| Case
study 4: Can the acceptance criteria for the drug substance
particle size distribution (D10, D50, D90) of “EMD Compound
A” be widened based on a PBBM approach?3
|
PBBM developed using particle size distribution from
nonmicronized,
micronized, and fine-micronized drug substance. Validation with clinical
data for different formulations and doses. Wider, yet clinically relevant
drug substance acceptance criteria (as D10, D50, and D90) proposed
based on the PBBM analysis. |
Low (1) |
Medium
(2) |
Low (2) |
Low (2) |
Oral
solution; SAD PK (micronized and nonmicronized API in
capsules); relBA and BE of various tablet formulations; no non-BE
batch. All PK data in HV. |
Model built using iv microdosing
data. Lysosomal trapping of
drug in enterocytes assumed, and model was adopted accordingly (fit
fu,ent). Low CL drug with no significant first pass metabolism. Compartmental
PK model used to model postabsorptive drug disposition. |
| Case study 5: Is the OOS batch based on the QC dissolution
method, bioequivalent to the reference product?3
|
PBBM developed using PBDT and validated using
clinical data
with different formulations. VBE trials to demonstrate that the OOS
batch is BE to the reference batch eliminating the requirement for
a clinical study. PBBM submitted as part of data package to justify
QC dissolution spec widening |
Low (1) |
Medium
(2) |
Low (2) |
Medium/High (eliminate clinical
study) |
Oral solution, BE and non-BE batches |
PBBM built using PBDT data as input, not QC dissolution data |
| Case study 6: Is X% of polymorphic impurity allowed
in the
drug product?3
|
PBBM developed
with PBDT as input. PBBM used to simulate VBE
trials which are used to define a certain % where there would be no
influence on the extent of absorption and plasma PK, eliminating the
requirement for a clinical study. PBBM submitted as part of data package
to justify the % of polymorphic impurity |
Low (1) |
Medium–High (3–4) |
Medium (3) |
Medium/High (eliminate clinical study) |
Parallel
and crossover design, fasted state, different formulations,
effect of process and scaling, PSD |
PopPK used to parametrize
disposition parameters. No iv data
available |
| Case study, Drug Cb.12 How do you conduct extrapolation
of bioequivalence study
results obtained in male subjects to both genders? |
Model
was utilized to demonstrate that BE study results obtained
in male subjects can be extrapolated to females |
Medium
(2) |
Medium (2) |
Low (2) |
Low
(2) |
Pilot and pivotal batches (model differentiated
between BE
and non-BE batches) |
Model was built wherein appropriate
inputs for dissolution,
enzymes and transporters are included. |
| Case
Study GSK3640254.3 How do you
support a biopredictive dissolution method? |
Important
for internal decision making, risk assessment. Changes
in disintegration time (DT) due to process changes but within the
clinically relevant dissolution safe space. Model demonstrated no
clinically relevant changes in DT |
Medium (2) |
Medium (2) |
Low (2) |
Low (2), GSK3640254
development was terminated |
Human relBA data (capsule
to tablet). TIM1 data of reference
and stretched batch |
QC method was not biorelevant, but
it was biopredictive. It
was assessed using DLM scalar in ADAM model. A non-BE batch could
not be produced within the formulation design space. |
| Case Study GSK3640254b,3 How do support clinically relevant dissolution specification |
Important for internal decision making, risk assessment |
Medium (2) |
Medium (2) |
Low (2) |
Low (2), GSK3640254 development was terminated |
Human relBA data (capsule to tablet). TIM1 data of reference
and “stretched” batch |
Clinically relevant
model informed dissolution safe space,
defined based on PK/PD relationship, was wider that then changes observed
with QC method between reference and “stretched” batches. |
| Case Study Fevipiprantb:39 How do you to establish
dissolution bioequivalence safe space? |
PBBM to define
BE safe space with QC method for 450 mg dose.
Dissolution profiles are used as an input to the PBBM, the PBBM is
then used to predict Cmax and AUC. |
Medium (2) |
Medium (2) |
Low (2) |
Medium (2), widening of dissolution specification; Fevipiprant
development was discontinued |
The PBBM performance was
demonstrated for various oral dosage
forms (150–450 mg), including the non-BE batches in fasted
HVs. To define the safe space at 450 mg, simulations were performed
using theoretical, virtual dissolution profiles |
A specification
of Q= 80% dissolved after 60 min for an IR
oral solid dosage form reflected the boundaries of the safe space. |
| Case study 11. Elagolixb Justifying
widening of dissolution specification without a non-BE lot. (US FDA
Product Quality Review Available29) |
PBPK model based on DDI was verified/validated using in vitro
dissolution and in vivo data from pivotal and commercial materials,
which are BE to the reference. This model predicted similar exposures
from lots with slower dissolution profiles (75% slower dissolution
rate led to 14% difference in exposure which was within 80–125% of reference,27,30 which resulted in widening of dissolution specifications and approved
specifications.29
|
Medium
(2) |
Medium (2) |
Low (2) |
Medium
(2), widening of dissolution specification |
Reference,
Phase III and commercial lots were evaluated. Both
Phase III and commercials lots were found BE to the reference in two
separate PK studies. Slower-releasing lots were not tested in vivo
but were evaluated with the PBBM/PBPK model. The dissolution safe
space was extrapolated to slower dissolving lots using PBPK modeling. |
|
| Q1. Can PBPK model reasonably describe
elagolix PK after input
of dissolution data? |
|
|
|
|
|
|
Agency response
to Q1 (R1). Yes. With the incorporation of
in vitro dissolution profiles, the ratio of predicted Cmax and AUC by PBPK model to respective clinical observations
were within 0.80–1.25. |
| Q2. Can PBPK models provide a reasonable prediction
of the
impact of slow dissolution on in vivo exposure ? |
|
|
|
|
|
|
R2. The slower dissolution would not significantly
affect the
in vivo exposure of elagolix. See reference for further details. |
| Q3. Can modeling support a clinically relevant dissolution
acceptance criterion? |
|
|
|
|
|
|
R3. Yes,
the PBPK model supported a clinically relevant dissolution
acceptance criterion. |
