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insulin (Rinsulin R)

✓ Approved

GeroPharm · INSR · 重组蛋白

什么是 insulin？

insulin 是一种重组蛋白，由GeroPharm研发。该药已获批，用于治疗相关适应症，给药途径：Injectable (Others)、Intramuscular (IM) Injection、Intravenous (IV)、Subcutaneous Injection。

药物档案

商品名Rinsulin R
公司GeroPharm
药物类别重组蛋白
分子靶点INSR
给药途径Injectable (Others), Intramuscular (IM) Injection, Intravenous (IV), Subcutaneous Injection
状态Approved
来源： ClinicalTrials.gov, GeroPharm

作用机制

分子靶点

insulin 作用于 1 个分子靶点：

INSRinsulin receptor (CD220, HHF5)
需要更深入的分析？Noah AI 可解释复杂机制并与同类药物比较。

治疗适应症

insulin 针对 2 个适应症，涉及 1 个治疗领域。

治疗领域疾病/病症分期
Metabolism and nutrition disordersType 1 diabetes mellitus✓ Approved
Metabolism and nutrition disordersType 2 diabetes mellitus✓ Approved

相关研究文献

PubMedJournal of medical case reports2026-10-26

High-dose regular insulin as a potential rescue therapy in severe aluminum phosphide poisoning: a case report.

Sedaghattalab Moslem M, Akbari Ghaidafeh G

Aluminum phosphide (rice tablet) can cause cardiocirculatory collapse and has negative cardiac inotropic effect. Positive inotropic effect of insulin on the cardiac myocytes is through calcium flux. Insulin increases the intramyocytes calcium concentration by increasing conductance of calcium through the L-type calcium channels and by increasing intramyocytes concentration of cyclic adenosine monophosphate. In addition to increasing the intramyocytes calcium level, insulin also enhances the responsiveness of the cardiac cells to calcium. High-dose insulin is a potential therapy for hypodynamic and hypotensive septic shock due to its positive inotropic qualities. In this paper, a critical aluminum phosphide poisoning patient (a 25-year-old Iranian young woman), presented with mixed severe metabolic acidosis and respiratory alkalosis, tachypnea, tachycardia, and hypotension. In contrast to our previous experiences that ingestion of aluminum phosphide tablets associated with multiple organ failure and severe shock in approximately all critical poisoning patients, early initiation of high-dose intravenous regular insulin for this patient prevented multiorgan dysfunction and death. Treatment with high-dose intravenous insulin associated with IV fluids, sodium bicarbonate, hydrocortisone, potassium, dextrose therapy and supportive care resolved completely signs and symptoms of patient after 3 days in ICU. High-dose intravenous regular insulin may be act as a rescue therapy for aluminum phosphide poisoning patients. While this single case suggests a potential benefit, further studies are required to confirm these findings.

PMID 42928247
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PubMedDiseases (Basel, Switzerland)2026-10-26

Clinical Effectiveness, Safety, and Implementation of Artificial Intelligence-Assisted Insulin Management Systems in Type 1 and Type 2 Diabetes: A Systematic Review of Randomized Controlled Trials.

Rodrigues Victória Dogani VD, Catharin Virgínia Maria Cavallari Strozze VMCS, Audi Mauro M, Pereira Eliana de Souza Bastos Mazuqueli ESBM et al.

Artificial intelligence (AI) is increasingly being integrated into insulin management through decision-support systems, adaptive bolus calculators, conversational platforms, and automated insulin delivery (AID) technologies. However, the clinical effectiveness and safety of AI-assisted insulin management remain uncertain. To systematically evaluate evidence from randomized controlled trials (RCTs) investigating AI-assisted insulin management systems in individuals with type 1 or type 2 diabetes. A systematic literature review was conducted following PRISMA guidelines. PubMed/MEDLINE, Embase, and Cochrane CENTRAL were searched for RCTs evaluating AI-enabled insulin management interventions in insulin-treated individuals with diabetes. Eligible studies compared AI-based systems with standard care, clinician-guided insulin titration, conventional bolus calculators, or other AID algorithms. Outcomes included glycemic control, insulin titration, safety, and implementation-related measures. Owing to substantial heterogeneity, findings were synthesized narratively. We included seven RCTs published between 2020 and 2025. Interventions comprised clinical decision-support systems, adaptive bolus calculators, conversational AI platforms, neural-network-based artificial pancreas algorithms, and exercise-aware AID systems. AI-assisted interventions consistently demonstrated favorable safety profiles, with no increase in severe hypoglycemia, diabetic ketoacidosis, or serious adverse events. Some systems, particularly fully automated closed-loop platforms and conversational AI-guided insulin titration, showed improvements in time in range, glucose control, adherence, and insulin optimization. User acceptance and adherence emerged as important determinants of effectiveness. Current randomized evidence suggests that AI-assisted insulin management systems are safe, feasible, and capable of achieving glycemic outcomes comparable to conventional care. Although certain technologies demonstrate promising clinical benefits, the evidence base remains limited by small sample sizes, short follow-up durations, and heterogeneity across interventions. Larger, long-term randomized trials are needed to establish comparative effectiveness, optimize human-AI interaction, and support broader clinical implementation.

PMID 42930005
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PubMedBiosensors2026-10-26

Hybrid Multi-Biorecognition Laser-Scribed Graphene Platform for Electrochemical Detection of Insulin Resistance Biomarkers.

Rizalputri Lavita Nuraviana LN, Shetty Saptami Suresh SS, Martinez Mario Soto MS, Roux Eckaard Le EL et al.

Insulin resistance (IR) is a multifactorial metabolic condition that can precede type 2 diabetes, motivating integrated monitoring of complementary biomarkers associated with glucose-insulin homeostasis and adipose tissue dysfunction. Here, we present a hybrid multi-biorecognition laser-scribed graphene (LSG) electrochemical platform with four independently functionalized working electrodes for detecting glucose, insulin, adiponectin, and leptin. The platform combines glucose oxidase-mediated enzymatic sensing, a methylene-blue-labeled insulin aptamer, and antibody-based recognition for adiponectin and leptin. Each sensing channel showed concentration-dependent electrochemical responses in PBS and analyte-spiked 10% human serum. The glucose sensor retained comparable sensitivity in PBS and serum, while the insulin aptasensor and the adiponectin and leptin immunosensors remained responsive in the diluted biological matrix. A preliminary mixed-analyte study further showed that all four channels remained responsive in a common four-biomarker sample. Importantly, the four-analyte panel combines glucose and insulin, used in HOMA-IR, with adiponectin and leptin, which form the adiponectin-to-leptin ratio, demonstrating thcombines high surface area, good electrical conductivitye feasibility of integrating complementary biomarkers and distinct biosensing approaches side by side within a single multiplexed electrochemical platform, with potential for future application in early-stage insulin resistance assessment.

PMID 42930092
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PubMedOxford medical case reports2026-10-26

Probable Rabson-Mendenhall syndrome presenting with acanthosis nigricans: a case report.

Akhras Mira M, Hmaidan Mohammad M, Ghazal Rahaf R, Alebrahem Asad A et al.

Rabson-Mendenhall syndrome (RMS) is a rare autosomal recessive disorder caused by mutations in the insulin receptor gene (INSR), resulting in severe insulin resistance. We report the case of an 8-year-old boy who presented with progressive acanthosis nigricans of the neck, coarse facial features, generalized hypertrichosis, dental abnormalities, a fissured tongue, thickened nails, penile hypertrophy, and hepatomegaly. Laboratory results indicated hyperinsulinemia, severe insulin resistance and fasting hypoglycemia. Based on the clinical and laboratory findings, Rabson-Mendenhall syndrome was considered. Genetic confirmation was not performed because it was unavailable in our country. This case highlights the importance of recognizing acanthosis nigricans as a clinical marker of inherited metabolic syndromes, and the important role of dermatologists in its early recognition.

PMID 42928893
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PubMedBJOG : an international journal of obstetrics and gynaecology2026-10-26

Oral Antihyperglycemic Agents Versus Insulin for Gestational Diabetes Mellitus: Societal Cost-Effectiveness Analysis of the SUGAR-DIP Randomized Controlled Trial.

Broulikova Hana M HM, van der Wel Anne W T AWT, Rademaker Doortje D, de Wit Leon L et al.

To assess the cost-effectiveness of treatment with sequential oral antihyperglycemic agents (OHA; metformin and glibenclamide) versus insulin for gestational diabetes (GDM). Cost-effectiveness analysis from a societal and healthcare perspective alongside a randomized controlled trial (SUGAR-DIP). Twenty-five hospitals in the Netherlands. Women with GDM and a singleton pregnancy, randomized to OHA (n = 409) or insulin (n = 411) between 16 to 34 weeks' gestation. Missing data were handled using multiple imputation. Differences in costs and effects were estimated using bivariate regression with bootstrapping to derive incremental cost-effectiveness ratios. Cost-effectiveness acceptability curves were constructed across a range of willingness-to-pay (WTP) thresholds. Large for gestational age (LGA), quality-adjusted life-years (QALYs), costs and cost-effectiveness. OHA slightly increased QALYs (0.009; 95% CI 0.004 to 0.014), corresponding to approximately 3 days in perfect health. There were no statistically significant differences in LGA avoided (-0.039; 95% CI-0.097 to 0.018) or societal costs (mean difference-€1004; 95% CI-€3503 to €1495). OHA were less costly and less effective than insulin for LGA, whereas for QALYs they were less costly and more effective. The probability of OHA being cost-effective at a WTP threshold of €0 was 79% for both outcomes. OHA have a high probability of being cost-effective compared with insulin for QALYs, although the QALY gain is small and of limited clinical relevance. For LGA, OHA were less costly but less effective, and cost-effectiveness depends on acceptable trade-offs between costs and neonatal outcomes.

PMID 42928492
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PubMedCells2026-10-26

Skeletal Muscle Insulin Resistance in Three Dimensions: Mechanisms, Myokines, and Microphysiological Platform.

Salih Mohamed M, Bacon Joe J, Johnson Simon C SC, Hilgen Gerrit G et al.

Skeletal muscle insulin resistance is a major determinant of impaired glucose disposal in type 2 diabetes. The mechanisms underlying insulin resistance in muscles are shaped by tissue architecture, contraction, extracellular-matrix signalling, mitochondrial function, and endocrine communication; processes that are not fully reproduced by conventional cell-based two-dimensional (monolayer) models of disease. This narrative review integrates our current understanding of canonical IRS-1-PI3K-AKT-GLUT4 signalling with contraction-dependent pathways, lipotoxicity, mitochondrial and endoplasmic-reticulum stress, inflammation, extracellular-matrix remodelling, and myokine dysregulation. We then evaluate experimental models, with particular emphasis on three-dimensional (3D) engineered muscle tissues (EMTs). Current evidence indicates that 3D EMTs can provide aligned myofibres, matrix-dependent mechanosignalling, measurable force and calcium handling, insulin-stimulated glucose uptake, and contraction-regulated myokine secretion. Emerging co-culture and myosteatosis models also recapitulate aspects of adipose-muscle crosstalk. However, current platforms remain limited by incomplete fibre maturation, absent or immature neuromuscular junctions, limited vascularisation and perfusion, variability across cell and scaffold systems, and sparse validation against patient-specific multi-omic signatures. Integrating patient-derived cells, innervation, perfusion, controlled mechanics, and multi-tissue modules could make 3D EMTs a more predictive microphysiological platform for mechanistic studies, therapeutic screening, and precision metabolic medicine.

PMID 42929864
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