Pharmaceuticals: Bioequivalence & Clinical trials

an INTER-COMPARISONmethodology

for BIOAVAILABILTY/BIOEQUIVALENCY

purposes

karafede@hotmail.com

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 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

Guidelines for a COMPATIVE ANALYSYS TOOL

Bioavalability/Bioequivalency data

Bioequivalence Studies

Assure therapeutic equivalence of generic

products to innovator products

Bioavailability should be compared for innovator and generic products

Pharmacodynamic studies

The Acceptance criteria of equivalence is established by considering the

pharmacological activity of each drug

Clinical studies

Targeting the EQUIVALENCE

The Acceptance criteria of equivalence is the pharmacological characteristics and activity of each drug

Data entry

Gathering data by category

Data classification

Compare classified data(inter-comparison)

Data evaluation(proficiency test)

Guide User Interface (GUI)

Data filteringaccording to acceptability criteria

(correlation, weighted difference)

Compare data with standards/reference(inter-comparison)

Inter-Comparison STRUCTURE

Bioequivalence/Bioavailability

TEST(i) vs TEST(j)Pearson correlation

and weighted difference (WD)

TEST(i,j) vs REFERENCESPearson correlation

and weighted difference (WD)

CONTRIBUTIONS(i,j) (TIME TRENDS)Pearson correlation

Tests for bioavailability

and bioequivalency

If 4 out of 7 tests are nor meetthen

the TEST is considered dubious

Z-score(proficiency test)

Trialperformance

treatement performance

compare Bioavailability/Bioequivalence data

Pharmacological dataClinical data

INTER-COMPARISON methodology

Assure therapeutic equivalence of generic products to innovator products

CLINICAL TRIALS and their COMPONENTS

TEST (Pj) with observables (pji)and uncertainties (vji)

pj1 pj2 pj3 pj4 pjnpj5 ... ... ... ...Pj =

vj1 vj2 vj3 vj4 vjnvj5 ... ... ... ...± Vj =

Uncertainty:- standard deviation of the TEST- analytical uncertainty associated to the TEST

comparison(bioavailability\bioequivalencepharmacology; clinical trial )

chemicalin vitroin vivo

chemicalin vitroin vivo

i j

correlation is made at components level (pij , pji )

CorrelationTEST (Pj)TEST (Pi)

0.6

0.0

1.0

0.6

0.0

1.0

NOT OK OK

The criterion of R2 = 0.6 is used to establish if trials are comparable to each other in the same TEST study

INTER-COMPARISON methodology I:Correlation

R2

max

Example taken from intercomparison of receptor models for air quality purposes: correlation

Algorithm (R

tool)

INTER-COMPARISON methodology II: Weighted difference

n

1i2ji

2ji

jijiPP

pp

pp1/nWD

ji

2.0

0.0

4.0

0.0 OK NOT OK

3.0

2.0

4.0

3.0

1.0 1.0

Acceptability: from 0 to1

WD

more robust assessment compared to Pearson correlation

Weighted difference is made at components level (pij , pji )

Bioequivalency weighted on the uncertainty of a specific TEST

Example taken from intercomparison of receptor models for air quality purposes: weighted difference

Algorithm (R

tool)

the TEST is considered coherent and satisfactory if:

the TEST is unsatisfactory if:

the TEST is considered questionable if:

INTER-COMPARISON methodology III: proficiency test for bioavailabilty/bioequivalency, clinical studies

Defining the standard deviation for proficiency assessment p as criterion to evaluate new treatment performance (ISO 13528)(p = 50%,25%...)

“OK”2z

3z2 “Warning”

3z “Action”

p

jj

σ

XPz

z-score

Assigned value

* s1.5d

dpp *jji

dpp *jji

dpp *jij,

dpp *jij,

ij,ij, pp

if

if

otherwise

ji*i pMEDp

*jji

*j pp MED1.483s

n

1j

j*j pn1pX

Z-score method: TEST performance

Define a new assigned reference value (X) among TESTS (Pj)

X is generated by robust analysis iterative algorithm:

action

acceptable

warning

OK

TESTS

Example taken from intercomparison of receptor models for air quality purposes: proficiency test

Example taken from intercomparison of receptor models for air quality purposes: proficiency test

Algorithm (R

tool)