Clinical Trial Simulation training with simulo 20161124
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Transcript of Clinical Trial Simulation training with simulo 20161124
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Clinical Trial Simulationswith Simulo
Ruben Faelens, Quentin Leirens, Emilie Hénin, Marc-Antoine Fabre
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About me
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Ruben Faelens
• Belgian, living in Leuven
• call me Ruben
Computer Scientist, graduated in 2010
Started in PK/PD modeling & simulation in 2012
Wrote Simulo, a Clinical Trial Simulation software
Clinical Trial Simulation expert
Working at SGS Exprimo
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We are SGS Exprimo
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Per Olsson Gisleskog Andreas Lindauer Nancy Smets Marc-Antoine Fabre Eric Snoeck(external)
Julia Winkler Bernardo de Miguel LilloIsabelle Delor
(external)
Koen JollingDaniel Röshammar
Quentin Leirens Erno van Schaick (external)
Ruben FaelensPhilippe Jacqmin(external)
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Who are we?
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• founded in 2002, part of SGS since 2012
• company registered in Belgium (Mechelen), home-based offices
• team of >10 experienced modellers, currently recruiting
• strong academic/industrial backgrounds in pharmacometrics, clinical pharmacology, statistics and engineering
• we help clients answering key questions throughout drug development
• >300 projects performed across a range of therapeutic areas – very well received by clients and regulatory authorities
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Clinical Trial Simulation
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https://www.youtube.com/watch?v=dW4fek6plP4
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Clinical Trial Simulation
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Risk management tool
Pick the most effective design
Models + design elements = prediction
Cost-effective
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Backup: introduction
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M&S: Modeling & Simulation
• Modeling: explain what we see
• Simulation: predict what will happen next
Why do we use M&S?
• They help answer questions
• They help support decisions
CTS: Clinical Trial Simulation
• Simulate a full clinical trial
• Drug Model, Protocol, Dose Adaptations, Dropout
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We want to optimize the clinical trial together with the development strategy to get the best treatment as an outcome
Background
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Dose Concentration EffectClinical
response
PK PD
What the body does to the drug
What the drug does to the body
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Drug development
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Simulations support
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What kind of questions can we address?
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What is the best dose and administration interval?
What is the best sampling schedule?
Which protocol design will we choose?
How many subjects do I enrol in the next phase study?
Which proportion of my population will be well treated?
What is the best population targeted by the drug?
Will you continue this drug development?
Can we look at another dosage form?
Having information on other doses, what is the mean effect of a 100mg dose after 2 weeks of treatment?
What is the probability of success in phase III?
…
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Limitations
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Explain everything
Give you the answer you want
Find an effect where there isn’t one
Provide one “true” answer
Make good studies unnecessary
Make a silk purse out of a sow’s ear
Make your decisions for you
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Simulo for quantitatively informed discussions/decisions
Time since study entry, year
Hip
pocam
pus v
olu
me
0.0 0.5 1.0 1.5 2.0 2.5 3.0
1000
2000
3000
4000
5000
6000
NLMCIAD
Hippocampal volumeversus time since study entry
Estimated time since disease onset, year
RH
PN
M
-4 -2 0 2 4 6 8 10
0.4
0.6
0.8
1.0
1.2
1.4
1.6 o NL
o MCI slowo MCI fasto AD
MalesFemales
Hippo. vol. norm. to NL value for sameage and head size versus DOT
model-based simulation of various potential experimental scenarios enables;
1) visualization and summary of overall results/conclusions 2) quantitatively informed discussions/decisions (internal & regulatory)3) optimized study designs, better investment-decisions, regulatory success
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Sunitinib: our example
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Sunitinib is a multi-targeted tyrosine kinase inhibitor used in the treatment of advanced renal cell carcinoma (RCC) and imatinib-resistant/intolerant gastrointestinal stromal tumors (GIST).
Sutent - Pfizer (2006)
Reference: Reza Khosravan et al. Population Pharmacokinetic/PharmacodynamicModeling of Sunitinib by Dosing Schedule in Patients with Advanced Renal Cell Carcinoma or Gastrointestinal Stromal Tumor. Clin Pharmacokinet(2016) 55:1251–1269
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Focus on Sunitibib PK
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Dose
Elimination
KA
CL/VC
Q/VC
Q/VP
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PK parameters
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PK parameters are taken from the publication. We don’t take into account any covariate effects or lag time.
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IIV vs. RE
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What do we need to know?
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What is the best dose and administration interval?
• Which dose gives a Cp of >0.01 mg/L at day 4 post-dose?
Which proportion of my population will be well treated?
What is the best sampling schedule?
How many subjects do I need?
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Translation in Simulo Drug Model
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Translation in Simulo Drug Model (2)
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Access to Simulo on web
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Then click Login to enter as a guest
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Open a study
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Select ‘PK_sunitinib’ and click ok
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When selecting a tab, 2 panels are displayed
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The left one enables to create, delete, move, and select elements
The right one enablesto edit a selectedelement
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Demo of Live Simulation View
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Interactively show how: - to set up a single dose of 50mg- to plot lines for 100 hours- How A0, A1 and A2 behave- to change the number of subjects- To deactivate variability
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A) Play with typical values
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Change THETA_VC, THETA_CL or THETA_KA
• What happens?
Experiment with different doses
• What dose would you recommend to reach a targetconcentration of 0.01 mg/L at day 4 ?
Double THETA_VC
• How do you adapt the dose to different Vc?
• When could this happen?
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B) Play with different levels of variability
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Plot the histogram of model parameter VC• Activate variability• What happens when you change THETA_VC ? (i.e. the population
parameter)• What happens when you change ETA_VC ? (i.e. the subject
variability)
Plot concentration in central compartment versus time.• How does each parameter influence the curve?
Let’s find the population-recommended dose• Keep the dose previously found• Use the default script as CUSTOM chart• What dose would you recommend to reach a target concentration
of 0.01 mg/L at day 4 ? We want to treat well at least 95% of ourpopulation.
Add the actual observed concentration to plot• What happens when you change EPS ? (i.e. the residual variability)
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Any questions so far?
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Any questions so far?
My own questions
• THETA?
• Parameter uncertainty
• ETA?
• Residual Error?
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Let’s run a proper clinical trial simulation
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AUC and CMax
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N median_auc q05_auc q95_auc median_cmax q05_cmax q95_cmax
1000 1.56 0.99 2.37 0.025 0.0089 0.048
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Changing the schedule
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What is the best schedule?
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Every blood sample costs…
• Collection
• Storage
• Bio-assay
Can you use 10 observations and still be accurate?
• median_AUC = 1.56
• Your design should get a value between +25% and -20%= [1.42, 1.74] Note: optimal design
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How many subjects?
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How many subjects?
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Every subject costs
• Screening visit
• Follow-up
• Remuneration fee
Why include more subjects?
• Residual Error vs. Inter-Individual Variability
• Standard Error of the Mean
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Extra info
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What is the recommended dosage of sunitinib ?
• For RCC/GIST: 50mg 28 days on q1d, then 2w off
• For pancreatic cancer: 37.5mg every day
Dose adaptation?
• Up to maximum tolerable dose
• Side effects: liver toxicity, cardiomyopathy, arrhythmia, cardiovascular, …
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How to ensure good data?
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It is 2021 and Sunitinib is off-patent. Let’s make a biosimilar!
Do a single trial with N=50!Who established PK bio-equivalence with the originator compound ?
• Median_AUC should be [1.42, 1.74]
• Q05_AUC should be [0.8, 1.25]
• Q95_AUC should be [1.99, 2.94]
11% trials failed
• Probability of success / study power
• Publication bias / meta-analysis
• Lucky phase 2
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11% is predicted to fail
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53% is predicted to fail!
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Key learning
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Clinical trial simulation is a risk management tool
• Allows to simulate different trial designs
• Calculate study power
• Optimize design, test robustness
But within limits
• Available data, how good is the model?
• Based on assumptions (does the compound work ?)
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Life Science Services Ruben Faelens
Scientist - Modeling & Simulation
SGS Exprimo NV
Generaal De Wittelaan 19A Bus 5
B-2800 Mechelen, E-mail : [email protected]
BELGIUM
Web : www.sgs.com/lifescience
THANK YOU FOR YOUR ATTENTION
+ 41 22 739 9548
+ 1 866 SGS 5003
+ 65 637 90 111
+ 33 1 53 78 18 79
+ 1 877 677 2667
+ 33 1 41 24 87 87