Adaptive Clinical Trials: Role of Modelling and Simulation

Adaptive Clinical Trials: Role of Modelling and Simulation

CLINICAL TRIAL SOLUTIONSSGS Life Science Services Biopharm Day Seminar – Antwerp, November 13, 2014

Christian Laveille, Pharm.D., senior consultant at SGS Exprimo

OUTLINE

� Why use model based drug development ?

� Motivation

� Definitions

� Statistical and PK/PD Analysis Plan

2SGS Life Science Services Biopharm Day Seminar – Antwerp, November 13, 2014

� Modelling and Simulation (M&S)

� Data Monitoring Committee (DMC)

� Examples

� Conclusions

WHY USE MODEL BASED DRUG DEVELOPMENT ?

� Predict efficacy and safety

• Doses and dosing intervals, treatment duration, special populations, performance vs. competitors,

inter-patient variability…

� Simulation to optimize designs of clinical trials

• Inclusion/exclusion criteria, treatments, endpoints,


• Inclusion/exclusion criteria, treatments, endpoints, analysis methods, quantification of likelihood of

success…

� Combine in-house and public knowledge and

to facilitate communication with team

members, management and regulatory

agencies

� To aid in the understanding of the mechanism

of action and build translational model

between pre-clinical and clinical

MOTIVATION OF UNDERSTANDING

DOSE-RESPONSE

� Poor understanding of efficacy and safety dose-response:

pervasive problem in drug development.

� Indicated by both Health Authorities (EMA, FDA) and

Industry as one of the root causes of late phase attrition

and post-approval problems – at the heart of industry’s

pipeline problem.


pipeline problem.

� Currently “Phase III view” of dose finding: focus on dose

selection out of fixed, generally small number of doses, via

pairwise hypothesis testing ⇒ inefficient and inaccurate.

The ED50 of the dose-responserelationship can be

well determinedbased on the right

…. But dose-responserelationship will be

poorly defined whenactual potency is

One option might be to increase the number of doses to

be protected against the uncertainty in

Adaptive design: use dose-response from modelling to

select 1st dose -> based on results

ADAPTIVE DOSE FINDING


based on the right

range of doses in a classical dose-finding trial

actual potency is

higher or lower.

the uncertainty in

drug potency

based on results

select the appropriate dose for 2nd and 3rd cohort

DEFINITIONS OF ADAPTIVE DESIGN

� From PhRMA White Paper (2006):By adaptive design we refer to a clinical study design that uses

accumulating data to decide how to modify aspects of the study as it

continues, without undermining the validity and integrity of the trial.

� From EMEA Reflection Paper (2007):A study design is called “adaptive” if statistical methodology allows the


A study design is called “adaptive” if statistical methodology allows the

modification of a design element (e.g. sample-size, randomization ratio,

number of treatment arms) at an interim analysis with full control of the

type I error.

� From FDA Guidance for Industry (2010):An adaptive design clinical study is defined as a study that includes a prospectively planned opportunity for modification of one or more

specified aspects of the study design and hypotheses based on analysis

of data (usually interim data) from subjects in the study.

STATISTICAL AND PK/PD ANALYSIS PLAN

� Analyses of the accumulating study data are performed at

prospectively planned time points within the study, can be

performed in a fully blinded manner or in an unblinded

manner, and can occur with or without formal statistical

hypothesis testing.

� Prospective SAP more important for trials based on adaptive


� Prospective SAP more important for trials based on adaptive

procedures and generally more detailed and complex.

� SAP should be available by the time the protocol is finalized.

� SAP should include:

• planned changes

• statistical and/or PK/PD methods to implement adaptation

• data analysis procedure for each stage of adaptation

� Need a priori understanding of, summarizing by models:

• Concentration-efficacy response model

• Dose (concentration) – toxicity relationship

� Based on Bayesian statistics borrowing strength from

previous or neighboring doses.

MODELLING AND SIMULATION


previous or neighboring doses.

� Concept of Clinical Trial Simulations

• Clinical trials simulation (CTS) helps minimize risks and guide decision making by quantifying and evaluating decisions in the

face of uncertainties.

• CTS helpful in comparing the performance characteristics across several competing designs under different scenarios

with taking into account the uncertainty on model parameters.

� Data Monitoring Committee needs to be independent

(IDMC), non-sponsor controlled to protect study integrity.

� Responsible for review of interim analysis of unblinded data

and adaptive decision-making in accordance with the well-

specified adaptation plans.

DATA MONITORING COMMITTEE (DMC)


� Most important is to describe in the IDMC charter

• Who will perform the interim analysis,

• the implementation of the adaptation plan,

• who receives access to interim results,

• how access will be provided.

SGS IDMC-SGS IDMC coordinator

-SGS statistician

-IDMC voting members

-- Drug development expertSGS STAT

SGS SDO

SGS EXPRIMOSimulations (SIMULO)

Client steering

CommitteeScientific experts +long

term implications

IDMC asks input from ...

TLFs or patient profiles +

SGS MA

SCEPTRE safety data

SGS COORDINATOR

Deblinding of data SGS EXPRIMO

PK/PD Analysis

SGS INDEPENDENT ANALYSIS OF BLINDED DATA


DM Client

TRIAL

DATA

DM CRO

or DM SGS

Blinded data

Blinded data

Client trial team

SGS STATAdditional analysisIDMC communicates

final decision

(termination, reassess,

refinement or changes)

TLFs or patient profiles +

stat analysis

Implement changes

according to IDMC charter

Client trial team: try to eliminate role in decision process. Only allowed to see IA results if prespecified in the IDMC charter:

(special circumstances, describe which info can be released, R&R + processes, describe the firewall process, regulatory agreement

needed!!!)

� Founded in 2002 and joined SGS in 2012

� EXPRIMO in latin means to define, to model,

to extract, to reveal…

� A Consultancy group of about 15 experienced

pharmacometricians with pharmaceutical industry, academic and regulatory

simuloDRUG TRIAL SIMULATOR

SGS EXPRIMO: ADVANCED PK/PD M&S


industry, academic and regulatory backgrounds

� More than 300 M&S projects have been performed in wide range of therapeutic areas

� Work performed by Exprimo has been very well received by regulatory authorities

� All analyses are focused on key question(s) a client may have at a specific drug

development phase

EXPERIENCE OF EXPRIMO WITH ADAPTIVE

DESIGN

� Adaptive phase 2 dose-finding trials

� PK-PD-disease model development for use in trial

simulation and design optimization (dosing schedule and

dose adjustment performance)

� Model based interim analyses during clinical trials using


� Model based interim analyses during clinical trials using

Bayesian approaches

• Accumulate knowledge (learning) and continuous model

improvement to prepare for decisions or fast transition to next phase

• Model estimates to support design adaptations

• Experience with blinded and un-blinded interim analyses and reports to DSMBs (Data and Safety Monitoring Boards)

EXAMPLE 1: DOSE ADAPTATION SIMULATION IN

ONCOLOGY

0 5 10 15 20

0100

200

300

400

Patients with Grade I Neutropenia

Trials

Grade I

0 5 10 15 20

0100

200

300

400

Patients with Grade II neutropenia

Trials

Grade II

200

300

400

Trials

Grade III200

300

400

Trials

Grade IV

1. Number of patients with grade I-IV neutropenia can be

predicted for future study

2. Can be compared with observed trial results

Observed values


0 5 10 15 20

0100

200

Patients with Grade III neutropenia

Trials

0 5 10 15 20

0100

200

Patients with Grade IV neutropenia

Trials

Grade III

Grade IV

Days

Neutr

ophils

(E

06/L

)

0 20 40 60 80

01000

3000

5000

476 238 0 357 0 238 mg/day

id = 18 , Age= 69 Y , BSA= 1.9 m2 , CL= 70 L/h

results

3. Complex (individual) treatment scenarios

can be simulated…

4. …and the per protocol dose

adaptation rules can be evaluated

2nd cycle:25%

dose decrease

3rd cycle:33%

dose decrease

baseline

nadir

� Monoclonal antibody with highly non-linear PK and target

PD

� Prior to study, develop a target mediated drug disposition

model (TMDD) with uncertainty based on pre-clinical data

model based on:

EXAMPLE 2: MODEL BASED DOSE ESCALATION

(PHASE 1)

learning


� Measure PK and compare with simulated scenario’s and

re-estimate model uncertainty

• Use simulations to support clinical team with dose

decisions

• Model duration of PD measure to justify the start of new cohort

� Enriched PK-PD model used for design multiple dose part

EXAMPLE 2: MODEL BASED DOSE ESCALATION

(PHASE 1)

� Observed data in cohort does not provide true

information on shape of profile

� Prediction based on

NI-0101 c

oncentration (ng/m

L)

1000

10000

PredictionsObservations

NI-0101 dose: 0.25 mg/kgObservations vs predictions


� Prediction based on model will be allowed to decide when follow-

up of subjects can be terminated or next

cohort can be started

Time (day)

NI-0101 c

oncentration (ng/m

L)

0 10 20 30 40 50

110

100

?

� Study with monoclonal antibody for treatment of rare and

life-threatening disease in children.

� Prior model based on:

• previous PK trial in adults

• clinical observations and biomarker data from previous

EXAMPLE 3: CONCENTRATION TARGETED

DOSE- ADAPTATIONS IN INDIVIDUAL SUBJECTS


• clinical observations and biomarker data from previous studies

� Analysis:

• Observations of PK and PD are used in a Bayesian approach

to guide dosing frequency that inhibits immune response

• Data is combined to guide dose adjustment after 3 days based on pre-defined effect targets

• Very short turn-around time of PK, PD and simulations; within 48 hours recommendation of next dose within individual child


DOSE- ADAPTATIONS IN INDIVIDUAL SUBJECT


Minimum concentration inhibiting 99% of biomarker, maximum concentration observed in healthy volunteers


DOSE- ADAPTATIONS IN INDIVIDUAL SUBJECT

Last dose Conditioning Eventτ ↑ to 6 days


� simulo is a PK-PD-Disease model

simulator, and provides the ability

to simulate and subsequently analyse clinical studies using

public, published or custom-

developed nonlinear mixed-effects models, in order to explore the

impact of variables on outcomes.

� Thanks to its web-based

configuration, simulo offers during

simulo: A SIMULATION SOFTWARE THAT

PROMOTES SUSTAINED COLLABORATION AND

COMMUNICATION


configuration, simulo offers during

a project a high flexibility and

consistency in the collaboration and communication between

Exprimo and the client.

� simulo is offered as an integrated

part of the consultancy service that

Exprimo delivers to clients during a project. Based on your needs, we

offer an adapted project proposal

for the use of simulo.

simulo at: http://www.simulo.eu

CONCLUSIONS

� Adaptive design could/should be foreseen for early clinical

trials (dose-response or dose-exposure studies).

� Potential advantages offered by adaptive designs need to

be balanced against any perceived risks or complexities.

� Extensive regulatory guidance is available, mostly


� Extensive regulatory guidance is available, mostly

applicable in the context of confirmatory drug

development.

� M&S is an important tool in drug development and is very

supportive when an adaptive design needs to be

implemented.

REFERENCES

� Executive Summary of White Paper. Adaptive designs in

clinical drug development. An executive summary of the

PhRMA working group. Journal of Biopharmaceutical

Statistics, 16: 275-283, 2006.


� Reflection paper on methodological issues in confirmatory clinical trials planned with an adaptive design. October 2007. CHMP. EMEA.

� Guidance for Industry. Adaptive Design Clinical Trials for

Drugs and Biologicals. February 2010. United States

Department of Health and Human Services. Food and

Drug Administration.

Life Science Services Laveille Christian, Pharm.D.Senior Consultant

SGS Exprimo NV Phone: +33 474688184 Generaal De Wittelaan, 19A Bus 5, E-mail : [email protected]

THANK YOU FOR YOUR ATTENTION

+ 41 22 739 9548

+ 1 866 SGS 5003


Generaal De Wittelaan, 19A Bus 5, E-mail : [email protected] Mechelen Web : www.sgs.com/Exprimo

Belgium

+ 1 866 SGS 5003

+ 65 637 90 111

+ 33 1 53 78 18 79

+ 1 877 677 2667

+ 33 1 41 24 87 87

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Adaptive Clinical Trials: Role of Modelling and Simulation

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