Background: To overcome the complicated mixing procedures required in the use of insulin formulations, premixed formulations consisting of rapid-acting and intermediate-type insulin in various mixing proportions have been developed. Biphasic insulin aspart 50 (BIAsp50) and 30 (BlAsp30) are 2 premixed formulations containing the active ingredient insulin aspart (IAsp) and consisting of a rapid-acting component soluble IAsp) and intermediate-acting component (protamine-crystallized protracted IAsp) in ratios of 50/50 and 30/70, respectively. These formulations are provided with the expectation that BIAsp30 and BIAsp50 will be beneficial for patients needing to improve their postprandial blood glucose control without changing their dietary habits and lifestyles. BIAsp30 has been widely used in medical practice, whereas BIAsp50 is being investigated in clinical trials.
Objective: The aim of this study was to compare the pharmacokinetic (PK) and pharmacodynamic (PD) profiles of BIAsp50 (test) and BIAsp30 (reference) after single-dose SC injection in patients with type 2 diabetes mellitus.
Methods: This single-center, randomized, doubleblind, 2-period, crossover trial was conducted at the H.E.C. Science Clinic, Yokohama, Japan. Male and female patients aged > or = 20 years with a > or = 1 year history of type 2 diabetes were eligible. Patients were randomly assigned to 1 of 2 treatment sequences: group A received BIAsp30 in period 1 and BIAsp50 in period 2; group B received BIAsp50 in period 1 and BIAsp30 in period 2. All treatments were administered as an SC injection of a single dose (0.3 U/kg). The study periods were separated by a washout period of 4 to 21 days. For PK analysis of IAsp (maximum serum IAsp concentration [C(max,IAsp); primary end point], AUC of serum IAsp 0 to 120, 240, and 480 minutes after administration [AUC(0-120 min,IAspl), AUC(0-240 min,IAsp), and AUC(0-480 min,IAsp5) respectively], and time to (Cmax,IAsp) [T(max,IAsp)] ), blood samples were drawn immediately before (baseline) and at prespecified time points over 480 minutes after administration. The PD profiles of BIAsp50 and BIAsp30 were also examined by comparing the time course of the glucose infusion rate (GIR) using the euglycemic clamp technique. The PD end points were AUC of GIR 0 to 120 minutes after administration (AUC(0-120 min,GIR)), maximum GIR (GIR(max)), and time to GIRmax (T(max,GIR)). Tolerability was assessed using physical examination, including vital sign measurement, electrocardiography, body weight, adverse events (AEs), and clinical laboratory analysis (hematology and serum biochemistry).
Results: Six men and 4 women were enrolled in the study (mean age, 62.4 years; mean body weight, 58.3 kg; mean body mass index, 22.22 kg/m(2); mean duration of diabetes, 9.53 years; and mean glycosylated hemoglobin concentration, 6.07%). Mean(Cmax,IAsp) with BIAsp50 was 63% higher than that for BIAsp30 (P < 0.002). The BIAsp50/BIAsp30 ratio with AUC(0-120 min,IAsp) was 1.68 (95% CI, 1.31-2.14). The BIAsp50/BIAsp30 ratiofor AUC(0-120 min,GIR) was 1.31 (95% CI, 1.02-1.68). A total of 9 AEs were reported in 5 patients, but none of the AEs were considered related to the study drug.
Conclusion: In this small PK/PD study in adults with type 2 diabetes in Japan, mean C(max,IAsp) was significantly higher with BIAsp50 than with BIAsp30, and AUC(0-120 min,IAsp) and AUC(0-120 min,GIR) were higher with BIAsp50 than with BIAsp30.
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http://dx.doi.org/10.1016/j.clinthera.2007.05.017 | DOI Listing |
Nat Methods
January 2025
Broad Institute of MIT and Harvard, Cambridge, MA, USA.
A key challenge of the modern genomics era is developing empirical data-driven representations of gene function. Here we present the first unbiased morphology-based genome-wide perturbation atlas in human cells, containing three genome-wide genotype-phenotype maps comprising CRISPR-Cas9-based knockouts of >20,000 genes in >30 million cells. Our optical pooled cell profiling platform (PERISCOPE) combines a destainable high-dimensional phenotyping panel (based on Cell Painting) with optical sequencing of molecular barcodes and a scalable open-source analysis pipeline to facilitate massively parallel screening of pooled perturbation libraries.
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January 2025
Department of Endocrinology and Metabolism, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China.
With the rapid advancement of proteomics, numerous scholars have investigated the intricate relationships between plasma proteins and various diseases. Therefore, this study aims to elucidate the relationship between BDH1 and type 2 diabetes using Mendelian randomization (MR) and to identify novel targets for the prevention and treatment of type 2 diabetes through proteomics. This study primarily employed the Mendelian Randomization (MR) method, leveraging genetic data from numerous large-scale, publicly accessible genome-wide association studies (GWAS).
View Article and Find Full Text PDFIntroduction: The most frequent form of diabetes in pediatric patients is polygenic autoimmune diabetes (T1D), but single-gene variants responsible for autoimmune diabetes have also been described. Both disorders share clinical features, which can lead to monogenic forms being misdiagnosed as T1D. However, correct diagnosis is crucial for therapeutic choice, prognosis and genetic counseling.
View Article and Find Full Text PDFBr J Nutr
January 2025
Laboratório de Nutrição e Metabolismo, Faculdade de Nutrição, Universidade Federal de Alagoas, Maceió, Brazil.
To determine the prevalence of FA in individuals with type 2 diabetes and to assess the association between FA and type 2 diabetes. MEDLINE, EMBASE, Web of Sciences, Latin American and Caribbean Literature in Health Sciences, ScienceDirect, Scopus, and PsycINFO were searched until November 2024. This study was registered with PROSPERO (CRD42023465903).
View Article and Find Full Text PDFSLAS Discov
January 2025
Bonds Biosystems, 27 Strathmore Rd, Natick, MA, USA. Electronic address:
Obesity and type 2 diabetes (T2D) are strongly linked to abnormal adipocyte metabolism and adipose tissue (AT) dysfunction. However, existing adipose tissue models have limitations, particularly in the stable culture of fat cells that maintain physiologically relevant phenotypes, hindering a deeper understanding of adipocyte biology and the molecular mechanisms behind differentiation. Current model systems fail to fully replicate in vivo metabolism, posing challenges in adipose research.
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