how modeling & simulation can optimize a clinical trial

HOW MODELING & SIMULATION CAN OPTIMIZE A

CLINICAL TRIAL

Ruben Faelens, SGS Exprimo, Scientist - Modeling & Simulation

2 © SGS SA 2014 ALL RIGHTS RESERVED

MODELING & SIMULATION

PDUFDA goals for 2018 - 2022:

3. To facilitate the development and application of

exposure-based, biological, and statistical models

derived from preclinical and clinical data sources

4. To facilitate the advancement and use of complex

adaptive, Bayesian, and other novel clinical trial designs

Source: PDUFA REAUTHORIZATION PERFORMANCE GOALS AND

PROCEDURES FISCAL YEARS 2018 THROUGH 2022


POPULATION PK/PD M&S

THROUGHOUT DRUG DEVELOPMENT

Objectives of M&S should focus on the next phase(s)

of development to support decisions that need to be made

Pre-clinical Discovery Phase I Phase IIb Phase IIa Phase III

Confirm Explore Explore Confirm Confirm Explore

Candidate

Selection Drug Evaluation Global Development

(Semi-)mechanistic PK-PD

Descriptive Drug & Disease


1. Translate the animal data to human

2. Define the first dose to be administered in human

Non-effective dose

3. Define the dose escalation strategy

Range of doses to be studied and interval between the dose

levels

4. Define the stopping rules

When PK is sufficiently understood

When dose covers a multiple of the expected efficacious

dose (single or multiple)

HOW PK-PD MODELING CAN

HELP IN FIRST-IN-MAN STUDY?


A REAL EXAMPLE

STEP 1: ANIMAL DATA

First data received from a multiple

dose study in animals indicated

linear kinetics

However, data from single dose

studies with lower doses exhibited

non-linear kinetics probably due to

target mediated drug disposition

Production rate

Elimination rate

mAb

Elimination rate

Target

Production rate

Elimination rate

mAb

Elimination rate

Target

TMDD

Elimination rate


TARGET MEDIATED DRUG

DISPOSITION (TMDD)

Target

Production rate

Elimination rate

mAb

Elimination rate

TMDD

Log(F

ree

mA

b)

Time

Log(F

ree

trag

et)

Time

Elimination rate

mAb - target

Time

Log(m

AB

- t

arget

)

Target

+

mAb-target

Production rate

Elimination rate

mAb

Elimination rate

Target

TMDD

Elimination rate


ANIMAL DATA WERE MODELLED

AND EXTRAPOLATED TO HUMAN

Animal data were analysed

using the appropriate TMDD

model

Results were scaled to

human and simulations were

performed taking into

account the uncertainty

about the magnitude of

TMDD

Linear PK

Saturable PK


A REAL EXAMPLE

STEP 2: SECOND DOSE IN HUMAN

The observations are

compared with the prediction

range

The observations help to

reduce the uncertainty on the

possible mechanisms

TMDD appears to be present.

However, some uncertainty

remains and data can still be

described by two possible

competitive mechanisms

Original model is fine-tuned

testing these two mechanistic

hypotheses


NEXT DOSE TO BE GIVEN?

VMAX hypothesis

KM hypothesis

Scenarios are simulated with

different possible doses under

different possible hypotheses

These simulations help the

team to determine which dose

has to be given next


A REAL EXAMPLE

STEP 2: THIRD DOSE IN HUMAN

Again, the

observations are

compared to the

predictions based on

the two possible

hypothesis

Data of the second

and third cohorts are

modelled together

using TMDD

assuming quasi

steady state. Run is

successful and fits

acceptable

mA

b c

once

ntr

ation

Time (day)


NEXT DOSE TO BE GIVEN?

Simulations are performed

with the TMDD QSS model to

predict the concentration-time

profiles for different doses

These simulations again help

the team to determine which

dose has to be given next


Before the first

administration, PK-PD

predictions are made

and a first dose with

marginal PD effect is

selected

During the FIM, PD is

also modelled and

simulations are

performed to predict

effect-time profiles

The combination of both

PK and PD increased

the confidence of the

team in choosing the

next doses

WHAT ABOUT PD ?

Ta

rge

t (%

inh

ibitio

n)


A REAL EXAMPLE

STEP 3: STOPPING RULES

In absence of tolerability and safety

issue, PK-PD can be help

determining the highest dose to be

tested

PK and PD Monte Carlo

simulations are performed based

on the last fine-tuned model After single dose After multiple doses

These simulations together with the

target product profile are use to

define the stopping rule and to

make sure that the drug has a

chance to reach expectations


1. Translate the animal data to human

2. Define the first dose to be administered in human

Non-effective dose

3. Define the dose escalation strategy

Range of doses to be studied and interval between the dose

levels

4. Define the stopping rules

When PK is sufficiently understood

When dose covers a multiple of the expected efficacious

dose (single or multiple)

HOW PK-PD MODELING CAN

HELP IN FIRST-IN-MAN STUDY?


An integrated PK/PD modelling and simulation approach is key

to make informed decisions in first-in-man study.

To ensure the value of PK/PD modelling in FIM study, it needs

to be organised operationally.

SGS has the experience and the flexibility in providing such a

service, as both CRO and PK/PD modelling group.

SGS Exprimo has extensive experience in using modelling and

simulation to aid our clients answer the questions they face in

their drug development process and regulatory interactions.

The analyses we do are highly suitable for submission to regulatory

authorities.

We have consistently received excellent feedback from regulatory

authorities about the quality and comprehensibility of our reports.

OVERALL CONCLUSIONS

22 SGS BIOPHARMA DAY – OCTOBER 25, 2016

Life Science Services Ruben Faelens

Scientist - Modeling & Simulation

SGS Exprimo NV Phone:: + 32 (0) 494 06 72 59

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

mailto:[email protected]

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how modeling & simulation can optimize a clinical trial

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