Discuss the various aspects about model exploration. (10 marks)

Modelling is building representations of things in the ‘real world’ and allowing ideas to be
investigated.

Models can be explored by the following:

➢ Parameter Sensitivity Analysis (PSA)
➢ Virtual trial
➢ In vitro dissolution and in vitro–in vivo correlation
➢ Biowaiver considerations

Parameter sensitivity analysis

Sensitive analysis is defined as the technique used to determine how independent variable values
will impact a particular dependent variable under a given set of assumptions.

It is also defined as the study of how uncertainty in the output of a model can be attributed to
different sources of uncertainty in the model input

When performing PSA, one parameter is changed gradually within a predetermined range,
knowledge, while keeping all other parameters at baseline levels.

Applications of PSA

PSA can serve as a useful tool when the input values for some of the physicochemical properties
of a compound are rough estimates and when model predictions do not correlate well with in
vivo values.

PSA can predict the effect of inter-individual variation in PK parameters on drug absorption for
a highly variable drugs.

PSA can also be used to guide formulation design. For example, if a compound has a poor
predicted percentage of drug absorbed, PSA can aid identification of critical parameters limiting
the absorption or bioavailability of a drug.

PSA help to save a great deal of time and effort, and minimize loss of resources in
(pre)formulation processes.

Virtual trial

In the later stages of formulation development, it is especially valuable to anticipate inter-
subject variability that may influence oral drug bioavailability. In this way, the formulator might
gain a better insight on what can be achieved by means of the formulation.

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In order to in silico simulate the influence of population variability and/or the combined effect of
formulation variables that are not precise values, but for which distributions of values can be
estimated the use of virtual trial feature in various simulation softwares.

This feature allows the user to perform stochastic simulations on a number of virtual subjects,
wherein the values of the selected variables are randomly sampled from predetermined
distributions which are usually estimated on the basis of previous knowledge or analysis of
literature data.

The results of the simulations are expressed as means and coefficients of variation for fraction of
drug absorbed, bioavailability, t max, C max, and AUC values, as well as absolute minimum and
maximum values for each of these parameters reached during the trials.

The prime objective of this study was to demonstrate how an in silico approach can be used to
predict nonlinear dose- dependent absorption properties of a drug. Simulations are performed in
a virtual trial mode to include the effects of physiological variables, such as transit times in
various GI compartments, GI pH, lengths and radii, PK parameters, plasma protein binding, and
renal CL on drug absorption.

Stochastic variables were randomly selected within the range defined by the means with
predetermined coefficients of variation in log normal space, and used for the simulation.

The simulation results revealed that all of the observed clinical data lay within the minimal and
maximal individual patient simulations. Thus, it was deduced that virtual trial simulations based
on the presumed distribution of the selected variables were able to predict variability associated
with the observed clinical data.

In vitro dissolution and in vitro–in vivo correlation

IVIVC has been defined as “a predictive mathematical model describing the relationship
between an in-vitro property of a dosage form and an in-vivo response”.

There are two approaches enabling to be used to assess the relationship between the in vitro and
in vivo data:

▪ Convolution: To predict the plasma concentration profile
▪ Deconvolution: To estimate the in vivo dissolution profile.

Once an IVIVC is developed, an in vitro dissolution test can be used to identify changes that
may affect the efficacy and safety of the drug product. In addition, biowaiver justification could
be discussed in terms of whether dissolution from the dosage form is expected to be the rate-
limiting factor for drug in vivo absorption.

In the convolution approach, a set of in vitro data representing different dissolution scenarios
is used as the input to estimate the expected drug plasma concentration- time profiles. In the next

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step, the obtained profiles are compared with the mean drug plasma concentration profile
observed in vivo, in order to establish an IVIVC.

In deconvolution approach, in vivo absorption profile estimated by GastroPlusTM is compared
with in vitro obtained dissolution profiles to identify ‘bioperformance’ dissolution conditions.

Biowaiver considerations

Biowaiver refers to the situation in which in vivo BE studies can be substituted with the relevant
in vitro data.

The role of biowaivers in the drug approval process has been emphasized since the introduction
of BCS and the release of FDA guidance on waiver of in vivo bioavailability and BE studies.

The term biowaiver refers to the situations in which in vivo BE studies can be substituted with
the relevant in vitro data. The main purpose of adopting the biowaiver concept was to reduce
time and costs, and to offer benefits in terms of ethical considerations.

The most common type of biowaiver adopted by the regulatory authorities includes the
application of the BCS-based scheme or the application of IVIVC.

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