Drug Database
PA

pasireotide (Signifor LAR / pasireotide, LAR / pasireotide LAR)

✓ Approved

Novartis AG · SSTR1 · Small Molecule

What is pasireotide?

pasireotide is a small molecule developed by Novartis AG. It is approved for therapeutic indications via injectable (others) or intramuscular (im) injection or subcutaneous injection.

Drug Profile

Brand NamesSignifor LAR, pasireotide, LAR, pasireotide LAR
CompanyNovartis AG
Drug ClassSmall Molecule, Polypeptide
Molecular TargetSSTR1, SSTR2, SSTR3, SSTR5
RouteInjectable (Others), Intramuscular (IM) Injection, Subcutaneous Injection
StatusApproved
Sources: ClinicalTrials.gov, Novartis AG

Mechanism of Action

Molecular Targets

pasireotide acts on 4 molecular targets:

SSTR1somatostatin receptor 1 (SS-1-R, SS1-R)
SSTR2somatostatin receptor 2 (SST2)
SSTR3somatostatin receptor 3 (SST3, SS3R)
SSTR5somatostatin receptor 5 (SST5, SS-5-R)
Want deeper analysis?Noah AI can explain complex mechanisms and compare to similar drugs.

Therapeutic Indications

pasireotide is developed for 11 unique indications across 2 therapeutic areas.

Therapeutic AreaConditionPhase
Endocrine disordersAcromegaly✓ Approved
Endocrine disordersPituitary-dependent Cushing's syndrome✓ Approved
Endocrine disordersCarcinoid syndromePhase III
Neoplasms benign, malignant and unspecified (incl cysts and polyps)Colon cancer recurrentPhase III
Neoplasms benign, malignant and unspecified (incl cysts and polyps)Pituitary tumour benignPhase II

+6 more indications available with a free account

Sign up free to view all indications →

Related Research Articles

PubMedThe Journal of biological chemistry2026-07-17

Macrocyclic and linear peptides promote LAR dimerization and neurite outgrowth.

Yasumura Misato M, Zhang Yuchen Y, Iguchi Tokuichi T, Fujimura Naoakusa N et al.

Leucocyte common antigen-related protein (LAR), a member of the type IIa receptor protein tyrosine phosphatase (RPTP) subfamily, regulates biological processes such as cell differentiation, migration, axon elongation, and axon regeneration through its phosphatase activity or cell-cell interactions. The phosphatase activity of LAR is negatively regulated by its dimerization driven by the interaction with extracellular or cytoplasmic molecules. In the nervous system, monomeric LAR suppresses axon elongation and regeneration, while dimeric or oligomeric LAR exhibits the opposite effects. However, intracellular signaling mechanisms associated with LAR dimerization remain incompletely understood due to the lack of tools to control LAR dimerization at will. In this study, we performed peptide library screening using the random non-standard peptides integrated discovery (RaPID) system, which combines mRNA display with genetic code reprogramming. Through this approach, we identified high-affinity LAR-binding macrocyclic and linear peptides, named L6 and D1L, respectively. These peptides promoted the dimerization of both mouse and human LAR with minimal off-target effects in a split luciferase assay. When L6 or D1L was dimerized using a cross-linker, both peptides showed enhanced LAR dimerization activity, with D1L-derived dimers exhibiting the strongest effect. Furthermore, both monomeric and dimeric peptides promoted neurite outgrowth in cultured hippocampal neurons. Our results identify the de novo peptides as selective modulators of LAR dimerization, providing new tools to probe LAR-mediated signaling in axon growth and regeneration.

PMID 42463048
Read full article →
PubMedJMIR medical informatics2026-07-16

Machine Learning-Augmented Traditional Analysis of Lactate vs Lactate-to-Albumin Ratio for Predicting Mortality Risk in Patients With Sepsis: Large-Scale Retrospective Study.

Wang Xiaodi X, Xu Yi Y, Xiao Weijun W, Dou Peng P et al.

Effective risk stratification in sepsis remains a critical clinical challenge. Serum lactate is a cornerstone biomarker of metabolic dysfunction, yet its predictive limitations-particularly in patients without severe hyperlactatemia-are well recognized. The lactate-to-albumin ratio (LAR), a composite mixed-unit index integrating markers of acute metabolic dysfunction and systemic inflammation, has emerged as a promising predictor; however, its incremental discriminative advantage over lactate had not been formally tested in a large multicenter cohort using paired statistical methodology. This study aims to determine whether LAR provides statistically significantly higher prediction of 28-day mortality than lactate alone in adult intensive care unit (ICU) patients with sepsis, using threshold effect analysis, restricted cubic splines, DeLong test, and 9 interpretable machine learning models. We conducted a retrospective analysis of 3637 adult patients with sepsis from the multicenter eICU Collaborative Research Database (eICU-CRD; 208 hospitals, United States, 2014-2015). The primary outcome was 28-day all-cause in-hospital mortality among patients surviving the initial 48-hour ICU admission period. We used multivariable logistic regression (LR), Cox proportional-hazards regression, threshold effect analysis, restricted cubic spline modeling, DeLong test for area under the receiver operating characteristic curve (AUC) comparison, and machine learning models evaluated with Shapley additive explanations (SHAP) for interpretability. The cohort was divided 70/30 (stratified) into training and held-out test sets; the Synthetic Minority Oversampling Technique was applied exclusively within the training partition to prevent data leakage. LAR consistently demonstrated stronger and more stable associations with mortality than lactate across all subgroups. DeLong test confirmed statistically significantly higher AUC for LAR: 28-day hospital mortality (AUCLAR=0.646, 95% CI 0.623-0.670 vs AUClactate=0.617, 95% CI 0.593-0.641; Z=6.37; P<.001; ΔAUC=0.029) and 28-day ICU mortality (AUCLAR=0.642 vs AUClactate=0.621; Z=3.71; P<.001). A nominally significant Acute Physiology and Chronic Health Evaluation IV (APACHE IV) × LAR interaction (hospital mortality, P for interaction=.02) indicated stronger LAR prognostic effects in lower-severity patients (APACHE IV≤70), representing within-biomarker effect modification requiring prospective validation. Among 9 machine learning models for ICU mortality, LR, random forest (RF), and gradient-boosting decision tree (GBDT) achieved the 3 highest AUCs (0.727, 0.726, and 0.725); Light Gradient Boosting Machine (LightGBM) demonstrated the best calibration (Brier score 0.096, the only model below the null Brier of 0.101 at the natural prevalence of 11.4%); GBDT achieved the highest precision-recall AUC (0.293). SHAP identified LAR among the top 10 predictive features in 3 of 4 models for hospital mortality (RF rank 4, LR rank 7, and LightGBM rank 8) and 1 of 4 for ICU mortality (RF rank 4). LAR demonstrates statistically significantly higher discrimination than lactate alone for 28-day sepsis mortality prediction. LAR may offer greater prognostic utility in patients without severe hyperlactatemia, a population in whom early risk stratification may be particularly relevant.

PMID 42462220
Read full article →
PubMedKinases and phosphatases2026-07-16

Receptor Protein Tyrosine Phosphatases (RPTPs): Structure and Biological Roles in Cancer.

Conklin Abigail E AE, Welsh Colin L CL, Madan Lalima K LK

Receptor protein tyrosine phosphatases (RPTPs) are transmembrane enzymes that counterbalance protein tyrosine kinase activity by catalyzing the removal of phosphate groups from tyrosine residues on target proteins. Despite their critical roles in regulating cellular proliferation, adhesion, differentiation, and survival, RPTPs remain significantly understudied compared to their kinase counterparts. Contrary to early assumptions that PTPs function as constitutive housekeeping enzymes, emerging evidence demonstrates that RPTPs exhibit highly context-dependent roles in cancer, functioning as tumor suppressors, tumor promoters, or displaying dual activities depending on tissue type, cellular environment, and the specific signaling networks involved. This review provides a comprehensive analysis of RPTP structure, catalytic mechanisms, regulatory processes, and interactions with signaling effectors in cancer. Through a systematic examination of RPTP expression patterns across ten cancer types using Clinical Proteomic Tumor Analysis Consortium (CPTAC) and International Cancer Proteogenome Consortium (ICPC) datasets, we identify subfamily-specific and cancer-type-specific expression alterations that correlate with established functional classifications. PTPσ and PTPμ emerge as uniformly downregulated tumor suppressors across diverse malignancies, whereas, PTPα and PTPε, display oncogenic potential by activating Src family kinases. Context-dependent RPTPs, such as LAR and DEP-1, exhibit variable expression patterns that reflect their complex, multifaceted signaling roles. These findings establish RPTPs as critical regulators of cancer signaling with significant therapeutic potential, while underscoring the need to understand tissue-specific signaling architectures when developing RPTP-targeted interventions.

PMID 42460234
Read full article →
PubMedBMC plant biology2026-07-16

Integrated metabolomic and transcriptomic analysis of Camellia sinensis var. pubilimba 'Rucheng Baimaocha' reveals distinct flavonoid and strictinin biosynthesis.

Qu Furong F, Zhao Yang Y, Yang Peidi P, Cheng Yang Y et al.

'Rucheng Baimaocha' (RCBMC) is a traditional tea landrace found in Hunan Province, China. Its morphological characteristics differ substantially from those of the other cultivars, featuring larger mature leaves with thicker cuticle layers. Both young buds and leaf undersides are densely covered in silvery-white trichomes, indicating that RCBMC has a distinct metabolite composition compared to other cultivars. To elucidate the metabolic profile differences and their underlying molecular mechanisms, we conducted an integrated metabolomic and transcriptomic analysis of RCBMC and representative cultivars. Metabolomics revealed that RCBMC accumulated higher levels of non-epicatechins, such as catechin, catechin gallate, and gallocatechin gallate, and the ellagitannin strictinin, whereas flavonoid glycosides were significantly lower. Transcriptomics identified 11,775 differentially expressed genes with key shifts in the flavonoid pathway: upregulated LAR and downregulated ANS gene expression collectively redirected metabolic flux toward non-epicatechin synthesis. The downregulation of multiple UGT genes was correlated with reduced flavonoid glycoside levels. Weighted gene co-expression network analysis further identified transcription factors strongly associated with metabolite accumulation. Quantitative analysis of 607 medium- and small-leaf tea germplasms indicated that strictinin content was genetically influenced and seasonally regulated, with RCBMC exhibiting notably high levels. Correlation analysis identified candidate genes from the SCPL, CXE, and LAC families that are potentially involved in strictinin biosynthesis. This study revealed a unique pattern of bioactive compound accumulation in RCBMC and provides valuable germplasm resources and genetic targets for breeding tea cultivars with enhanced functional components.

PMID 42458239
Read full article →
PubMedJournal of clinical medicine2026-07-15

Prognostic Value of the Lactate-to-Albumin and C-Reactive Protein-to-Albumin Ratios in COVID-19-Associated ARDS.

Almuntashiri Sultan S, Alsubhi Yazeed Adel M YAM, Alhelali Ziyad Khalid B ZKB, Alanazi Abdulrahman Fraih M AFM et al.

Background: Coronavirus disease 2019 (COVID-19) is frequently complicated by acute respiratory distress syndrome (ARDS), which is associated with high mortality. The lactate-to-albumin ratio (LAR) and C-reactive protein-to-albumin ratio (CAR) have been proposed as prognostic markers in critical illness, but their comparative performance in COVID-19-associated ARDS is not well established. Methods: We conducted a retrospective cohort study using the MIMIC-IV database, which contains data from Beth Israel Deaconess Medical Center, United States, including COVID-19 ICU admissions from 2020 to 2022. Adult COVID-19 patients with available PaO2/FiO2, lactate, albumin, and C-reactive protein measurements within the first 48 h of ICU admission were included. Receiver operating characteristic analysis, Kaplan-Meier survival analysis, and Cox proportional hazards regression were performed. Results: Of the 3620 patients screened, 66 met the inclusion criteria; 36 survived and 30 died. Non-survivors had significantly higher LAR and CAR values at ICU admission. In ROC analyses, LAR demonstrated moderate discrimination for 30-day mortality (AUC 0.706) and showed higher discriminatory performance than CAR in most subgroup analyses. Among ARDS patients, LAR showed moderate predictive ability (AUC 0.693), compared with CAR (AUC 0.655). In severe ARDS, both markers demonstrated improved discrimination (0.722 AUC for LAR and 0.797 for CAR). High LAR was associated with significantly higher 30-day mortality in all ARDS patients (60.5% vs. 24.0%; p = 0.0056) and severe ARDS patients (72.0% vs. 20.0%; p = 0.0022). Elevated CAR was also associated with increased mortality, particularly in severe ARDS (73.1% vs. 14.3%; p < 0.001). In multivariable Cox regression, LAR remained independently associated with 30-day mortality. Conclusions: LAR demonstrated independent prognostic value for 30-day mortality in critically ill COVID-19 patients with ARDS. CAR showed variable performance. These readily available biomarkers, particularly LAR, may aid early risk stratification although larger studies are needed to confirm these findings.

PMID 42452753
Read full article →
PubMedJournal of clinical medicine2026-07-15

Association of Serial Lactate-to-Albumin and C-Reactive Protein-to-Albumin Ratios with In-Hospital Mortality After Out-of-Hospital Cardiac Arrest.

Heo Wan Young WY, Lee Dong Hun DH, Ryu Seok Jin SJ, Lee Byung Kook BK et al.

Background: The lactate-to-albumin ratio (LAR) and C-reactive protein-to-albumin ratio (CAR) are biomarkers for metabolic stress and inflammation. However, their prognostic significance after return of spontaneous circulation (ROSC) in out-of-hospital cardiac arrest (OHCA) remains unclear. Therefore, this study aims to investigate the association between serial LAR/CAR measurements and in-hospital mortality. Methods: This retrospective observational cohort study included adult comatose patients with OHCA treated with targeted temperature management between January 2022 and December 2025. Serum lactate, albumin, and C-reactive protein levels were measured at admission and at 24, 48, and 72 h after ROSC. The primary outcome was in-hospital mortality. Multivariable logistic regression analyses were performed to assess independent associations of LAR and CAR with in-hospital mortality, and discriminatory performance was assessed using the area under the receiver operating characteristic curve (AUC). Results: Of the 284 eligible patients, 253 were included in the final analysis. Of these, 80 patients died in hospital, corresponding to an in-hospital mortality rate of 31.6%. LAR and CAR were significantly higher in non-survivors than in survivors at admission and at 24, 48, and 72 h after ROSC. After adjustment for potential confounders, LAR was associated with in-hospital mortality at all assessed time points. CAR was independently associated with in-hospital mortality at admission and at 48 and 72 h after ROSC, but not at 24 h. The AUCs of LAR for predicting in-hospital mortality ranged from 0.702 to 0.734, whereas those of CAR ranged from 0.640 to 0.690. Conclusions: In this single-center retrospective cohort of post-ROSC OHCA patients, sequential tracking of LAR and CAR profiles during the first 72 h after ROSC provided meaningful insights into in-hospital mortality. LAR showed a more consistent independent association with mortality and fair discriminatory performance, whereas CAR demonstrated limited prognostic value despite its association with mortality.

PMID 42452313
Read full article →

+5226 more articles available with a free account

Sign up free to view all articles →

Ask about pasireotide