Similar pharmacokinetics and pharmacodynamics of a new biosimilar and reference insulin aspart in healthy Chinese males

Hui, Lam; Yu, Han‐Qing; Sun, Lisha; Qiao, Jingtao; Wan, Sainan; Li, Shuang; Li, Jiaqi; Tan, Huiwen; Yu, Yerong

doi:10.1038/s41598-021-88782-8

Cited by 4 publications

(4 citation statements)

References 21 publications

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“…One of the important limitations of this approach is the initial variability of the tested parameters. In this case, the CV of

{\rm{AUC}}_{{\rm{GIR}}_{0 - {\rm{t}}}}

was 31.7%, which is close to the values obtained in a similar clamp study for soluble IAsp (27% and 31% for the reference and test products, respectively) on a sample of 30 healthy volunteers, in which biosimilarity by pharmacodynamics was achieved 25 . Data on the CV for BIAsp 30 were not found in other clamp studies, but presumably BIAsp 30 variability may be greater than soluble IAsp variability.…”

Section: Discussionsupporting

confidence: 80%

“…In this case, the CV of AUC GIR 0−t was 31.7%, which is close to the values obtained in a similar clamp study for soluble IAsp (27% and 31% for the reference and test products, respectively) on a sample of 30 healthy volunteers, in which biosimilarity by pharmacodynamics was achieved. 25 Data on the CV for BIAsp 30 were not found in other clamp studies, but presumably BIAsp 30 variability may be greater than soluble IAsp variability. In addition, initially the lower limit of AUC GIR 0−t was outside the required interval by only 0.5%.…”

Section: Discussionmentioning

confidence: 82%

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PKPD Modeling and Simulations to Support Biosimilar Development of Biphasic Insulin Aspart 30

Petrov¹,

Zinnatulina²,

Drai³

et al. 2022

Clinical Pharm in Drug Dev

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This paper presents an analysis of data from a comparative study of biosimilarity in terms of pharmacokinetics and pharmacodynamics in healthy volunteers using a hyperinsulinemic euglycemic clamp for reference and test biphasic insulin aspart 30 (BIAsp 30). As a result of the study, one of the secondary pharmacodynamic (PD) endpoints did not satisfy the classical criterion of 80%-125% (the lower limit for PD parameter area under the glucose infusion rate-time curve [AUC GIR 0−t ] turned out to be 79.5%). The main hypothesis explaining this result is that the sample size is insufficient to conduct a PD test with 90% statistical power, since the sample size has been calculated based on the coefficient of variation (CV) of pharmacokinetic (PK) parameters. To test this hypothesis, population PKPD (popPKPD) modeling and subsequent simulations of the required number of PD profiles were used. Two popPKPD models were constructed (a one-compartment double simultaneous absorption model for PK and an effect compartment E max model for PD) to describe the PKPD data of reference and test insulins. As a result, using real data along with model-based simulation data, a biosimilarity test for PD was performed, and the lower limit for AUC GIR 0−t became 82.6%, while the CV decreased from 31.7% to 24.1%. Thus, popPKPD modeling and simulations have been shown to be effective in interpreting and supporting the results of clinical biosimilarity trials.

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“…One of the important limitations of this approach is the initial variability of the tested parameters. In this case, the CV of

{\rm{AUC}}_{{\rm{GIR}}_{0 - {\rm{t}}}}

Section: Discussionsupporting

confidence: 80%

Section: Discussionmentioning

confidence: 82%

PKPD Modeling and Simulations to Support Biosimilar Development of Biphasic Insulin Aspart 30

Petrov¹,

Zinnatulina²,

Drai³

et al. 2022

Clinical Pharm in Drug Dev

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“…This study was a retrospective study, and we collected the data from the database of 2 clinical trials (CTR20160095, CTR20180517) performed from 2016 to 2018. These 2 clinical trials aimed to evaluate the PK and PD similarity of the IAsp biosimilar produced by Zhuhai United Laboratories Co., Ltd, 20 and Yichang HEC Changjiang Pharmaceutical Co., Ltd, 21 respectively, with NovoRapid. In the present study, the subjects would be assigned to group A if the highest postdosing C‐peptide ([CP postdosing ] max ) level was higher than basal C‐peptide (CP baseline ), and the subjects whose (CP postdosing ) max level did not exceed baseline would be allocated to group B.…”

Section: Methodsmentioning

confidence: 99%

Effects of Unsuppressed Endogenous Insulin on Pharmacokinetics and/or Pharmacodynamics of Study Insulin in the Healthy: A Retrospective Study

Liu

Sun

et al. 2022

Clinical Pharm in Drug Dev

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C‐peptide, a marker of endogenous insulin, should be consistently inhibited during euglycemic clamping, while an elevated postdosing C‐peptide (CPpostdosing) is not an occasional phenomenon. This was a retrospective study that included 33 men who underwent a manual euglycemic clamp with a subcutaneous injection of insulin aspart (IAsp) aiming to describe the effects of insufficient suppression of endogenous insulin on estimates of the pharmacokinetics and pharmacodynamics of injected insulin. The time profiles of whole blood glucose, human insulin, glucose infusion rate (GIR), and C‐peptide were recorded. The subjects were divided into 2 groups at a ratio of 2:1: group A ([CPpostdosing]max>baseline CP [CPbaseline]), group B ([CPpostdosing]max ≤ CPbaseline). The endogenous insulin was approximately equal to the measured value of human insulin or calculated from the C‐peptide. The basal glucose, CPbaseline, basal human insulin, homeostatic model assessment of insulin resistance, IAsp dose, and demographic statistics were all comparable between the 2 groups except the “clamped” glucose. The average clamped glucose was 99.7% (group A) and 94.9% (group B) of baseline. After correction for clamped glucose, GIR area under the concentration‐time curve from time 0 to 8 hours was higher in group A (P < .05) under comparable IAsp exposure. Endogenous insulin area under the concentration‐time curve from time 0 to 8 hours calculated from C‐peptide was different from that measured from human insulin in group A (P < .05), whereas no statistical difference between these measures was observed in group B. Hence, blood glucose should be controlled below the baseline to ensure the inhibition of endogenous insulin. Unsuppressed endogenous insulin may contribute to observed GIR, and the endogenous insulin–corrected pharmacokinetics estimated by C‐peptide may be inaccurate with insufficient endogenous insulin suppression.

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“…In conclusion, peripheral C-peptide is a more appropriate and accurate marker for assessing endogenous insulin secretion ( Alieva et al, 1985 ; Jones and Hattersley, 2013 ). A previous study indicated that a C-peptide suppression of over 50% would have been more powerful for indicating adequate restriction of endogenous insulin ( Liu et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Reduction in C-Peptide Levels and Influence on Pharmacokinetics and Pharmacodynamics of Insulin Preparations: How to Conduct a High-Quality Euglycemic Clamp Study

Tao

Zhu

et al. 2021

Front. Pharmacol.

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Objective: The aim of the study was to investigate the different extent of inhibition of endogenous insulin secretion by the reduction of C-peptide levels in an euglycemic clamp study and its effects on the evaluation of pharmacokinetics, pharmacodynamics of insulin preparations, and quality of clamp study to determine the best reduction range of C-peptide levels.Methods: Healthy Chinese male volunteers were enrolled and underwent a single-dose euglycemic clamp test. Participants were subcutaneously injected with long-acting insulin glargine (0.4 IU/kg). Blood samples were collected pretest and up to 24 h post-test to assess pharmacokinetics (PK), pharmacodynamics (PD), and C-peptide levels.Results: We divided the 39 volunteers enrolled in the study into three groups according to the reduction of C-peptide levels: group A (ratio of C-peptide reduction <30%, n = 13), group B (ratio of C-peptide reduction between ≥ 30% and <50%, n = 15), and group C (ratio of C-peptide reduction ≥50%, n = 11); there were significant differences in the three groups (p= 0.000). The upper and lower limits of blood glucose oscillation in group C was statistically lower than the other groups, the range of oscillating glucose levels in group C was −17.0 ± 6.6% to −1.1 ± 6.7%. The AUC0–24 h in groups A, B, and C were 9.7 ± 2.2, 11.0 ± 2.9, and 11.9 ± 2.1 ng/ml × min, respectively, which indicated an increasing trend in the three groups (Ptrend = 0.041). For quality assessment, the average glucose (p = 0.000) and MEFTG (p = 0.001) levels in three groups were significantly different.Conclusion: The different extent of inhibition of endogenous insulin will influence the PK/PD of insulin preparations and the quality of the euglycemic clamp. Furthermore, the ratio of C-peptide reduction should be above 50% to free from the interference of endogenous insulin, and the range of blood glucose levels should be consistently maintained at −10% to 0 in the euglycemic clamp.

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Similar pharmacokinetics and pharmacodynamics of a new biosimilar and reference insulin aspart in healthy Chinese males

Cited by 4 publications

References 21 publications

PKPD Modeling and Simulations to Support Biosimilar Development of Biphasic Insulin Aspart 30

PKPD Modeling and Simulations to Support Biosimilar Development of Biphasic Insulin Aspart 30

Effects of Unsuppressed Endogenous Insulin on Pharmacokinetics and/or Pharmacodynamics of Study Insulin in the Healthy: A Retrospective Study

Reduction in C-Peptide Levels and Influence on Pharmacokinetics and Pharmacodynamics of Insulin Preparations: How to Conduct a High-Quality Euglycemic Clamp Study

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