Drug Database
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human insulin (Biohulin)

✓ Approved

Novo Nordisk A/S · INSR · Small Molecule

What is human insulin?

human insulin is a small molecule developed by Novo Nordisk A/S. It is approved for therapeutic indications.

Drug Profile

Brand NamesBiohulin
CompanyNovo Nordisk A/S
Drug ClassSmall Molecule, Polypeptide
Molecular TargetINSR
StatusApproved
Sources: ClinicalTrials.gov, Novo Nordisk A/S

Mechanism of Action

Molecular Targets

human insulin acts on 1 molecular target:

INSRinsulin receptor (CD220, HHF5)
Want deeper analysis?Noah AI can explain complex mechanisms and compare to similar drugs.

Therapeutic Indications

human insulin is developed for 1 unique indication across 1 therapeutic area.

Therapeutic AreaConditionPhase
InvestigationsGlucose tolerance test abnormal✓ Approved

Related Research Articles

PubMedIranian journal of pharmaceutical research : IJPR2026-09-20

Lyoniresinol Improves Insulin Sensitivity and Induces White-to-Beige Adipose Tissue Conversion in Obese Rats: Associated with JNK/PI3K/mTOR Pathway Modulation.

Lei Wen W, Tripathi Alok A, Hu Shuwen S

Obesity contributes to multiple chronic diseases and remains a critical global health challenge. This study evaluated the therapeutic effects of lyoniresinol on high-fat diet-induced obesity and its underlying molecular mechanisms. Network pharmacology was used to identify potential targets of lyoniresinol in obesity treatment, followed by validation using molecular docking. High-fat diet-induced obese rats received lyoniresinol (30 mg/kg/day) for six weeks. The primary efficacy endpoints were insulin sensitivity, assessed by the oral glucose tolerance test (OGTT), insulin tolerance test (ITT), fasting glucose, and fasting insulin, and adiposity measures, including body weight and regional fat mass. The key secondary endpoint was uncoupling protein 1 (UCP1) expression in adipose tissue, evaluated by Western blotting and immunohistochemistry. Mechanistic validation comprised analysis of the phosphorylation status of c-Jun N-terminal kinase (JNK), phosphatidylinositol 3-kinase (PI3K), and mammalian target of rapamycin (mTOR) by Western blotting. Exploratory assessments included serum lipid profiles, inflammatory cytokines, oxidative stress biomarkers, and histopathological examination. Network pharmacology identified 50 shared targets between lyoniresinol and obesity. Molecular docking indicated favorable binding to JNK, PI3K, and mTOR. For the primary endpoints, lyoniresinol treatment was associated with reduced body weight gain, restored normoglycaemia, enhanced insulin sensitivity, and decreased regional adipose tissue mass. For the key secondary endpoint, UCP1 expression was upregulated, suggesting the browning of white adipose tissue. For the exploratory endpoints, lyoniresinol was associated with improved dyslipidaemia, reduced oxidative stress, suppressed pro-inflammatory cytokines and C-reactive protein (CRP), and attenuated adipocyte hypertrophy. For mechanistic validation, lyoniresinol treatment was associated with suppressed JNK phosphorylation and activation of PI3K/mTOR signaling in adipose tissue, suggesting potential involvement of the JNK/PI3K/mTOR pathway in these effects. Based on the primary efficacy endpoints, lyoniresinol was associated with improved insulin sensitivity and reduced adiposity in obese rats. The key secondary endpoint (UCP1 upregulation) and mechanistic validation (altered JNK/PI3K/mTOR phosphorylation) further support its association with the browning of white adipose tissue. These findings suggest that lyoniresinol may represent a multi-target candidate for further investigation in obesity-related metabolic disorders; however, the precise molecular mechanisms require additional validation.

PMID 42763601
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PubMedCureus2026-09-20

Edinburgh University Solution of Lime (EUSOL) Versus Platelet-Derived Growth Factor Dressing for Wound Contraction in Grade II Wagner Diabetic Foot Ulcers: A Randomized Controlled Trial.

Batool Fizza F, Munawwar Fasiha F, Shaukat Hassan H, Janjua Atif A AA et al.

Background Diabetic foot ulcers remain a leading cause of lower-limb amputation worldwide, and wound management is especially difficult in resource-limited settings where older antiseptic agents such as Edinburgh University Solution of Lime (EUSOL) are still in routine use. This trial compared EUSOL dressing with platelet-derived growth factor (PDGF) dressing for wound contraction in Grade II Wagner diabetic foot ulcers. Methodology In this randomized controlled trial, 120 patients aged 30 to 70 years with Grade II Wagner diabetic foot ulcers were assigned in a 1:1 ratio to daily EUSOL dressing or PDGF dressing applied every fourth day for four weeks after debridement and infection control. Wound healing was defined as a reduction in ulcer area of at least 50% from baseline at four weeks. A multivariate logistic regression model examined treatment group, age, sex, body mass index (BMI), diabetes duration, and antidiabetic therapy as predictors of healing. Results Patients averaged 49.8 ± 10.2 years of age and a BMI of 27.1 ± 3.45 kg/m²; 58.3% were male. Seventy-eight patients (65%) used oral hypoglycemic agents alone, while 42 (35%) required insulin. Seventy-one patients (59.2%) had diabetes for more than 10 years. Wound contraction occurred in 20 of 60 (33.3%) patients on EUSOL versus 44 of 60 (73.3%) on PDGF (P < 0.001). PDGF remained a strong independent predictor of healing on multivariate analysis (adjusted odds ratio (OR) 6.14, 95% confidence interval (CI) 2.69-14.02, P < 0.001), as did insulin therapy (adjusted OR 2.48, 95% CI 1.10-5.59, P = 0.028). Conclusions PDGF dressing produced substantially better wound contraction than EUSOL in Grade II diabetic foot ulcers, an effect that persisted after adjustment for the usual confounders. Insulin use was independently linked to better healing, pointing to glycemic management as a modifiable lever alongside dressing choice. Confirmation in multicenter trials with longer follow-up, blinded outcome assessment, and cost data would strengthen the case for wider adoption of PDGF-based dressings in similar settings.

PMID 42763719
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PubMedEuropean journal of nutrition2026-09-20

Serum lipidomic profiles associated with Mediterranean diet in overweight and obese breast cancer survivors: an exploratory study.

Lee Jae Hwa JH, Park Ji Seo JS, Park Jin Ju JJ, Lee Ji-Won JW et al.

Among breast cancer (BC) survivors, overweight and obesity increase the risk of recurrence, underscoring the importance of dietary strategies for weight management. The Mediterranean diet (MD) can promote weight loss and reduce lipid levels. Analyzing alterations at the lipid species level can provide more detailed insights into the metabolic benefits associated with the MD. This study aimed to explore lipid remodeling associated with MD adherence in BC survivors through comprehensive lipidomic analysis. This exploratory ancillary study was conducted as non-randomized, non-controlled pre-post intervention analysis of serum samples collected before and after an 8-week MD intervention from 12 overweight or obese BC survivors. Fasting paired serum samples (n = 24) were used to profile lipid species using ultra-high-performance liquid chromatography-tandem mass spectrometry in both positive and negative ionization modes. Multivariate and correlation analyses were used to assess overall lipidomic alterations. Participants were further classified into maintainer or improver subgroups based on changes in their Mediterranean diet score (MDS), and subgroup-specific lipidomic responses to the MD intervention were examined. Participants showed significant reductions in body weight, waist circumference, and clinical triglyceride levels, along with increased quantitative insulin sensitivity check index and MDS following the MD intervention. Forty-three putative lipid species were identified, predominantly characterized by reductions in triacylglycerols (TGs) enriched with saturated fatty acids. TG 16:0_18:0_18:0 and TG 16:0_18:1_24:0 exhibited strong negative correlations with MDS and positive correlations with insulin resistance markers. Significant lipid remodeling was observed only in the maintainer group. In this exploratory study, adherence to an 8-week MD was associated with changes in body composition, metabolic markers, and the serum lipidomic profile in overweight and obese BC survivors. These findings provide preliminary evidence that MD adherence may be associated with lipidomic and metabolic changes in BC survivors, warranting confirmation in larger, controlled studies. http://clinicaltrials.gov , NCT03581630.

PMID 42763329
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PubMedIranian journal of pharmaceutical research : IJPR2026-09-20

ALDH1A3 Inhibition by Prosopis farcta Phytochemicals: A Computational Exploration of a Potential Antidiabetic Mechanism.

Torabi Nilufar N, Taheripak Gholamreza G, Najjar Nabaa N, Nooraniyan Esfehani Mohammad Amin MA et al.

Diabetes mellitus is a chronic condition caused by insufficient insulin secretion or impaired insulin action. Traditionally, pancreatic β-cell loss has been attributed to hyperglycemia-induced apoptosis. However, more recent evidence indicates that β-cells can also undergo dedifferentiation, a process in which they lose their specialized identity and revert to a precursor-like state. ALDH1A3 has been reported as a marker associated with dedifferentiated β-cells in diabetes, making it a potential molecular target for studies of β-cell identity and their redifferentiation. This study aimed to evaluate the potential interactions between phytochemicals in Prosopis farcta root extract and ALDH1A3 using an in silico workflow that included molecular docking, molecular dynamics simulations, and Molecular Mechanics Generalized Born Surface Area (MM-GBSA) analysis. This in silico study evaluated phytochemicals reported in the root extract of Prosopis farcta. The three-dimensional structures of the phytochemicals were downloaded from the PubChem database in SDF format. Molecular docking and molecular dynamics simulations were performed using PyRx and GROMACS, respectively. MM-GBSA analysis was performed using gmx_MMPBSA. Docking analysis suggested that several Prosopis farcta phytochemicals could interact with functionally relevant regions of ALDH1A3, including the retinal- and NAD-binding regions. Among the evaluated compounds, luteolin 7-O-glucoside and luteolin 3'-glucoside exhibited favorable docking scores and stable interaction profiles in subsequent MD and MM-GBSA analyses. These findings suggest that these compounds may form energetically favorable interactions with ALDH1A3. Among the evaluated Prosopis farcta phytochemicals, luteolin 7-O-glucoside and luteolin 3'-glucoside emerged as the most promising computational candidates for further ALDH1A3-focused studies. These findings provide an initial basis for investigating whether interaction with ALDH1A3 may represent a potential mechanism contributing to the reported antidiabetic effects of Prosopis farcta extract and its possible relevance to β-cell dysfunction in diabetes. However, experimental validation is essential to confirm ALDH1A3 inhibition, its effects on β-cell redifferentiation, and antidiabetic potential.

PMID 42763645
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PubMedZhongguo yi xue ke xue yuan xue bao. Acta Academiae Medicinae Sinicae2026-09-20

Standards and Guidance for Transparent Disclosure of Human-Artificial Intelligence Collaboration Content in Medical Research (2026).

Medical Journals Committee of the Society of China University Journals

The rapid iteration of artificial intelligence (AI) tools is propelling medical research into a new phase characterized by human-AI collaboration.In the course of this process,AI has evolved from an external instrument into a functional component embedded within research workflows.As the collaborative boundary between human researchers and AI becomes increasingly ambiguous,governance challenges have grown increasingly salient.Concurrently,there remains a lack of internationally harmonized standards for the declaration of AI-assisted content,giving rise to notable disclosure gaps and implementation disconnects both domestically and abroad.To address these issues,the Professional Committee of Medical Journals of the Society of China University Journals assembled a multidisciplinary expert team covering fields such as medicine,biostatistics,epidemiology,medical ethics,scientific journal editing,and medical AI technology.Employing a modified Delphi method,the team conducted three rounds of online surveys and two consensus meetings.Drawing upon evidence from policy surveys of 1 692 medical journals,position statements from international organizations such as the International Committee of Medical Journal Editors,AI policy texts from the world's major academic publishers (Elsevier,Springer Nature,Wiley,Taylor & Francis,SAGE,etc.),and comparative studies on AI detection tool performance,the team ultimately formulated ten recommendations addressing core issues in medical publishing.This guidance emphasizes the core principles of transparent disclosure,human accountability,risk stratification,and technology-assisted oversight,aiming to fully harness the benefits of AI technology while upholding the bottom line of academic integrity.It provides a systematic framework for the standardized disclosure of human-AI collaboration content in medical research and offers actionable normative guidance for researchers,journal editors,peer reviewers,and academic institutions.

PMID 42763420
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PubMedOncogene2026-09-20

Beyond the blood-brain barrier: humanised mice, the missing link in glioblastoma research.

Shirazi Nia Reza R, Lu Jian J, De Vega Daniel D, Poudine Niloufar N et al.

Glioblastoma (GBM) remains a major challenge in neuro-oncology, associated with a high rate of mortality despite decades of intensive research and therapeutic advancements, underscoring the urgent need for innovative preclinical platforms that can more accurately recapitulate the biological and pathological features of human disease. While conventional animal models have contributed to our understanding of GBM biology and the evaluation of treatment efficacy, they fail to capture the full complexity and heterogeneity of the tumour microenvironment (TME). Ex vivo models are associated with certain advantages in this context; however, they can not mirror the complex dynamic and multicellular interactions present in living organisms, particularly the critical treatment barriers unique to the central nervous system: the blood-brain barrier (BBB), blood-cerebrospinal fluid barrier (BCSFB) and blood-meningeal barrier (BMB). In response to these limitations, humanised mouse models have emerged as an advanced platform capable of faithfully mimicking the molecular, pathological and immunological features of human GBM. These models enable the replication of complex in vivo crosstalk between the immune system and the TME, while preserving the relevant treatment barriers that govern drug delivery to the brain. Accumulating evidence indicates that humanised mouse models closely reproduce the infiltration of human immune components into the TME, enabling the study of clinically relevant interactions that contribute to therapeutic resistance and treatment failure in GBM. This review aims to provide a comprehensive and systematic overview of the currently employed humanised mouse models in GBM research, highlighting their applications and comparative advantages. Finally, we evaluate the opportunities and challenges associated with each model and discuss future directions to increase the translational relevance and predictive power of preclinical GBM research. Humanised mouse models provide a valuable translational platform combining the human immune system and PDX orthotopic engraftment. Compared to conventional models and ex vivo models, these models can reproduce the complex cross-talk between tumour cells and the immune system, tumour heterogeneity, immunosuppressive TME, as well as complex in vivo interactions such as brain-specific barriers, including BBB, BCSFB and BMB. Future implementation of the human gut microbiome in these models has the potential to further increase translational relevance and precision in GBM research. Created in BioRender.com.

PMID 42763326
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