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Wen YF, Ji P, Schrieber SJ, Rathi S, McGuirt D, Liu J, Chen J, Wang YM, Doddapaneni S, Sahajwalla C. Evaluation of Truncated AUC as an Alternative Measure to Assess Pharmacokinetic Comparability in Bridging Biologic-Device Using Prefilled Syringes and Autoinjectors. J Clin Pharmacol 2023; 63:1417-1429. [PMID: 37507728 DOI: 10.1002/jcph.2322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 07/24/2023] [Indexed: 07/30/2023]
Abstract
Pharmacokinetic (PK) comparisons between therapeutic biologics have largely been based on the total area under the concentration-time curve (AUC) and the maximum concentration (Cmax ). For biologics with a long half-life, a PK comparability study may be long in duration and costly to conduct. The goal of this study was to evaluate whether a truncated AUC (tAUC) can be used to assess PK comparability when bridging prefilled syringe (PFS) and autoinjector (AI) treatment options for biologics with a long half-life. Fifteen biologics license applications (BLAs) were included to determine the concordance and geometric percent coefficient of variation (%CV) between tAUCs evaluated on days 7, 14, 21, and 28 and AUC evaluated to infinity (AUC0-inf ). Concordance is established if the tAUCs are comparable with AUC0-inf . Trial simulation was performed to examine the effect of the absorption rate constant (ka ) and sample size on the concordance of tAUCs. The tAUCs evaluated on day 14, 21, and 28 had 100% concordance with AUC0-inf for all 15 BLAs. The concordance of tAUC evaluated at day 7 was 87.5%. Based on the trial simulation, tAUC evaluated to day 28 post-dose can achieve high concordance (≥85%) for biologics exhibiting linear or nonlinear elimination with a ka of ≥0.1/day and with a sample size of 70 subjects per arm. tAUC appears to be a promising alternative PK measure, relative to AUC0-inf , for PK comparability assessments.
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Affiliation(s)
- Ya-Feng Wen
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Ping Ji
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Sarah J Schrieber
- Office of Therapeutic Biologics and Biosimilars, Office of New Drugs, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Sneha Rathi
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Delaney McGuirt
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Jiang Liu
- Division of Pharmacometrics, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Jianmeng Chen
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Yow-Ming Wang
- Therapeutic Biologics Program, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Suresh Doddapaneni
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Chandrahas Sahajwalla
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
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Fisher D, Kramer W, Burmeister Getz E. Evaluation of a Scenario in Which Estimates of Bioequivalence Are Biased and a Proposed Solution: tlast (Common). J Clin Pharmacol 2015; 56:794-800. [PMID: 26479406 PMCID: PMC5064724 DOI: 10.1002/jcph.663] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2015] [Accepted: 10/14/2015] [Indexed: 11/10/2022]
Abstract
In bioequivalence (BE) testing, it is the convention to identify tlast separately for each concentration‐vs‐time profile. Within‐subject differences in tlast between treatments can arise when assay sensitivity is reached during washout, causing profiles to fall below the limit of quantitation (LOQ) at different sampling times. The resulting tlast difference may be systematic, due to true differences in exposure, and/or random, due to measurement noise. The conventional profile‐specific tlast approach assumes that concentrations in the terminal phase are sufficiently low that use of different tlast values between treatments within a subject causes negligible bias in the AUC0‐t geometric mean ratio (GMR). Here we investigate the validity of this assumption. Using concentration‐vs‐time data following oral inhalation of 50 μg salmeterol as an example data set, we conducted simulations to evaluate whether use of different test/reference AUC timeframes arising from a systematic difference in exposure causes sufficient AUC0‐t GMR bias to influence the determination of BE. To ensure that results would be relevant to BE testing, we considered only test/reference relative systemic exposures within the BE window (80.00%–125.00%). We show that use of conventional profile‐specific tlast exaggerates true differences in systemic exposure; the resulting AUC0‐t ratios are biased from true relative exposure by an amount large enough to impact the conclusion of BE. Thus, drugs whose concentrations fall below LOQ during washout may fail BE inappropriately using conventional methods. AUC0‐t calculated over a common timeframe within each subject (tlast[common]) minimizes this bias and harmonizes the statistical analysis of BE.
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Moreno I, Ochoa D, Román M, Cabaleiro T, Abad-Santos F. Effect of Truncating AUC at 12, 24 and 48 hr When Evaluating the Bioequivalence of Drugs with a Long Half-Life. Basic Clin Pharmacol Toxicol 2015; 118:53-7. [PMID: 26086613 DOI: 10.1111/bcpt.12432] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2015] [Accepted: 06/15/2015] [Indexed: 11/26/2022]
Abstract
Bioequivalence studies of drugs with a long half-life require long periods of time for pharmacokinetic sampling. The latest update of the European guideline allows the area under the curve (AUC) truncated at 72 hr to be used as an alternative to AUC0-t as the primary parameter. The objective of this study was to evaluate the effect of truncating the AUC at 48, 24 and 12 hr on the acceptance of the bioequivalence criterion as compared with truncation at 72 hr in bioequivalence trials. The effect of truncated AUC on the within-individual coefficient of variation (CVw) and on the ratio of the formulations was also analysed. Twenty-eight drugs were selected from bioequivalence trials. Pharmacokinetic data were analysed using WinNonLin 2.0 based on the trapezoidal method. Analysis of variance (ANOVA) was performed to obtain the ratios and 90% confidence intervals for AUC at different time-points. The degree of agreement of AUC0-72 in relation to AUC0-48 and AUC0-24, according to the Landis and Koch classification, was 'almost perfect'. Statistically significant differences were observed when the CVw of AUC truncated at 72, 48 and 24 hr was compared with the CVw of AUC0-12. There were no statistically significant differences in the AUC ratio at any time-point. Compared to AUC0-72, Pearson's correlation coefficient for mean AUC, AUC ratio and AUC CVw was worse for AUC0-12 than AUC0-24 or AUC0-48. These preliminary results could suggest that AUC truncation at 24 or 48 hr is adequate to determine whether two formulations are bioequivalent.
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Affiliation(s)
- Isabel Moreno
- Clinical Pharmacology Service, Hospital Universitario de la Princesa, Instituto Teófilo Hernando, University Autónoma de Madrid (UAM), Instituto de Investigación Sanitaria Princesa (IP), Madrid, Spain
| | - Dolores Ochoa
- Clinical Pharmacology Service, Hospital Universitario de la Princesa, Instituto Teófilo Hernando, University Autónoma de Madrid (UAM), Instituto de Investigación Sanitaria Princesa (IP), Madrid, Spain
| | - Manuel Román
- Clinical Pharmacology Service, Hospital Universitario de la Princesa, Instituto Teófilo Hernando, University Autónoma de Madrid (UAM), Instituto de Investigación Sanitaria Princesa (IP), Madrid, Spain
| | - Teresa Cabaleiro
- Clinical Pharmacology Service, Hospital Universitario de la Princesa, Instituto Teófilo Hernando, University Autónoma de Madrid (UAM), Instituto de Investigación Sanitaria Princesa (IP), Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Madrid, Spain
| | - Francisco Abad-Santos
- Clinical Pharmacology Service, Hospital Universitario de la Princesa, Instituto Teófilo Hernando, University Autónoma de Madrid (UAM), Instituto de Investigación Sanitaria Princesa (IP), Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Madrid, Spain
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