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Simplifying study designs and statistical models for new dose & dosage forms DIA 11 april 2019 r

Part of a workshop that I gave. This session was on study designs used for bioequivalence.

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Simplifying study designs and statistical models for new dose & dosage forms DIA 11 april 2019 r

  1. 1. Prof. (Dr.) Bhaswat S. Chakraborty Emeritus Professor, Institute of Pharmacy, Nirma University Former Sr.VP &Chair, R&D, Cadila Pharmaceuticals Former Director, Biopharmaceutics, Biovail, Toronto Former Sr. Efficacy & Safety Reviewer, TPD (Canadian FDA), Ottawa Simplifying Study Designs and Statistical Models: for new dose & dosage forms
  2. 2. Study Designs for New Dose or Dosage form BE (Comparative Bioavailability) Main Principle in Study Design • PK based study – blood concentration can be measured reliably? • Simple or complex PK? • Modified‐release dosage forms? • Drugs with serious toxicity within the normal dosage range? Drugs exhibiting non‐linear pharmacokinetics? • Drugs with a terminal elimination half‐life of more than 24 hours? • Drugs with an important time of onset of effect or rate of absorption? • Critical dose drugs? • Combination product? • Highly variable drug products? Research supports In-vitro BE? © 2019 Prof. Bhaswat Chakraborty 2
  3. 3. Study Designs :Parallel or Crossover? The standard study design used is a 2‐period cross‐over, in which each subject is given the test and reference formulations The advantage of the cross‐over design is that the intra‐subject error is always lower than the inter‐subject error used in a parallel design Replicated cross‐over designs may also be used, where the formulations are tested more than once in the same subjects The main advantage of these designs is that fewer subjects are required; however, they must appear for more periods Parallel designs may be useful when studying drugs with very long elimination half‐lives or some depot formulations. The error term used is the inter‐subject variance © 2019 Prof. Bhaswat Chakraborty 3
  4. 4. Higher Order Study Designs In cases where more than two formulations are under study, or are studied under different conditions, a higher order design (that is (i.e.), more periods and sequences) should be considered Since the intra‐subject error term of these designs has more degrees of freedom, smaller sample sizes are often adequate The choice of a variance balanced design (Williams’ Design) or separate incomplete block design should be justified. A cross‐over design without a drug‐free period between formulations may be employed for studies conducted in patients in whom it would be unethical to discontinue treatment during a washout period • Instead of a drug‐free washout period, the study drugs are administered long enough, prior to sampling, to allow elimination of the previously administered formulation © 2019 Prof. Bhaswat Chakraborty 4
  5. 5. Alternative Study Designs When the proposed estimate of the intra‐subject variance from the literature has large uncertainty, it is possible to collect the data in stages based on the observed intra‐subject variance from the first stage Two strategies for collecting data in stages are Group Sequential Designs and Adaptive Designs For both types of designs the overall Type I error rate should be maintained at 5% and the algorithm should be defined a priori in the protocol These approaches can be used for both cross‐over and parallel designs. © 2019 Prof. Bhaswat Chakraborty 5
  6. 6. Pharmacodynamic (PD) Study Designs In cases where PK endpoints cannot be reliably measured, in- vivo comparability using PD studies • The use and design of PD studies should be justified Design of PD studies should consider the underlying pathology and natural history If baseline conditions are not reproducible, it may be necessary to use a parallel‐group design Patients who are non‐ responders should be excluded from the study by prior screening Important placebo effects should also be considered, as comparisons between drug products can be made only after a priori consideration of such effects in the study design A placebo cross‐over phase may be necessary to evaluate placebo effects © 2019 Prof. Bhaswat Chakraborty 6
  7. 7. N (Number of Subjects ) N should be estimated by considering the objectives of the study, the study design, the drug products being compared and the conditions under which the study is carried out A complete literature search should be conducted in order to understand the drug and drug product Expected mean difference between T & R and anticipated intra‐subject variance for the parameters & the power, determine the N All calculations are to be based on maintaining the overall Type I error rate at 5%. The minimum number of subjects in pivotal studies is 24 © 2019 Prof. Bhaswat Chakraborty 7
  8. 8. Crossover Fed Study Designs A randomized, balanced, single-dose, two-treatment (fed vs. fasting), two period, two sequence crossover design is used for studying the effects of food on the bioavailability of IR or MR product The test product and the RLD should be administered under fed conditions An adequate washout period should separate the two treatments Test product should be administered on an empty stomach (fasting condition) in one period and following a test meal (fed condition) in the other period A similar, 2x2x2 crossover design for a fed BE study is often recommended except that the treatment should consist of both T & R following a test meal (fed condition Usually the same 90% CI BE standard is used for AUC & Cmax © 2019 Prof. Bhaswat Chakraborty 8
  9. 9. Modified Release Dosage Forms (MRDFs) For MR products, increased inter‐subject variability in bioavailability will occur, including the possibility of dose‐dumping There may also be an increased risk of adverse effects such as gastrointestinal irritation, depending on the site of drug release, or absorption, or both Thus for all MR forms (including delayed‐release formulations), BE should be demonstrated under both fasted and fed conditions BE standards • The 90% confidence interval of the relative mean area under the concentration versus time curve to the time of the last quantifiable concentration (AUCT) of the test to reference product should be within 80.0% ‐ 125.0% inclusive. • The relative mean maximum concentration (Cmax) of the test to reference product should be within 80.0% ‐ 125.0% inclusive © 2019 Prof. Bhaswat Chakraborty 9
  10. 10. MRDFs © 2019 Prof. Bhaswat Chakraborty 10
  11. 11. Modified Release Dosage Forms (MRDFs) Steady‐state studies are not generally required. However, if a steady‐state study is conducted, the following standards should be met: • The 90% confidence interval of the relative mean area under the concentration versus time curve at steady state over the dosing interval (AUCtau) of the test to reference product should be within 80.0% ‐ 125.0% inclusive. • The relative mean Cmax at steady state of the test to reference product should be within 80.0% ‐ 125.0% inclusive. • The relative mean minimum concentration (Cmin) at steady state of the test to reference product should not be less than 80.0% inclusive. • Modified‐release products with multiphasic plasma concentration profiles demonstrated to be integral to their therapeutic effect will be subject to standards on the partial area under the concentration versus time © 2019 Prof. Bhaswat Chakraborty 11
  12. 12. Multiphasic Modified Release Dosage Forms The requirement for pAUC assessment metrics for multiphasic modified‐release formulations will be based on data available from scientific literature • The time course of changes in the rate of drug delivery throughout the day should be reconciled with generally accepted and clinically relevant response data generated from a well‐designed randomized clinical trial program • Specifically, standards based on the 90% confidence interval of pAUC metrics should be met • The specific pAUC time intervals to be considered will be based on clinical data showing the therapeutic relevance of the particular time interval (e.g. early onset, maintenance, dose clearance, fasted versus fed state). © 2019 Prof. Bhaswat Chakraborty 12
  13. 13. New Dose – Non-Linear Kinetics Consideration For drugs with non‐linear pharmacokinetics in the single unit dose range of approved strengths resulting in greater than proportional increases in AUC with increasing dose • BE study should be conducted on at least the highest strength. For drugs with non‐linear dose-PK due to saturable absorption and resulting in less than proportional increases in AUC with increasing dose • BE study should be conducted on at least the lowest strength (single dose unit) For drugs with non‐linear PK due to limited solubility of the medicinal ingredient and resulting in less than proportional increases in AUC with increasing dose • BE be conducted on at least the lowest strength (single dose unit) in the fasted state and the highest strength in both the fasted and fed states © 2019 Prof. Bhaswat Chakraborty 13
  14. 14. © 2019 Prof. Bhaswat Chakraborty 14
  15. 15. In Vitro Studies Sometimes better than In Vivo Studies? Human PK in vivo studies are often presumed to serve as the “gold standard” to assess product BE of IR solid oral dosage forms It appears that in vitro studies are sometimes better than in vivo studies in assessing BE of IR solid oral dosage forms Reasons for in vitro studies to sometimes serve as the better method are that in vitro studies: (a) reduce costs, (b) more directly assess product performance, and (c) offer benefits in terms of ethical considerations Reduced costs are achieved through avoiding in vivo studies where BE is self-evident, where biopharmaceutic data anticipates BE, and where in vivo BE study type II error is high © 2019 Prof. Bhaswat Chakraborty 15
  16. 16. In Vitro Studies Sometimes better than In Vivo Studies?.. In vitro studies more directly assess product performance than do conventional human BE studies, since in vitro studies focus on comparative drug absorption from the two products, while in vivo BE testing can suffer from complications due to its indirect approach Ethics: “No unnecessary human testing should be performed” and can result in faster development Situations when in vitro test should be viewed as preferred include Class I drugs with rapid dissolution, Class III drugs with very rapid dissolution, and highly variable drugs with rapid dissolution and that are not BE problem drugs Sponsors of potential in vivo human PK BE testing should be required to justify why in vitro data is insufficient © 2019 Prof. Bhaswat Chakraborty 16
  17. 17. Challenges in BE Determination of Topical Products BE assessment of locally acting topical dosage forms using traditional PK endpoints is challenging. Historically, there were limited options for alternate approaches to PK or clinical endpoint BE studies FDA recognized the need to find more sensitive and efficient surrogate approaches to demonstrate BE for topical dermatological products. Development of new alternate BE approaches using a collective weight of evidence from in-vitro studies (e.g. IVRT, IVPT) © 2019 Prof. Bhaswat Chakraborty 17
  18. 18. In Vitro BE Option: Acyclovir Cream Formulation Q1/Q2 Sameness: The test and RLD products are qualitatively and quantitatively same. Q3 Similarity: The physicochemical properties of test and RLD products are similar. In Vitro Release Test (IVRT) Studies: The test and RLD products have an equivalent rate of acyclovir release. In Vitro Permeation Test (IVPT) Studies: The rate and extent of acyclovir permeation through excised human skin from the test and reference products are comparable. There are other options e.g., In Vivo Clinical study © 2019 Prof. Bhaswat Chakraborty 18
  19. 19. In Vitro Release Test (IVRT) An IVRT) is an established method to characterize this rate of API release and compare the underlying sameness in product quality characteristics An approach to validate an IVRT method may include • qualification of the apparatus • IVRT method development • validation of the analytical method • validation of critical parameters of the IVRT method Application of IVRT – PSGs of: • Acyclovir Ointment • Silver Sulfadiazine Cream • Acyclovir Cream • Benzyl Alcohol Lotion • … © 2019 Prof. Bhaswat Chakraborty 19
  20. 20. IVRT Method Development Justification, Qualification and Validation • Method Parameters: Information should be provided to support the selection of the IVRT apparatus, product dose amount, sampling times, stirring/agitation rate, and other parameters of the test method. • Membrane: Information on acyclovir membrane binding and chemical compatibility with relevant receptor solutions should be provided to support the inertness of the membrane selected, and information on the linearity and precision of the resulting acyclovir release rate in an IVRT should be provided to support the selection of a membrane for the test method. • Receptor Solution: Information on the empirical solubility and stability of acyclovir in the receptor solution, as well as information on the linearity and precision of the resulting acyclovir release rate in an IVRT should be provided to support the selection of a receptor solution for the test method © 2019 Prof. Bhaswat Chakraborty 20
  21. 21. IVRT Conduct The IVRT pivotal study comparing the [drug] release rates between the test and RLD products should be performed in a manner compatible with the general procedures and statistical analysis method specified in the United States Pharmacopeia (USP) General Chapter <1724>, Semisolid Drug Products – Performance Tests An IVIVC of any kind of IVRT results and In vivo BE study results should not be expected © 2019 Prof. Bhaswat Chakraborty Image courtesy of PermeGear 21
  22. 22. IVRT Method Development: Membrane Evaluation © 2019 Prof. Bhaswat Chakraborty  3 replicate membrane incubations for the IVRT duration (e.g. 6 hours) at 32°C ± 1°C  Aliquots of these solutions may be collected before and after the duration of incubation, to assess any decrease in the amount of acyclovir in solution  The recovery of acyclovir in solution is recommended to be within the range of 100% ± 5% at the end of the test duration to qualify the inertness of the membrane. 22
  23. 23. IVRT Method Development: Receptor Solubility © 2019 Prof. Bhaswat Chakraborty  Minimum solubility of acyclovir in the IVRT receptor solution should be empirically determined in triplicate with acyclovir dissolved to saturation in the receptor solution  This conc. should exceed the highest sample concentration obtained in the pivotal IVRT study, ideally by an order of magnitude or demonstrably sufficient to facilitate the linearity of the release rate for the duration of the study 23
  24. 24. © 2019 Prof. Bhaswat Chakraborty 24
  25. 25. © 2019 Prof. Bhaswat Chakraborty 25
  26. 26. Other IVRT Validation Parameters IVRT Receptor Solution Sample Analytical Method Validation: The receptor sample HPLC analysis procedures should be validated in a manner compatible with the current FDA Guidance for Industry on Bioanalytical Method Validation, and/or the ICH Harmonised Tripartite Guideline on Validation of Analytical Procedures Q2 (R1). The validation of the receptor sample analytical method should include relevant qualifications of dilution integrity as well as stability assessments with the highest relevant temperature in the receptor solution, which may be warmer than 32°C, for the duration of the IVRT study (e.g., 34°C for 6 hours). IVRT Environmental Control: Ambient laboratory temperature and humidity during the study should be monitored and reported. An environmentally controlled temperature range of 21°C ± 2°C and a humidity range of 50% ± 20% relative humidity are recommended. IVRT Linearity and Range: The linearity (r2 value) of the release rate (slope) may be calculated across the range of the sampling times, which corresponds to the IVRT study duration. Linearity may be compared within and across all IVRT runs, and a minimum r2 value ≥ 0.90 across the IVRT study duration (time range) is recommended. © 2019 Prof. Bhaswat Chakraborty 26
  27. 27. Other IVRT Validation Parameters IVRT Precision and Reproducibility: The intra-run and inter-run precision and reproducibility may be compared for the release rate (slopes) calculated for each diffusion cell. • a minimum intra-run and inter-run %CV ≤ 15% is recommended. IVRT Recovery, Mass Balance & Dose Depletion: The recovery of released acyclovir in the receptor solution may be characterized in each diffusion cell as the accumulated amount of acyclovir in the receptor solution over the IVRT duration (%acyclovir in the applied dose) IVRT Discrimination Sensitivity, Specificity and Selectivity: The IVRT method should be able to discriminate acyclovir release rates from similar formulations • one with a higher strength (e.g., 7.5%) and one with a lower strength (e.g., 2.5%) © 2019 Prof. Bhaswat Chakraborty 27
  28. 28. Other IVRT Validation Parameters.. IVRT Robustness: The IVRT method may be considered robust to a variation in the test method if the average slope of that IVRT run (under altered conditions) is within ± 15% of the average slope of the Precision & Reproducibility IVRT runs. Robustness testing may encompass variations in the IVRT method that are relevant to the apparatus and test method, for example: • Temperature variations (e.g. - 1°C and +1°C relative to 32°C ± 1°C) • Dose volume variations (e.g. +10% and -10% in the dose volume) • Receptor solution variations (e.g. change in composition and/or pH) • Mixing rate variation (e.g. differences in stirring speed, or without stirring) © 2019 Prof. Bhaswat Chakraborty 28
  29. 29. Biopharmaceutics Classification System (BCS) The BCS concept equation: J = Pw*Cw where, J is the flux across the gut wall, Pw is the permeability of the gut wall to the drug and Cw is the concentration profile at the gut wall For bioequivalence (BE), highly permeable & highly soluble drugs housed in rapidly dissolving drug products will be bioequivalent For such drugs, unless major changes are made to the formulation, dissolution data can be used as a surrogate for pharmacokinetic data to demonstrate BE of two drug products or an untested strength BCS reduces cost of scale-up and post-approval changes, multiple strength proportional formulations to certain oral drug products without compromising public safety interests © 2019 Prof. Bhaswat Chakraborty 29
  30. 30. Permeability Following methods are routinely used for determination of permeability: a) Pharmacokinetic studies in human subjects including mass balance studies[8] and absolute bioavailability (BA) studies or intestinal permeability methods b) In vivo or in situ intestinal perfusion in a suitable animal model c) In vitro permeability methods using excised intestinal tissues d) Monolayers of suitable epithelial cells e.g. Caco-2 cells or TC-7 cells © 2019 Prof. Bhaswat Chakraborty 30
  31. 31. Permeability.. In mass balance studies, unlabelled, stable isotopes or radiolabelled drug substances are used to determine the extent of drug absorption In absolute BA studies, oral BA is determined and compared against the intravenous BA as reference Intestinal perfusion models and in vitro methods are suggested for passively transported drugs. An interesting alternative to intestinal tissue models is the use of in vitro systems based on the human adenocarcinoma cell line Caco-2 • These cells serve as a model of small intestinal tissue. The differentiated cells exhibit the microvilli typical of the small intestinal mucosa and the integral membrane proteins of the brush-border enzymes • They also form the fluid-filled domes typical of a permeable epithelium • Caco-2 cell lines also have the ability to transport ions, sugars and peptides • These properties have established the Caco-2 cell line as a reliable in vitro model of the small intestine © 2019 Prof. Bhaswat Chakraborty 31
  32. 32. © 2019 Prof. Bhaswat Chakraborty 32
  33. 33. © 2019 Prof. Bhaswat Chakraborty Caco-2 cell monolayers from a) Bock et al.(14) in a 12-well, 21-day assay, b) Lentz et al. in a six-well, 4-day assay (53), and c) Withington (54) in a 24-well, 3-day assay. Triangle HP drugs, Circle LP drugs, Dashed line LP/HP boundary, Dotted line 90% absorption 33
  34. 34. The BCS Classification According to BCS, drug substances or APIs are divided into high/ low solubility and permeability classes: Class I : High Solubility - High Permeability Class II : Low Solubility - High Permeability Class III : High Solubility - Low Permeability Class IV : Low Solubility - Low Permeability In combination with the dissolution, the BCS takes into account the three major factors governing BA, viz. dissolution, solubility and permeability The BCS in accordance with WHO guideline is shown in next slide © 2019 Prof. Bhaswat Chakraborty 34
  35. 35. The BCS Classification © 2019 Prof. Bhaswat Chakraborty 35
  36. 36. Additional Considerations by WHO © 2019 Prof. Bhaswat Chakraborty BCS classification is associated with drug dissolution and absorption model, which identifies the key parameters controlling drug absorption as a set of dimensionless numbers • Absorption number, An = mean residence time/mean absorption time • Dissolution number, Dn = mean residence time/mean dissolution time • Dose number, Do = (maximum dose strength/250)/solubility Class I drugs exhibit a high absorption number and a high dissolution number. • The rate-limiting step is drug dissolution and if dissolution is very rapid then gastric emptying rate becomes the rate-determining step 36
  37. 37. Additional Considerations by WHO.. © 2019 Prof. Bhaswat Chakraborty Class II drugs have a high absorption number but a low dissolution number • In vivo drug dissolution is then a rate-limiting step for absorption except at a very high dose number • The absorption for Class II drugs is usually slower than Class I and occurs over a longer period of time For Class III drugs, permeability is a rate-limiting step for drug absorption • These drugs exhibit a high variation in the rate and extent of drug absorption • Because the dissolution is rapid, the variation is attributable to alteration of physiology and membrane permeability rather than the dosage form factors Generally, Class IV drugs exhibit problems for effective oral administration Examples of drugs for different classes are given in Table in next slide 37
  38. 38. © 2019 Prof. Bhaswat Chakraborty 38
  39. 39. © 2019 Prof. Bhaswat Chakraborty FITC-insulin transport across Caco-2 monolayers. (a) Time-course study of FITC-insulin transport (mg) at different loading concentrations. FITC-insulin was loaded in apical chambers at 0.05 (open circles), 0.15 (filled circles), 0.3 (squares), and 0.6 (triangles) mg/well respectively; and permeation was measured by measuring the fluorescence in samples collected from basolateral chamber at different time-points up to 5 hrs. (b) % FITC- insulin transport across Caco-2 monolayers. Data represent mean ± SD (n = 3). 39
  40. 40. © 2019 Prof. Bhaswat Chakraborty Sulforhodamine-B transport across Caco-2 monolayers. (a) Time-course study of sulforhodamine-B transport (mg) at different loading concentrations. Sulforhodamine-B was loaded in apical chambers at 0.05 (open circles), 0.15 (filled circles), 0.3 (squares), and 0.6 (triangles) mg/well respectively; and apical-to-basolateral permeation was measured by measuring the fluorescence in samples collected from basolateral chamber at different time- points up to 5 hrs. (b) % Sulforhodamine-B transport across Caco-2 monolayers over of 5 hrs of incubation. Data represent mean ± SD (n = 3). 40
  41. 41. Innovative Model for Future ANDAs Source: Robert Lionberger. Application of PBPK models in assessment of bioequivalence (AAPS Annual Meeting 2014) © 2019 Prof. Bhaswat Chakraborty Source: Robert Lionberger. Application of PBPK models in assessment of bioequivalence (AAPS Annual Meeting 2014) 41
  42. 42. © 2019 Prof. Bhaswat Chakraborty 42
  43. 43. References Canadian bioavailability and bioequivalence guidelines https://www.canada.ca/en/health-canada/services/drugs-health- products/drug-products/applications-submissions/guidance- documents/bioavailability-bioequivalence.html https://www.fda.gov/downloads/Drugs/NewsEvents/UCM591918.pd f Kregar et al, Int J Pharm. 2015 May 15;485(1-2):202-14. doi: 10.1016/j.ijpharm.2015.03.018. Epub 2015 Mar 12. Gupta et al. PLOS One https://doi.org/10.1371/journal.pone.0057136 © 2019 Prof. Bhaswat Chakraborty 43
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