Incorporating population variability into mechanistic prediction of PK and modeling PK/PD
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a dataset collected by the EU Commission in June-September 2018
. Some of these links will therefore die out with time.
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overview of courses maintained by ETPLAS
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United States of America
06 August 2018
China, Japan, United States of America
Tokyo, Princeton, Shanghai, Washington
Incorporating population variability into mechanistic prediction of PK and modeling PK/PD
The model-informed approach to various aspects of drug development is rapidly being adopted by the leading pharmaceutical companies. The Simcyp workshops focus on the optimal use of
compound-specific in vitro and in vivo data together with systemspecific information related to humans to simulate and understand drug behavior in various target populations. This integrated approach informs decisions related to Investigational New Drugs and assists
with the conduct and optimal design of clinical studies.
The ultimate aim is to better understand drug PK/PD properties, reduce the cost and time of drug development, improve the quality of regulatory submissions, and eventually implement precision medicine.
Delegates will learn how to simulate and predict:
• Metabolic drug clearance (CL)
• Metabolic drug-drug interactions (DDIs)
• Gut first-pass metabolism
• Oral drug absorption incorporating food effects and the impact
of dosage form
• Effect of transporters and enterohepatic recirculation on
kinetics and DDIs
• Drug distribution to different organs
• Population variability in drug concentration-time profiles
• Variation in kinetics in specific populations (pediatrics, ethnic
groups, various disease populations)
• Modeling of therapeutic proteins
• Pharmacodynamic effects of different compounds
• Time-course of drug in plasma that fits observed clinical data
(achieved by combining fitting techniques with IVIVE, PBPK and
drug-specific in vitro data)
Optional / Voluntary
our workshops are relevant to senior level managers as well as scientists working in the fields of drug metabolism, ADME, clinical pharmacology, pharmacokinetics, PBPK and PK/PD, both in industry or in academia and research institutes. There is a focus on facilitating communication and interaction between pre-clinical in vitro groups and those responsible for the conduct of early clinical studies. The courses provide a solid grounding in model-informed approaches and are not aimed solely at individuals who have hands-on experience.
Researchers, Regulators and policy-makers, Teachers and educators, Technicians, Managers, Scientific officers / Project managers
Academia, Industry, Governmental bodies, Contract Research Organizations (CROs), Consulting, SMEs
Continuing Professional Development
Designing procedures and projects, Computational methods
Full coverage (a dedicated course)
|Details on the topic or technology covered:||
In vitro-in vivo extrapolation (IVIVE) for metabolic clearance (CL) and quality issues:
Attendees will make quantitative predictions of metabolic clearance using data from human liver microsomes and rhCYP systems. There will be discussion of non-specific binding,
active uptake, differences between in vitro systems, and aspects of
quality assurance related to IVIVE. Scaling from other systems such
as hepatocytes and rhUGT will also be discussed.
Quantitative prediction of gut metabolism:
Incorporation of biological variability in the prediction of gut metabolism and first-pass
effects and the interplay between permeability and metabolism.
Incorporation of information on population variability:
This module will focus on how drug elimination differs between individuals
(eg, special populations: children, different ethnic groups,
those with different CYP genotypes, renal failure, cirrhosis, and
obesity). Elements of the demographic, physiological, genetic, and
biochemical factors that need to be considered when predicting
drug clearance in these groups are described along with practical
examples to demonstrate the impact with different drugs.
Prediction of concentration-time profiles and dose nonlinearity:
Discussions will focus on the necessary elements for
predicting concentration-time profiles and contrasting different
modeling approaches. Dose-linearity issues related to metabolism
including saturation of different pathways will be considered.
Prediction of metabolic drug-drug interactions (DDIs)—inactivation,
induction, suppression and stabilization of enzymes:
A step-by-step introduction on how to use in vitro information on
the metabolic routes of drug elimination and the characteristics of
the perpetrator drug to estimate the potential for metabolic DDIs.
The impact of inactivation parameters, turnover-rate constant and
dose-staggering on mechanism-based inhibition (MBI), in vivo as
well as the effect of different in vitro input data on the simulation
of CYP induction and calibration of new inducers against in vivo
reference compounds will be explored. Inter-individual variability
and how to identify the most susceptible patients will be discussed.
Study design issues:
The conduct of clinical investigations to
explore enzyme induction and inhibition within the framework
of regulatory assessment will be discussed. The influence of
trial design elements on DDIs, prediction of mechanism-based
inactivation, induction, and multiple DDIs will be demonstrated
using practical examples.
Sensitivity analysis, parameter estimation, and model fitting:
Attendees will receive guidance on the assessment of the sensitivity
of model parameters and assumptions and gain experience
with fitting PBPK models to observed clinical data (bridging
bottom-up and top-down approaches).
An introduction will be given to the
importance of metabolites in determining pharmacological
outcomes as well as DDIs. Subsequently, IVIVE issues in the
prediction of metabolite kinetics will be explored and practical
examples of the impact of metabolite kinetics for DDI considered.
Distribution aspects of physiologically-based pharmacokinetics
Physicochemical characteristics are combined with biochemical
and physiological features of organs in algorithms to estimate
volume of distribution, tissue blood partitioning, and drug concentration
time-profiles in different tissues and organs. Further, perfusionand
permeability-limited models and the required systems and drug
parameters for liver, brain, and kidney will be discussed.
The Simcyp PD module will be used to
simulate pharmacological responses to drug compounds using
simple and advanced pharmacodynamic models including intrinsic
efficacy transduction, indirect response, and survival models.
The impact of variables such as concurrent medication, disease
conditions, ethnicity, CYP-enzyme phenotypes, and different formulations
on the response to the drug will also be investigated.
Prediction of drug absorption and assessment of food effects
and dosage form:
This module considers entry of the drug into
the enterocyte, gut wall metabolism and the effects of food, both
on the physiology of the GI tract, as well as its impact on the processes
of drug solubility, dissolution, and metabolism. Population
variability and the elements that influence oral drug bioavailability
are examined using the Advanced Dissolution, Absorption and
Metabolism (ADAM) model. Dermal and pulmonary routes of drug
administration will also be considered.
IVIVE of transporter-related information and biliary excretion:
Attendees will investigate the effects of intestinal apical uptake and
efflux transporters on drug absorption, gut metabolism, and DDIs,
as well as the impact of hepatic transporters on metabolism, DDIs,
and biliary excretion considering potential reabsorption of the
drug in the intestine. Transport in the brain and kidney, including
competitive inhibition of kidney transporters, will also be covered.
Attendees will become familiar with the Simcyp biologics
module and the steps involved in simulating data for therapeutic
proteins. The effect of target-mediated drug disposition (TMDD) on
the pharmacokinetics of therapeutic proteins will be investigated.
The Simcyp Animal Simulators will be introduced to
assess the PK properties of compounds and simulate concentrationtime
profiles in the virtual rat, dog, knock-out mouse, and monkey
Participants will learn about the application of “prior knowledge” to
improve the selection and design of clinical studies. The workshops
are designed to provide the necessary understanding and skills to
simulate and predict the pharmacokinetics of drugs in any relevant
populations and assess pharmacodynamic effects at an early stage
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