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sumatriptan (Alsuma autoinjector / sumatriptan, King / Alsuma)

✓ Approved

US WorldMeds, LLC · HTR1D · Small Molecule

What is sumatriptan?

sumatriptan is a small molecule developed by US WorldMeds, LLC. It is approved for therapeutic indications via injectable (others) or subcutaneous injection.

Drug Profile

Brand NamesAlsuma autoinjector, sumatriptan, King, Alsuma
CompanyUS WorldMeds, LLC
Drug ClassSmall Molecule
Molecular TargetHTR1D
RouteInjectable (Others), Subcutaneous Injection
StatusApproved
Sources: ClinicalTrials.gov, US WorldMeds, LLC

Mechanism of Action

Molecular Targets

sumatriptan acts on 1 molecular target:

HTR1D5-hydroxytryptamine receptor 1D (HTR1DA, HT1DA)
Want deeper analysis?Noah AI can explain complex mechanisms and compare to similar drugs.

Therapeutic Indications

sumatriptan is developed for 1 unique indication across 1 therapeutic area.

Therapeutic AreaConditionPhase
Nervous system disordersMigraine✓ Approved

Related Research Articles

PubMedFrontiers in oral health2026-10-15

Assessing knowledge and awareness of dental practitioners in detecting, evaluating, and managing pre-eruptive intracoronal resorption: a cross-sectional study.

Al Tuwirqi Amani A AA, Almashaikhi Jamila A JA, Felemban Osama M OM, Elkhodary Heba M HM

This study aimed to evaluate the proficiency of dental practitioners at King Abdulaziz University Dental Hospital (KAUDH) in detecting and diagnosing pre-eruptive intracoronal resorption (PEIR). It also sought to examine their knowledge of PEIR etiology, severity, and management, while investigating how factors such as educational level and clinical experience influence their detection capabilities and overall understanding of the condition. This cross-sectional study was conducted at KAUDH and involved 125 participants. The participants were categorized into four subgroups based on their educational level: interns, general dentists, postgraduate pediatric dentistry residents, and postgraduate residents from other specialties. Each participant was asked to examine eight orthopantomograms, which included one normal radiograph, one case of tooth impaction, one case of odontodysplasia, and five cases of PEIR with varying severities. Participants were also required to answer four general questions about PEIR using a validated questionnaire. The results showed that the participants were generally proficient in the radiographic diagnosis and interpretation of common and obvious anomalies. However, they had difficulty recognizing and identifying PEIR lesions. As the severity of PEIR increased, participants were better able to identify the affected teeth; however, awareness of the correct management decreased. Pediatric dentistry residents and participants with ≥5 years of clinical experience demonstrated better diagnostic ability, both generally and specifically in relation to PEIR, than other dental practitioners. The participants had limited knowledge of PEIR. Only 24.8% of the participants had heard of PEIR, and only 6.4% had encountered a PEIR lesion in their clinics. Furthermore, only 8.8% of the participants knew that PEIR lesions are caused by resorption. The study identified important gaps in awareness and conceptual understanding of PEIR among dental practitioners, particularly regarding its etiology and management. Recognition of subtle PEIR lesions was limited, although participants demonstrated improved detection as lesion severity increased. Diagnostic accuracy and radiographic interpretation were positively associated with higher educational levels and greater clinical experience. These findings highlight the need for enhanced undergraduate and continuing dental education to improve the early detection and appropriate management of PEIR lesions.

PMID 42876693
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PubMedOnline journal of public health informatics2026-10-14

The Prevalence of Ophthalmic Symptoms Among Adults in King Saud Bin Abdulaziz University for Health Sciences: Cross-Sectional Survey.

Alnahedh Taghreed T, Taha Mohammed M, Alhadlaq Omar Saad OS

Eye diseases are prevalent conditions around the world. More than 2 billion individuals globally have visual impairment. However, reducing the worldwide burden of eye disorders requires increased public awareness of prevalent eye diseases. This study aimed to investigate the prevalence of ophthalmic symptoms and associated factors among adults studying or working at King Saud bin Abdulaziz University for Health Sciences, Saudi Arabia. A cross-sectional study was conducted among adults studying or working at King Saud bin Abdulaziz University for Health Sciences, Saudi Arabia. Data were collected on ophthalmic symptoms experienced within the past 30 days, along with demographic characteristics and other relevant factors. Statistical analyses were performed to determine the prevalence of these symptoms and to identify associated factors. The presence of at least 1 ophthalmic symptom was reported by 73.9% (184/249) of the respondents. The most prevalent symptoms included stinging eyes (76/249, 30.5%) and eye pain (71/249, 28.5%). Female participants reported a significantly higher prevalence of several symptoms, including stinging eyes, bloodshot eyes, swelling around the eyes, dark spots in the central field of view, foreign body sensation, and near vision difficulty. Multivariable analysis revealed that sex and the use of eye lubricants were the most significant predictors of ophthalmic symptoms (adjusted odds ratio [AOR] 3.73, 95% CI 2.02-6.87; P<.001). Specifically, female participants had 3 times the odds of experiencing at least 1 ophthalmic symptom compared with male participants. Additionally, participants who used eye lubricants were 70% less likely to report ophthalmic symptoms (AOR 0.31, 95% CI 0.15-0.6; P<.001). Ophthalmic symptoms are highly prevalent among adults in Saudi Arabia. Sex and the use of eye lubricants are key factors associated with these symptoms. These findings underscore the need for increased awareness, targeted interventions, and the promotion of eye lubricant use to reduce the burden of ophthalmic symptoms in this population.

PMID 42873571
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PubMedJournal of imaging informatics in medicine2026-10-14

AI-based Hip Fracture Classification from Pelvic X-ray Images Using a Hybrid PEFT-ViT and XGBoost Model.

Mohaidat Ziyad M ZM, Amin Mohammad M, Khasawneh Ruba R, Manasrah Ahmad A et al.

Accurate radiographic classification of hip fractures into femoral neck (intracapsular) versus intertrochanteric (extracapsular) types is essential for surgical planning, yet most AI studies focus on binary detection using large datasets from high-resource regions, with no prior work from the Middle East. This study proposes a Hybrid PEFT-ViT and XGBoost framework for three-class classification of hip radiographs (Normal, Intertrochanteric fracture, Neck of femur fracture), using 768 X-ray images collected from King Abdullah University Hospital (KAUH) in Northern Jordan. A LoRA-fine-tuned ViT-Base/16 backbone extracted fused class-token and patch-token features, which were classified using XGBoost. On an independent test set of 77 radiographs, the proposed model achieved an accuracy of 88.31% (95% CI 79.3-93.7%), a sensitivity of 87.75%, a specificity of 94.28%, and an F1-score of 87.75%, the highest among the evaluated CNN-based (MobileNetV2, DenseNet121) and transformer-based (ViT, DeiT, Swin) baselines. These results show that clinically meaningful hip fracture classification can be achieved using a single-center dataset, providing a practical framework for resource-limited settings, although external validation is still required.

PMID 42870151
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PubMedEBioMedicine2026-10-14

CNPY3 variants associated with a recessive developmental and epileptic encephalopathy affect inflammasome and TLR function.

Garloff Vera V, Grimmel Mona M, Maroofian Reza R, Efthymiou Stephanie S et al.

Canopy FGF signalling regulator 3 (CNPY3) is an endoplasmic reticulum (ER)-resident chaperone essential for toll-like receptor (TLR) folding, trafficking and inflammasome activation. In rare paediatric cases, biallelic CNPY3 variants have been associated with developmental and epileptic encephalopathy (DEE), but available data remain sparse. 50 individuals from 38 unrelated families with biallelic CNPY3 variants and DEE were evaluated for exome and genome findings, standardised clinical phenotype descriptions, EEG results, and neuroimaging data. A selection of variants underwent functional analysis focussing on protein stability and localisation, TLR2 function, NLPR3 inflammasome activation, and structural conformation. Disease onset occurred in early infancy (median age at onset 68 days), with a clinical phenotype comprising global developmental delay (100%) and intractable epilepsy (86%), accompanied by microcephaly (70%), spasticity (77%), growth faltering (63%), stridor (48%), and early mortality (38%). Epileptic spasms and tonic seizures (46% each) were the most frequent seizure types, and EEG findings included suppression-burst (37%) and hypsarrhythmia (28%). Phenotypic severity varied substantially, with most patients being severely affected (median score 16, range 2-20). Most variants occurred in the homozygous state (95%), including 13 missense changes and 7 truncating alleles. Variants were classified as of uncertain significance (71%), followed by likely pathogenic (23%) and pathogenic (6%) according to ACMG/AMP criteria. Genotype-phenotype correlation showed that individuals with truncating variants were, on average, more severely affected than those with non-truncating variants (median score 18 vs 14.5). Protein modelling predicted conformational effects for most missense variants. In cells, frameshift alleles abolished CNPY3 protein expression, whereas nonsense alleles markedly reduced protein levels. ER localisation of CNPY3 remained preserved across tested genotypes; however, capacity to support TLR2 maturation and processing varied substantially. Remarkably, some missense variants permitted TLR2 surface expression but impaired downstream signalling and inflammasome activation, uncoupling trafficking from signal transduction. CNPY3-associated DEE is a severe early-onset disorder with genotype-dependent phenotypic severity, accompanied by allele-specific disruption of innate immune pathways. Our findings reveal separable effects on TLR trafficking, downstream signalling and inflammasome activation, identifying CNPY3 as a key regulator of multiple cellular pathways involved in inflammatory responses and neurodevelopment. Interdisciplinary Center of Clinical Research and Jena School of Molecular Medicine, Jena University Hospital; Friedrich Schiller University Jena; The Wellcome Trust; The Medical Research Council; The MSA Trust; The National Institute for Health Research University College London Hospitals Biomedical Research Centre; The Michael J Fox Foundation; Biotechnology and Biological Sciences Research Council; The Fidelity Trust; Rosetrees Trust; Ataxia UK; Brain Research UK; Sparks GOSH Charity; Alzheimer's Research UK; CureDRPLA; UK Dementia Research Institute; Parkinson's UK; South-Eastern Norway Regional Health Authority, Norway; France Genomic Medicine Plan 2025; Deutsche Forschungsgemeinschaft; European Commission; Federal Government of Germany; State of Thuringia; Pakistan Science Foundation; King Abdullah International Medical Research Center; Science and Technology Development Fund; King Salman Center for Disability Research.

PMID 42874293
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PubMedFrontiers in pharmacology2026-10-14

Patterns and appropriateness of antipsychotic prescribing in community-dwelling older adults: a retrospective study.

Alamer Khalid A KA, Alsugeir Dana D, Alotaibi Fawaz M FM, Khalil Hussein H et al.

Antipsychotics carry substantial risk in older adults, yet their use among community-dwelling outpatients remains insufficiently characterized in Saudi Arabia, where most prior work examined potentially inappropriate medications broadly or within psychiatric services. This study assessed patterns and appropriateness of antipsychotic prescribing and examined factors associated with prescribing without a documented qualifying indication among community-dwelling older adults across outpatient specialties. We conducted a retrospective cross-sectional study of patients aged 65 or older with a qualifying outpatient antipsychotic dispensing at King Fahad Hospital of the University, Saudi Arabia, from January 2019 to May 2023. The index date was the first qualifying antipsychotic dispensing. A criteria-based algorithm classified each patient's prescribing appropriateness using FDA-approved indications, American Psychiatric Association guidelines, and the 2023 AGS Beers Criteria. Multivariable logistic regression identified factors associated with prescribing without a documented qualifying indication. Among 394 patients, clearly appropriate prescribing was identified in 16.0%, while dementia- or delirium-related prescribing was classified as high-risk/context-dependent in 18.8%. Documented off-label prescribing was identified in 11.2%, 48.0% had no documented qualifying indication, and 6.1% had no diagnosis recorded within the ascertainment window. The latter group was excluded from comparative analyses. In the regression sample (n = 370), prescribing without a documented qualifying indication was more likely when the index antipsychotic was prescribed by medical or primary care (AOR 4.43, 95% CI 2.00 to 9.81; p < 0.001), neurology (AOR 2.42, 95% CI 1.27 to 4.63; p = 0.007), or other departments (AOR 3.16, 95% CI 1.16 to 8.63; p = 0.025) than by psychiatry. Prescribing without a documented qualifying indication was common outside psychiatry, but the absence of a qualifying diagnosis in the records does not confirm inappropriate prescribing. Systematic indication documentation, medication review, and targeted stewardship may improve prescribing quality in older adults.

PMID 42871175
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PubMedFrontiers in medicine2026-10-14

Perceptions of artificial intelligence for radiographic image accuracy: a cross-sectional survey of radiology personnel.

Kaifi Reham R, Yamani Byadr B, Almarwani Rawan R, Qahaf Raghad R

To evaluate the perceptions of radiology students, interns, and technologists regarding the role of artificial intelligence (AI) in improving the accuracy of radiographic images, and to compare these perceptions across the three groups. A quantitative, cross-sectional study was conducted at King Saud bin Abdulaziz University for Health Sciences (KSAU-HS) campuses in Riyadh, Jeddah, and Al-Ahsa, and at National Guard hospitals in Jeddah, between January and December 2025. Radiology students, interns, and technologists were recruited by non-probability convenience sampling (n = 81). Data were collected through a structured, self-administered online questionnaire using a five-point Likert scale. Descriptive and inferential statistics (Chi-square, Mann-Whitney U, and Kruskal-Wallis tests) were performed using Microsoft Excel and JMP, with significance set at 0.05. Of 81 respondents, 91.4% self-rated their AI knowledge as good to excellent, although 60.5% reported never having used AI tools in radiological practice. Most respondents (79.0%) had not received AI-related training, and 86.4% agreed that combining AI with human expertise increases diagnostic accuracy. AI was widely regarded as an effective diagnostic aid (87.7%), although trust in AI-processed radiological images was considerably lower (30.9% agreement, 42.0% neutral). The overall composite AI-attitude score (median 3.85, IQR 3.54-4.15; mean 3.82 ± 0.53) showed no statistically significant differences in this sample across the subgroups examined, including gender (p = 0.063), professional role (p = 0.193), prior AI use (p = 0.086), or formal AI training (p = 0.178); effect sizes were small. Most respondents (82.7%) disagreed that AI will replace radiologic technologists. Participants held positive perceptions of AI as a supportive tool and believed that its integration with human expertise could improve radiographic image accuracy and reduce diagnostic errors, without viewing AI as a replacement for radiologic technologists. These findings reflect participants' perceptions rather than objectively measured diagnostic performance. Understanding how radiology students, interns, and technologists perceive artificial intelligence supports its integration into clinical imaging workflows, informs targeted training programs, and helps align professional expectations with the realistic role of AI in improving radiographic image accuracy.

PMID 42870988
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