Transcript Best practices: Industry Example

Best Practices in
Modeling and Simulation
Why do we need?
Industry example
Wonkyung Byon
Pfizer Global Clinical Pharmacology
Best Practices in M&S
Great idea!
…….well,
whytododevelop
we
Hi Won,
we need
need any
on
an internal
popguidance
PK guidance….
Pop
PKare
modeling???
and
you
the chair!
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Best Practices in M&S
Pharmacometrics/MBDD
Session 1: Is Model-based Drug Development Delivering on its
Promise? Assessing the Business Impact
Session 2a: Can Systems Pharmacology Provide a Way Forward in
the Search for Novel Treatments in Alzheimer’s Disease?
Session 2b: Model-Based Meta-Analysis in Oncology
Session 2c: "Curve” balls in Pharmacometrics- Roundtable
Session 3: Advances in Pediatric Physiologically Based
Pharmacokinetic Modeling in Pediatric Drug Development
Session 4a: Catastrophe and Chaos in Pharmacodynamics
Session 4b: Population Modeling Using Complex PhysiologicallyBased Models
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Best Practices in M&S
Pharmacometric analyses
• Six-fold increase in the number of New Drug
Applications that include pharmacometric
analyses over a recent 9-year span (from 2000
through 2008) [Lee, J.Y. et al. Clin. Pharmacokinet. 2011]
• Enhanced knowledge management and
decision-making through model-based drug
development
[FDA Critical Path 2004]
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Best Practices in M&S
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Best Practices in M&S
Objectives? Assumptions? Communications?
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Best Practices in M&S
Best Practices/Guidance… Why?
Pharmacometrics
= Evolving and
interdisciplinary science
Pharma industry
= GLP,GCP,GMP
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Best Practices in M&S
Good “Modeling” Practice
Benefit
 Increased consistency
 High quality output
 Greater efficiency
 Training
Risk
 “One size fits all.”
 Soon to be outdated
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Best Practices in M&S
FDA/EMA Guidance For Industry
• Population Pharmacokinetics
• Guideline on reporting the results of Pop PK
analyses
• Exposure-Response Relationships
• End-of-Phase 2A Meetings
• Pharmacokinetics and pharmacodynamics in
the development of antibacterial medicinal
products
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Best Practices in M&S
Recent Publications
• Fundamentals of population pharmacokinetic modelling:
modelling and software/validation methods
[Clin Pharmacokinet. 2012;51(8):515-25/51(9):573-90]
• Basic Concepts in Population Modeling, Simulation, and
Model-Based Drug Development—Part 1/ Part 2:
Introduction to Pharmacokinetic Modeling Methods
[CPT: PSP. (2012) 1, e6 / 2: e38]
• White Paper: Landscape on Technical and Conceptual
Requirements and Competence Framework in
Drug/Disease Modeling and Simulation
[CPT: PSP. (2013) 2: e40]
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(iii) An update to the current regulatory guidance
on dose ranging/finding (see also BOS2 paper) will
be debated.
(iv) M&S methodology and reporting standards and
good practice documents are required (see also
BOS4 paper). This will be an industry-led initiative in
the first instance, though regulators wish to be
involved early in the discussion with the ultimate
objective to develop guidance documents.
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Best Practices in M&S
Acknowledgement
Phylinda Chan
Carol Cronenberger
Haiqing Dai
Jennifer Dong
Steve Riley
Ana Ruiz
Mike K. Smith
Kevin Sweeney
Mike Tortorici
Sandra Allerheiligen
Kevin Dykstra
Megan Gibbs
Rik De Greef
Pravin Jadhav
Mats Karlsson
Lan Ni
Daniele Ouellet
Vikram Sinha
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Best Practices in M&S
Best Practices
Process-related
Technical
PK/PD modeling
Model-qualification
Analysis
plan/report/unblinding
plan templates
Strategic
Go/No-Go
decision-making
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Coming Soon!
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Clin Pharm Guidance
Population Pharmacokinetic Analyses
A to Z of
Population PK Analysis
ASSUMPTIONS
Covariate selection
Diagnostics
Kowalski
Prior knowledge
SG
HS
R KI H
NR
KN
A G
E
E
I A
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 Assumptions/sensitivity analyses
 Analysis plan and report
 Leverage prior-knowledge
 Clinical relevance
 Communication
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Challenges?
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Opportunities!
Internal “Wikipedia” page
• Hub for collaboration
• To facilitate discussions
• To capture differing
viewpoints
• To assist in collaborative
writing
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“Why do you publish?”
 It provides opportunities to learn
and improve
 “Living document”
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Best Practices in M&S
Good Modeling Practice
Benefit
 Increased consistency
 High quality output
 Greater efficiency
 Training
Risk
 “One size fits all.”
 Soon to be outdated
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THANK YOU
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