This document describes a methodology for comparing bioavailability and bioequivalence data from pharmaceutical clinical trials. The methodology involves gathering generic and innovator drug data, classifying the data, comparing the data using statistical methods, and establishing equivalence criteria. The comparison methods calculate correlation coefficients and weighted differences between tests, and use z-scores to evaluate test performance in a proficiency test. The goal is to assure therapeutic equivalence between generic and innovator drugs.
2. Guidelines for a
COMPATIVE ANALYSYS TOOL
Gathering data:
Generic products
New formulation in new drugs
New content in new drugs
Change of ingredients in drugs
Release of dosage forms
Clinical data
Pharmacodynamic data
Bioavalability/Bioequivalency data
Classification:
Dose
Design
Subjects
Sampling intervals
Comparison:
compare data following a statistical methodology
Equivalence:
Establish acceptance criteria of equivalence to innovator products
Compliance:
Verify compliance with standards and regulations
3. Targeting the EQUIVALENCE
Bioequivalence Studies
Bioavailability should be compared
for innovator and generic products
Assure therapeutic equivalence of
generic
products to innovator products
Pharmacodynamic
studies
The Acceptance criteria of equivalence is
established by considering the
pharmacological activity of each drug
Clinical
studies
The Acceptance criteria of equivalence is the
pharmacological characteristics and activity of each drug
4. Data entry
Inter-Comparison
STRUCTURE
Gathering data by category
Guide User Interface (GUI)
Data classification
Compare classified data
Compare data with standards/reference
(inter-comparison)
(inter-comparison)
Data filtering
according to acceptability criteria
(correlation, weighted difference)
Data evaluation
(proficiency test)
Bioequivalence/Bioavailability
5. INTER-COMPARISON methodology
Tests for
bioavailability
and
bioequivalency
compare
Bioavailability/Bioequivalence data
Pharmacological data
Clinical data
TEST(i) vs TEST(j)
Pearson correlation
and weighted difference (WD)
TEST(i,j) vs REFERENCES
Pearson correlation
and weighted difference (WD)
CONTRIBUTIONS(i,j) (TIME TRENDS)
Pearson correlation
Assure therapeutic equivalence of
generic products to innovator products
If 4 out of 7 tests are nor meet
then
the TEST is considered dubious
Z-score
(proficiency test)
Trial
performance
treatement
performance
6. CLINICAL TRIALS and their COMPONENTS
chemical
in vitro
in vivo
comparison
i (bioavailabilitybioequivalence
chemical
in vitro
in vivo
pharmacology; clinical trial )
TEST (Pj) with observables (pji)
and uncertainties (vji)
Pj =
pj1 pj2 pj3
pj4 pj5 ... ... ...
...
pjn
Uncertainty:
- standard deviation of the TEST
- analytical uncertainty associated to the TEST
± Vj =
vj1 vj2 vj3
vj4 vj5 ... ... ...
...
vjn
j
7. INTER-COMPARISON methodology I:
Correlation
TEST (Pi)
TEST (Pj)
Correlation
correlation is made at components level (pij , pji )
The criterion of R2 = 0.6 is used to establish
if trials are comparable to each other in
the same TEST study
R2
max
1.0
1.0
0.6
0.6
0.0
0.0
NOT OK
OK
8. Example taken from intercomparison of receptor models
for air quality purposes: correlation
g
Al
m
th
i
or
(R
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ol)
o
9. INTER-COMPARISON methodology II: Weighted difference
Bioequivalency weighted on the uncertainty of a specific TEST
n
WDPi Pj = 1/n
∑
i =1
p ji − p ji
p2 + p2
ji
ji
Weighted difference is made at components level (p ij , pji )
Acceptability: from 0 to1
more robust assessment
compared to Pearson correlation
4.0
WD
4.0
3.0
3.0
2.0
2.0
1.0
0.0
1.0
0.0
OK
NOT OK
10. Example taken from intercomparison of receptor models
for air quality purposes: weighted difference
g
Al
m
th
i
or
(R
t
ol)
o
11. INTER-COMPARISON methodology III:
proficiency test for bioavailabilty/bioequivalency, clinical studies
Defining the standard deviation for proficiency assessment ( σ p)
as criterion to evaluate new treatment performance (ISO 13528)
Assigned value
(σ p = 50%,25%...)
Pj − X j
z=
z-score
σp
the TEST is considered coherent and satisfactory if:
z ≤2
“OK”
the TEST is considered questionable if:
2≤ z ≤3
“Warning”
the TEST is unsatisfactory if:
z >3
“Action”
12. Z-score method: TEST performance
Define a new assigned reference value (X) among TESTS (Pj)
X is generated by robust analysis iterative algorithm:
d = 1.5 s*
{ }
p* = MED p ji
i
{
}
p ji = p* − d
j
if
p j,i > p* + d
j
p ji = p* + d
j
if
p j,i < p* + d
j
p j,i = p j,i
otherwise
s*j = 1.483 MED p ji − p*
j
X = p* = 1 n
j
n
∑p
j =1
j
13. Example taken from intercomparison of receptor models
for air quality purposes: proficiency test
action
warning
acceptable
OK
TESTS
14. Example taken from intercomparison of receptor models
for air quality purposes: proficiency test
g
Al
m
th
i
or
(R
t
ol)
o