Pharmaceuticals: Bioequivalence & Clinical trials

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Pharmaceuticals: Bioequivalence & Clinical trials

  1. 1. Pharmaceuticals: Bioequivalence & Clinical trials an INTER-COMPARISON methodology for BIOAVAILABILTY/BIOEQUIVALENCY purposes karafede@hotmail.com
  2. 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. 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. 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. 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. 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. 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. 8. Example taken from intercomparison of receptor models for air quality purposes: correlation g Al m th i or (R t ol) o
  9. 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. 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. 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. 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. 13. Example taken from intercomparison of receptor models for air quality purposes: proficiency test action warning acceptable OK TESTS
  14. 14. Example taken from intercomparison of receptor models for air quality purposes: proficiency test g Al m th i or (R t ol) o

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