clinical trial simulation training with simulo 20161124

Clinical Trial Simulationswith Simulo

Ruben Faelens, Quentin Leirens, Emilie Hénin, Marc-Antoine Fabre

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

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)

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

Clinical Trial Simulation

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https://www.youtube.com/watch?v=dW4fek6plP4

Clinical Trial Simulation

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Risk management tool

Pick the most effective design

Models + design elements = prediction

Cost-effective

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

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

Drug development

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Simulations support

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?

…

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

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

Focus on Sunitibib PK

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Dose

Elimination

KA

CL/VC

Q/VC

Q/VP

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.

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?

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

Open a study

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Select ‘PK_sunitinib’ and click ok

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

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

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?

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)

Any questions so far?

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Any questions so far?

My own questions

• THETA?

• Parameter uncertainty

• ETA?

• Residual Error?

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

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

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

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, …

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!

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 ?)

Life Science Services Ruben Faelens

Scientist - Modeling & Simulation

SGS Exprimo NV

Generaal De Wittelaan 19A Bus 5

B-2800 Mechelen, E-mail : ruben.faelens@sgs.com

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