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human albumin (Kedbumin)

✓ Approved

Kedrion · Cell-based Therapies · Cell-based Therapies

What is human albumin?

human albumin is a cell-based therapies developed by Kedrion. It is approved for therapeutic indications via injectable (others) or intravenous (iv).

Drug Profile

Brand NamesKedbumin
CompanyKedrion
Drug ClassCell-based Therapies
RouteInjectable (Others), Intravenous (IV)
StatusApproved
Sources: ClinicalTrials.gov, Kedrion

Therapeutic Indications

human albumin is developed for 4 unique indications across 3 therapeutic areas.

Therapeutic AreaConditionPhase
Respiratory, thoracic and mediastinal disordersAcute respiratory distress syndrome✓ Approved
Metabolism and nutrition disordersHypoalbuminaemia✓ Approved
Injury, poisoning and procedural complicationsTraumatic shock✓ Approved
Injury, poisoning and procedural complicationsThermal burn✓ Approved

Related Research Articles

PubMedInternational journal of ophthalmology2026-08-25

Diagnostic value of urinary albumin creatinine ratio in predicting vision-threatening diabetic retinopathy in patients with diabetes: a systematic review and Meta-analysis.

Gao Ying Y, Zhuang Jia-Yuan JY, Ren Yu-Yan YY, Zhang Hua-Zhi HZ et al.

To evaluate the predictive value of urinary albumin creatinine ratio (UACR), albumin excretion rate (AER), and estimated glomerular filtration rate (eGFR) for vision-threatening diabetic retinopathy (VTDR) in individuals with diabetes. A comprehensive literature search across PubMed, Embase, Web of Science, Scopus, and the Cochrane Library from their inception to February 2024 were performed. The diagnostic accuracy of microalbuminuria (MA; including UACR and AER) and eGFR in predicting VTDR using sensitivity, specificity, positive likelihood ratio and negative likelihood ratio, diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristic (ROC) curve were assessed. Analyses incorporated both bivariate generalized linear mixed models and random-effects models to ensure a robust and unbiased interpretation of the data. The review included 14 studies with a total of 87 223 patients. The pooled sensitivity and specificity of MA and eGFR for predicting VTDR were 0.77 [95% confidence interval (CI), 0.57-0.89] and 0.51 (95%CI, 0.31-0.72), respectively. The DOR was 3.47 (95%CI, 1.94-6.18), with the area under the summary ROC curve at 0.70 (95%CI, 0.66-0.74). Notably, UACR as a predictor showed a sensitivity of 0.88 (95%CI, 0.43-0.99) and specificity of 0.55 (95%CI, 0.22-0.84), with an area under the curve of 0.78 (95%CI, 0.74-0.82). Despite significant heterogeneity among the studies (P<0.01), no publication bias was detected. UACR is a highly sensitive but moderately specific indicator for early detection and management strategies in this high-risk population.

PMID 42639243
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PubMedFrontiers in nutrition2026-08-25

Nutrition-related clinical laboratory indicators in perioperative management of geriatric hip fractures: a narrative review from risk stratification to precision intervention.

Xu Xin X, Pan Ying Y, Zheng Xuehong X, Wang Junxiang J et al.

Geriatric hip fracture represents a major global public health crisis that extends far beyond acute skeletal trauma, reflecting and accelerating systemic physiological decline in older adults. Malnutrition, affecting up to 46% of these patients depending on diagnostic criteria, has been established as a pivotal modifiable determinant of adverse postoperative outcomes including complications, functional decline, and mortality. Against this backdrop, nutrition-related clinical laboratory indicators have gained increasing recognition as objective, quantifiable, and readily accessible tools with potential dual utility in prognostic risk stratification and therapeutic monitoring, yet a comprehensive synthesis of their comparative performance and clinical translation remains lacking. This narrative review therefore aims to systematically synthesize current evidence on the spectrum of nutrition-related laboratory biomarkers ranging from classical protein markers (serum albumin and prealbumin), through inflammatory-nutritional composite indices (Prognostic Nutritional Index, Controlling Nutritional Status score, C-reactive protein/albumin ratio, glucose/albumin ratio, and systemic immune-inflammation index), to emerging proteomic and bone turnover biomarkers, and to critically appraise their predictive value for postoperative complications, functional recovery trajectories, and short- to long-term mortality. We further examine the pathophysiological nexus linking malnutrition, sarcopenia, and osteoporosis, and evaluate evidence-based perioperative nutritional interventions including oral nutritional supplements, enhanced recovery protocols, and multidisciplinary care models. Finally, we delineate future directions encompassing machine learning-driven predictive models, emerging diagnostic frameworks such as the Global Leadership Initiative on Malnutrition criteria, digital nutritional monitoring tools, and the integration of laboratory biomarkers into standardized clinical decision pathways. This review provides a comprehensive framework for clinicians and researchers to advance precision perioperative nutritional management in this vulnerable population.

PMID 42638826
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PubMedSheng wu gong cheng xue bao = Chinese journal of biotechnology2026-08-25

Preperation of an engineered tryptophan-depleted protein in Pichia pastoris and evaluation of its dietary anti-tumor efficacy.

Dai Huijia H, Chen Yuluo Y, Xie Yaying Y, Wang Wenhui W et al.

Targeting amino acid metabolism has emerged as a promising strategy for cancer therapy. To investigate the feasibility of tryptophan restriction as a dietary intervention strategy to suppress tumor growth in vivo, this study developed a novel tryptophan-depleted protein (TDP) through protein engineering combined with the Pichia pastoris expression system, for dietary intervention to suppress tumor growth. Based on the human serum albumin (HSA) scaffold, we designed the TDP by mutating tryptophan at position 238 to phenylalanine (Phe), and successfully expressed it in P. pastoris. Following purification by hollow fiber membrane ultrafiltration and liquid chromatography, High performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis confirmed that the tryptophan content in the purified TDP was only 0.35 μg/g. In a gastric adenocarcinoma xenograft model, the TDP-based tryptophan-restricted diet significantly suppressed tumor growth compared with the control group receiving a complete protein diet (P0.001), resulting in a 64% reduction in tumor weight. This study provides a proof-of-concept for developing engineered dietary proteins as foods for special medical purposes (FSMPs), and establishes a novel strategic framework for dietary intervention in adjuvant cancer therapy.

PMID 42638064
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PubMedFrontiers in medicine2026-08-25

Case Report: Nephrotic syndrome with minimal change disease during anti-tuberculosis treatment and tiopronin use.

Liao Heng H, Yan Fei F, Liu Xingxia X

Hepatoprotective agents are often added during prolonged anti-tuberculosis (anti-TB) therapy, and medication-associated nephrotic syndrome may be under-recognized. A 31-year-old man with pulmonary tuberculosis received long-term anti-TB therapy (rifapentine, isoniazid, and ethambutol) and continuous tiopronin (0.2 g three times daily). He developed edema, foamy urine, and oliguria. Pre-admission tests showed proteinuria (3+), serum albumin 19.6 g/L, and serum creatinine 161 μmol/L. On admission, urine protein was 4+, serum albumin 20.6 g/L, serum creatinine 142.9 μmol/L, and estimated glomerular filtration rate (eGFR) 58.86 mL/min, with hyperlipidemia. Kidney biopsy confirmed minimal change disease (MCD). All anti-TB drugs and tiopronin were discontinued, and tacrolimus was initiated after biopsy. Anti-TB therapy was reintroduced as isoniazid monotherapy. Renal function improved rapidly (serum creatinine 55 μmol/L; eGFR 128.1 mL/min at discharge), and dipstick proteinuria became negative on short-term follow-up. The tacrolimus trough concentration was 3.6 ng/mL. The improvement after withdrawal of multiple suspected agents and continued recovery after reintroduction of isoniazid alone support a drug-associated etiology, but do not allow definitive attribution to a single causative drug. Routine renal monitoring should accompany hepatoprotective add-on therapy during anti-TB treatment.

PMID 42638881
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PubMedFrontiers in medicine2026-08-25

Biomarker-integrated machine learning models for predicting treatment-related bowel dysfunction after rectal cancer surgery: a multicenter development and external validation study.

Liu Qiyuan Q, Liu Yunxin Y, Huang Yuxiang Y, Fu Yuchen Y et al.

Low anterior resection syndrome (LARS) is a prevalent treatment-related complication following sphincter-preserving surgery for rectal cancer that severely impairs survivors' quality of life. In the era of biomarker-driven personalized cancer therapy, reliable tools integrating clinicopathological biomarkers for individualized risk stratification remain lacking. Machine learning (ML) approaches offer the potential to integrate heterogeneous biomarkers-including nutritional, inflammatory, and treatment-related indicators-for precision prediction, yet their comparative performance against conventional nomograms in LARS prediction has not been rigorously evaluated in multicenter settings. This multicenter retrospective cohort included 906 patients undergoing laparoscopic low anterior resection for rectal adenocarcinoma, with 506 in the training cohort and 400 from four hospitals for external validation. Major LARS was defined as a 6-month LARS score ≥ 21. LASSO selected features from 24 candidate variables. Five machine-learning models and a logistic regression nomogram were evaluated using AUC, calibration, decision curve analysis, and SHAP interpretation. The incidence of major LARS was 48.0% (243/506) in the training cohort and 52.2% (209/400) in the validation cohort. LASSO regression selected 14 predictive biomarkers, including preoperative serum albumin, neoadjuvant chemotherapy, and preoperative radiotherapy. In external validation, the random forest model achieved the highest AUC of 0.903 (sensitivity 0.871, specificity 0.796), followed by the logistic regression nomogram (AUC 0.888). Multivariate analysis identified tumor-anal verge distance (OR = 0.733, 95% CI 0.679-0.792, p < 0.001), stoma reversal time (OR = 1.240, p < 0.001), anastomotic leakage (OR = 7.027, p = 0.004), and diabetes mellitus (OR = 2.793, p = 0.006) as independent risk factors. SHAP analysis confirmed tumor-anal verge distance as the dominant predictor, with preoperative albumin ranking fifth in feature importance, demonstrating the capacity of ML to extract predictive signal from clinically relevant but statistically marginal biomarkers. The random forest model integrating clinicopathological biomarkers and treatment-related variables demonstrated robust predictive performance for postoperative or post-treatment risk stratification of treatment-related bowel dysfunction (LARS). The model is intended to support postoperative monitoring, survivorship counseling, and rehabilitation planning rather than purely preoperative treatment selection. These biomarker-driven prediction tools can facilitate individualized functional-risk assessment in rectal cancer patients undergoing multimodal therapy.

PMID 42638889
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PubMedCell investigation2026-08-25

Beyond ADCs: Antibody-encapsulated drug for targeted cancer therapy.

Li Linrong L, Giuliano Armando A, Sun Qiang Q, Cui Xiaojiang X et al.

Antibody-drug conjugates (ADCs) have transformed cancer treatment by covalently linking the monoclonal antibody with cytotoxic payload, yet their clinical potential remains constrained by intrinsic limitations: heterogeneous drug-to-antibody ratios, linker instability, manufacturing complexity, and drug resistance. These challenges highlight the need for fundamentally different drug formulation and delivery platforms. Antibody-encapsulated drugs (AEDs) leverage the single protein encapsulation technology to enable one antibody to noncovalently encapsulate a predefined number of payload molecules. AEDs allow for a fixed drug-to-antibody ratio, mitigate premature drug release, simplify manufacturing, and expand the range of compatible payloads and protein molecules. Preclinical investigation of trastuzumab-encapsulated actinomycin D, a HER2-targeted AED, has demonstrated potent antitumor activity across cancer models with varying HER2 expression levels, alongside a favorable toxicity profile in animal models. The broader translational feasibility of the single protein encapsulation platform is further supported by ongoing clinical trials of albumin-encapsulated therapeutics. Together, these advances position AED as a promising next-generation targeted cancer therapy that complements and potentially extends beyond conventional ADCs, offering a compelling strategy to overcome existing resistance mechanisms and therapeutic limitations.

PMID 42639490
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