
0 2 4 6 8 10 12Time
compartment compartment
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Mechanistic pharmacokinetic models – statistical modelling17
Initial values for each parameter0
10
20
30
Co
ncen
tra
tion
(m
g/L
)
0 7 14 21 28Time
1*Volume
2*Volume
0.5*Volume
01
02
03
0C
on
cen
tra
tion
(m
g/L
)
0 7 14 21 28Time
1*Clearance
2*Clearance
0.5*Clearance0
10
20
30
Co
ncen
tra
tion
(m
g/L
)
0 7 14 21 28Time
1*Absorption rate
2*Absorption rate
0.5*Absorption rate
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Mechanistic pharmacokinetic models – statistical modelling
• Deterministic identifiability
– Is the study design sufficient to determine (or
estimate precisely) the parameters of interest?
18
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Mechanistic pharmacokinetic models – statistical modelling
19Adjei GO et al. AAC 2008
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Design of population pharmacokinetic studies
1. How many patients should be included in the
study?
2. How many samples need to be collected for each
patient?
20
3. At what times should the samples be collected?
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Design of population pharmacokinetic studies
21Simpson JA et al. Malaria Journal 2009
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Design of population pharmacokinetic studies –
Optimal design theory
Data independent approach using the Population Fisher
information matrix (FIM), which is simply the sum of all
individual(i=1,...,N) FIMs :-
22
D represents the set of all individual designs (d1, d2,..., dN)
where d1=(ti1,ti2,...,tini)
A is the vector of population parameters (θ,Ω,σ)
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Design of population pharmacokinetic studies –
Optimal design theory
To find the optimal design, an optimisation algorithm is
used to compare the determinant of the PFIM for several
candidate designs:-
23
Fortunately, software has been developed to do the above
job efficiently.....
WinPOPT (or POPT; www.winpopt.com ) – requires Matlab
PFIM (www.pfim.biostat.fr ) – requires R
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Design of population pharmacokinetic studies –
Anti-malarials
Artesunate
24Jamsen K et al. Malaria Journal 2011 & 2012
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Mechanistic pharmacokinetic-
pharmacodynamic models
Mechanistic model that links the drug concentrations
to the effect (pharmacodynamic measure)
25
Gut
compartment
Central
compartment ka ke
Effect
compartment
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Mechanistic PK-PD models for falciparum malaria
Parasite-age structured model
26
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Mechanistic PK-PD models for falciparum malaria
Number of parasites (N) in patient k at a particular stage
(denoted by a = 1, 2, …, 48) at hourly time point t,
)()1(
)()1(
)()1(
47,48,
1,2,
48,1,
tNtN
tNtN
tNPMFtN
kk
kk
kk
=+
=+
×=+
M• PMF – parasite multiplication factor
27Saralamba S et al. PNAS 2011
t=2
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Mechanistic PK-PD models for falciparum malaria
Number of parasites (N) in patient k at a particular stage
(denoted by a = 1, 2, …, 48) at hourly time point t following
drug administration,
• s(t) =exp(-kdrug.t)
proportion of parasites that
survive an hourly interval exposure
to the antimalarial drug concentration)()()1(
)()()1(
)()()1(
1,1,2,
48,48,1,
tstNtN
tstNtN
tstNPMFtN
kkk
kkk
×=+
×=+
××=+
M
28Saralamba S et al. PNAS 2011
to the antimalarial drug concentration)()()1( 47,47,48, tstNtN
kkk×=+
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Mechanistic PK-PD models for falciparum malaria
kdrug – function, dependent on drug concentration and time
1
2
3
4
5
Kill
rate
consta
nt
29
0
Drug Concentration (C)
01
23
45
Kill
ra
te c
onsta
nt
0 7 14 21 28Time
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Mechanistic PK-PD models for falciparum malaria
Exploration of parameter space
30Zaloumis S, et. al. Malaria Journal 2012
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Mechanistic PK-PD models for falciparum malaria-
Exploration of parameter space
31Zaloumis S, et. al. Malaria Journal 2012
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Mechanistic PK-PD models for falciparum malaria
Exploration of parameter space
1) Simulate 100 drug concentration-time profiles for each anti-malarial
2) Simulate 100 parasite-time profiles dependent on a single set of the 6 pharmacodynamic parameters and each of the drug concentration profiles for a particular anti-malarial combination therapy
32Zaloumis S, et. al. Malaria Journal 2012
3) Calculate from the100 parasite-time profiles the typical measures of clinical trials:-
PCT – parasite clearance timeCure – parasite infection cured within 28 days of follow-up
4) Repeat steps 2 and 3 for 5000 sets of the pharmacodynamicparameters that are sampled using Latin Hypercube Sampling
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Mechanistic PK-PD models for falciparum malaria
Exploration of parameter space
33Zaloumis S, et. al. Malaria Journal 2012
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Mechanistic PK-PD models for falciparum malaria-
Exploration of parameter space
• Latin Hypercube Sampling..
34
kmax
PMF
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Mechanistic PK-PD models for falciparum malaria-
Exploration of parameter space
• Latin Hypercube Sampling..
35
kmax
PMF
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Mechanistic PK-PD models for falciparum malaria-
Exploration of parameter space
• Latin Hypercube Sampling..
36
kmax
PMF
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Mechanistic PK-PD models for falciparum malaria-
Exploration of parameter space
• Latin Hypercube Sampling..
37
kmax
PMF
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Mechanistic PK-PD models for falciparum malaria-
Exploration of parameter space
• Latin Hypercube Sampling..
38
kmax
PMF
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Mechanistic PK-PD models for falciparum malaria-
Exploration of parameter space
• Latin Hypercube Sampling..
39
kmax
PMF
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Mechanistic PK-PD models for falciparum malaria-
Exploration of parameter space
40Zaloumis S, et. al. Malaria Journal 2012
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Mechanistic PK-PD models for falciparum malaria
Exploration of parameter space
Key findings.....
• kmax, EC50 of the anti-malarials are the key parameters
that influence the outcome measure:- cure by day 28 &
to a lesser extent, parasite clearance times.
41Zaloumis S, et. al. Malaria Journal 2012
to a lesser extent, parasite clearance times.
• Current estimates of EC50 from in vitro (experimental)
data did not accord well with the expected clinical
outcomes.
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Mechanistic PK-PD models for falciparum malaria-
Statistical modelling
Challenges with measurement of parasite count data
42
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Mechanistic PK-PD models for falciparum malaria-
Statistical modelling
Challenges with measurement of parasite count data
50000
500000
Para
sita
em
ia /
mic
roL
Adult - Bangladesh
43
50
100
1000
Para
sita
em
ia /
mic
roL
0 12 24 36 48
Time hrs~ 108 parasites
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Mechanistic PK-PD models for falciparum malaria-
Statistical modelling
• Challenges with measurement of parasite count data
44
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Mechanistic PK-PD models for falciparum malaria-
Statistical modelling
Are all parameters (including the random
effects) structurally and deterministically
identifiabile?identifiabile?
45
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• Back to the clinical research question....
• What have we achieved so far?
46
Translation.....
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Translation to policy
47
Translation to policy – adopted by WHO
• Mefloquine - Recommend split dosing (Simpson JA et al CPT
1999 & AAC 2000)
• Lumefantrine - Co-administer with a fatty meal (Ezzet F et al.
2000)
Translation to policy – not yet in WHO guidelines
• Piperaquine - Higher doses suggested for young children
(Tarning J et al 2012)
• Intra-muscular artesunate - Higher doses suggested for young
children (Hendriksen ICE et al. 2013)
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Translation to policy
48
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Future work
49
Optimising dosing of severe malaria patients
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Future work – a collaborative approach
50
Principal Investigator Julie Simpson
Postdoc biostatistician Sophie Zaloumis
Karen Barnes
Arjen Dondorp
Melba Gomes
Tim Davis
Lyle Gurrin
CollaboratorsLyle Gurrin
Kris Jamsen
Peter Kremsner
Sanjeev Krishna
Richard Maude
James McCaw
Paul Newton
Piero Olliaro
Ric Price
Joel Tarning
Nick White
Funded by NHMRC Project Grant & ViCBiostat
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Future work – Optimising dosing of severe malaria patients
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Summary(1)
• Current malaria treatment relies heavily on artemisinin
derivatives.
• Clinical trials in Cambodia, Thailand and southern Myanmar
have reported delayed clearance of the parasites following
treatment of artesunate.
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treatment of artesunate.
• Mechanistic population PK-PD modelling allow us to rationalise
drug therapy, thereby, extending the life-span of current anti-
malarials,
BUT there are many challenges.....
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Summary(2)
BUT there are many challenges.....
1) Does the mechanistic PK-PD model capture all the biology?
2) Can all the parameters be estimated precisely within a
proper statistical framework? Model validation...
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proper statistical framework? Model validation...
3) Current microscopic methods for determining parasite
burden do not detect parasite burdens below 108 parasites
nor parasites aged 26-48 hrs..
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Epidemiology – empirical models....
• Most epidemiological studies assess relationships
between exposures and outcomes using empirical
models!
• We can learn from other areas, and think more about
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• We can learn from other areas, and think more about
the mechanisms at play....
Causal Diagrams are a good starting point...