Drug Database
NI

nilotinib

✓ Approved

MolecularMD · ABL1 · Companion diagnostic

What is nilotinib?

nilotinib is a companion diagnostic developed by MolecularMD. It is approved for therapeutic indications via others.

Drug Profile

CompanyMolecularMD
Drug ClassCompanion diagnostic
Molecular TargetABL1, BCR
RouteOthers
StatusApproved
Sources: ClinicalTrials.gov, MolecularMD

Mechanism of Action

Molecular Targets

nilotinib acts on 2 molecular targets:

ABL1ABL proto-oncogene 1, non-receptor tyrosine kinase (c-ABL, bcr/abl)
BCRBCR activator of RhoGEF and GTPase (CML, ALL)
Want deeper analysis?Noah AI can explain complex mechanisms and compare to similar drugs.

Therapeutic Indications

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

Therapeutic AreaConditionPhase
Neoplasms benign, malignant and unspecified (incl cysts and polyps)Uterine cancer✓ Approved

Related Research Articles

PubMedDiagnosis (Berlin, Germany)2026-09-20

Diagnosis-related handoffs for inter-facility transfers to the pediatric intensive care unit.

Pantekidis Irene I, Pandiyan Poornima P, Singh Hardeep H, Landrigan Christopher P CP et al.

Inter-facility transfers to the pediatric intensive care unit (PICU) increase the risk of patient harm from communication breakdowns. We previously developed I-PASS-to-PICU, a structured inter-facility handoff program to improve information exchange during these transitions. However, it was not designed to optimize communication related to diagnosis (diagnostic handoff). This exploratory study evaluated how well I-PASS-to-PICU facilitated inter-facility diagnostic handoffs. Using mixed methods, we analyzed audio-recorded referral calls to a single PICU to characterize inter-facility diagnostic handoff communication before and after I-PASS-to-PICU implementation. Two pediatric intensivists trained to review calls indicated whether diagnosis-relevant information or activities were discussed. Discrepancies in review were resolved via consensus. Reviewers also provided qualitative observations on diagnosis-related discussions. Forty-four referral calls were reviewed (16 pre-and 28 post-I-PASS-to-PICU implementation). Compared with unstructured handoffs, I-PASS-to-PICU use did not result in statistically significant differences in the communication of diagnosis-related information in inter-facility handoffs. However, we observed some absolute differences; there were more calls using I-PASS-to-PICU in which illness severity was discussed (75 % vs. 50 %) and the primary diagnosis was stated by the referring clinician (68 % vs. 44 %) or receiving PICU physician (39 % vs. 25 %). Qualitative analysis revealed that shared mental models were more effectively created when primary diagnoses and diagnostic uncertainty were discussed. I-PASS-to-PICU may support aspects of the inter-facility diagnostic handoff but needs further revision to facilitate consistent discussion of diagnoses and diagnostic uncertainty. Future work will focus on redesigning and evaluating I-PASS-to-PICU for improving the diagnostic handoff during inter-facility PICU transfers.

PMID 42763795
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PubMedDiabetes, metabolic syndrome and obesity : targets and therapy2026-09-20

Metabolic Predictors and Diagnostic Performance of Fundus Autofluorescence for Diabetic Macular Edema: A Cross-Sectional Diagnostic Accuracy Study Using Swept-Source Optical Coherence Tomography as Reference Standard.

Amin Ramzi R, Pratama Adrian A, Ansyori Abdul Karim AK, Calisanie Mohammad Aulia Molid Ogest Putra MAMOP

To evaluate the diagnostic performance of fundus autofluorescence (FAF) imaging for detecting diabetic macular edema (DME) using swept-source optical coherence tomography (SS-OCT) as the reference standard, and to identify metabolic factors associated with FAF detection accuracy in patients with type 2 diabetes mellitus. This cross-sectional diagnostic accuracy study enrolled 120 eyes from 68 patients with type 2 diabetes mellitus at the Vitreoretina Subdivision, Department of Ophthalmology, RSUP Dr. Mohammad Hoesin, Palembang, Indonesia, between January 2024 and June 2025. All participants underwent comprehensive ophthalmic examination including FAF imaging and en face SS-OCT (DRI OCT Triton Plus, Topcon). Metabolic parameters including glycated hemoglobin (HbA1c), fasting lipid profile, body mass index (BMI), estimated glomerular filtration rate (eGFR), and diabetes duration were recorded. Diagnostic accuracy indices were calculated using 2×2 contingency tables. Multivariate logistic regression identified metabolic predictors of FAF detection concordance with SS-OCT. DME was present in 78 eyes (65.0%) by SS-OCT. FAF demonstrated sensitivity of 73.1% (95% CI: 61.8-82.5%), specificity of 76.2% (95% CI: 61.5-87.2%), positive predictive value of 85.1%, negative predictive value of 60.4%, positive likelihood ratio of 3.07, negative likelihood ratio of 0.35, and diagnostic odds ratio of 8.68. HbA1c ≥8.5% (OR 3.42, 95% CI: 1.28-9.14, p=0.014), diabetes duration ≥10 years (OR 2.87, 95% CI: 1.15-7.16, p=0.024), and BMI ≥30 kg/m2 (OR 2.31, 95% CI: 0.94-5.68, p=0.068) were independently associated with FAF-OCT concordance. Center-involved DME showed higher FAF sensitivity (82.4%) compared to non-center-involved DME (55.6%, p=0.012). FAF imaging demonstrates moderate diagnostic accuracy for DME detection, with performance significantly influenced by metabolic status and DME subtype. Integration of metabolic risk stratification may optimize FAF-based screening in diabetic populations.

PMID 42763671
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PubMedCurrent health sciences journal2026-09-20

The Role and Diagnostic Accuracy of Artificial Intelligence in Pulmonary Function Tests: A Systematic Review.

Orpwood Thomas T, Soica Irina-Lavinia IL

The rapid advancement of artificial intelligence (AI) has highlighted its potential as a supportive tool in pulmonary function test (PFT) interpretation given the inherent biological variation, inter-rater variability, lack of confidence in result interpretation and restricted access within resource-constrained settings. This study aims to systematically review the published literature on the diagnostic accuracy of AI-based interpretation of PFTs and evaluate its implications for current and future clinical practice in healthcare. After screening, forty-seven publications met the inclusion criteria and were analysed to create a narrative summary. Four main over-arching themes were identified from the available literature. AI appears to consistently outperform non-specialists in diagnostic accuracy of PFTs and showed a synergistic effect when used as an adjunct in both specialist and non-specialist settings. Using AI software also had greater diagnostic accuracy than clinicians when presented with suboptimal or limited clinical information and investigations. It was also observed that the implementation of AI can address the issue of inter-rater variability by giving more consultant interpretations. Chronic obstructive pulmonary disease diagnosis saw the greatest accuracy with other conditions such as obstructive sleep apnoea showing limited evidence for the introduction of AI as a diagnostic tool. The evidence suggests that AI has the potential to play a significant role in the future of healthcare but should be used as an adjunctive tool as opposed to an independent diagnostic decision maker. One such way it could be utilised is as a triage/screening tool to help bridge the gap between primary and secondary care.

PMID 42763768
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PubMedEuropean radiology2026-09-20

In vivo coronary stent evaluation using photon-counting computed tomography: diagnostic performance.

Lacaita Pietro G PG, Bilgeri Valentin V, Spitaler Philipp P, Kindl Benedikt B et al.

To assess the diagnostic performance of photon-counting computed tomography (PCCT) coronary angiography for the detection of in-stent restenosis (ISR) ≥ 50%, and image quality. 141 consecutive patients with coronary stents referred to coronary computed tomography angiography (CTA) were enrolled in this retrospective single-center study, using either PCCT or energy-integrating detector (EID)-CT. Image quality of the in-stent lumen (ISL) was graded using a 3-point scale as 2 = "excellent diagnostic", 1 = "limited diagnostic", or 0 = nondiagnostic. Coronary stents were assessed for ISR ≥ 50% compared to invasive coronary angiography (ICA), and quantitative image analysis was performed. 176 stents in 70 patients (age 73.64 ± 12.6, 27.1% women) who underwent PCCT were included and compared to a control group of 71 patients (126 stents) who underwent EID-CT. Subjective image quality scores were higher in stents assessed by PCCT compared with EID-CT (p < 0.001). The rate of nondiagnostic stents was lower (1.1% vs 46.8%, p < 0.001) with PCCT, while the proportion of stents excellent image quality was higher (70.5% vs 23%, p < 0.001). The diagnostic accuracy of PCCT (per-patient) for the detection of ISR ≥ 50% was 90.48% (71.09, 97.35), sensitivity 100% (64.57, 100), specificity 85.71% (60.06, 95.99), PPV 77.78% (45.26, 93.68), NPV 100% (75.75, 100), and per-stent: accuracy 88.52% (78.16, 94.33), sensitivity 100% (70.08, 100), specificity 86.54% (74.73, 93.32), PPV 56.25% (33.18, 76.90) and NPV 100% (92.13, 100). True positive ISR ≥ 50% showed a trend toward lower ISR/ISL ratios than false positives (mean, 0.35 vs 0.87). Image quality of PCCT for coronary stent evaluation is improved compared to EID-CT, and the accuracy for detection of ISR ≥ 50% is high. Question Does photon-counting CT improve the diagnostic accuracy for detection of in-stent restenosis (ISR) ≥ 50%, and image quality compared with energy-integrating detector (EID) CT? Findings Photon-counting CT provides higher image quality and a low rate of nondiagnostic stents (0.3%). For detecting ≥ 50% ISR, the diagnostic accuracy is high and the PPV is moderate. Clinical relevance Photon-counting computed tomography (PCCT) has the potential to overcome technical limitations of conventional energy-integrating CT in coronary stent assessment and could improve the reliability of non-invasive follow-up after percutaneous coronary intervention.

PMID 42763334
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PubMedCureus2026-09-20

Eleven-Year Diagnostic Delay in Episodic Cluster Headache With a Characteristic International Classification of Headache Disorders, 3rd Edition (ICHD-3) Clinical Pattern: A Case of Migraine Misdiagnosis and Otologic Confusion.

Kang Seungyoung S, Adi Amal A, Shetty Padma V PV, Alskaf Asma A

Cluster headache is a primary headache disorder characterized by recurrent attacks of severe unilateral headache accompanied by ipsilateral cranial autonomic symptoms. Despite well-established diagnostic criteria, it remains one of the most frequently misdiagnosed primary headache disorders, resulting in substantial diagnostic delay. We report a diagnostic dilemma involving a 31-year-old man with episodic cluster headache who remained undiagnosed for 11 years despite a clinical presentation highly consistent with the International Classification of Headache Disorders, 3rd edition (ICHD-3) criteria. Throughout the disease course, he experienced recurrent severe unilateral orbital pain lasting 30-60 minutes, occurring more than three times daily during annual cluster periods and accompanied by ipsilateral lacrimation, nasal congestion, rhinorrhea, and marked restlessness. However, he was repeatedly diagnosed with migraine without aura and later underwent ophthalmologic and otolaryngologic evaluations, further delaying recognition of the characteristic headache pattern. Detailed reassessment of the clinical history ultimately led to a clinical diagnosis of episodic cluster headache, and guideline-recommended therapy was followed by substantial clinical improvement. The principal educational feature of this case is how prominent ipsilateral ear pain and distracting otologic and ophthalmologic findings contributed to delayed recognition of an otherwise characteristic cluster headache presentation. Careful assessment of attack duration, periodicity, cranial autonomic symptoms, and restlessness remains essential for timely recognition of cluster headache, particularly when apparently relevant local findings do not adequately explain the overall headache pattern.

PMID 42763664
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PubMedCureus2026-09-20

A Four-Year Diagnostic Journey to Acute Intermittent Porphyria in a 19-Year-Old Woman: Lessons on Recognizing Neurovisceral Clues.

Rezwan Dilshad D, Dhinakharan S R SR

Acute intermittent porphyria (AIP) is a rare autosomal dominant metabolic disorder caused by hydroxymethylbilane synthase (HMBS) deficiency, resulting in the accumulation of neurotoxic porphyrin precursors. Its rarity and overlap with psychiatric, neurological, and gastrointestinal clinical features frequently lead to diagnostic delays and substantial morbidity. Therefore, we report the case of a 19-year-old woman who presented to a UK tertiary hospital with recurrent tonic-clonic seizures and severe episodes of abdominal pain over a four-year period. After initial investigations excluded cardiac and epileptic causes, she was diagnosed with pseudoseizures and referred to a psychiatric facility because no conclusive epileptiform activity was detected on electroencephalography (EEG). Multiple gastrointestinal diagnostic investigations, including gastric emptying studies, were unsuccessful in identifying an underlying cause. Following postoperative deterioration characterized by nausea, vomiting, and seizures, porphyria screening was initiated. Fecal total porphyrins were elevated at 72.3 nmol/g (reference range, 0-49.9 nmol/g), raising strong biochemical suspicion of an acute hepatic porphyria and prompting specialist referral, while plasma and urinary porphyrin levels remained within normal limits. The patient was referred to a specialist porphyria clinic for genetic confirmation and management. This case illustrates the diagnostic complexity of AIP, in which overlapping neurological and psychiatric features can frequently result in misdiagnosis, and demonstrates that fecal porphyrin elevation can provide valuable complementary biochemical evidence when other investigations are inconclusive, particularly when testing is performed outside an acute episode. AIP should therefore be considered in young women with recurrent unexplained seizures and abdominal pain, especially when standard investigations, including urinary aminolevulinic acid (ALA) and porphobilinogen (PBG), are unremarkable, as normal urinary ALA and PBG levels measured outside an acute attack do not exclude AIP. Early metabolic screening, including fecal porphyrin analysis, may prevent years of morbidity and facilitate timely specialist referral.

PMID 42763777
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