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NCT02961270UNKNOWNanonymous

Clinical Activity of Icotinib in Patients With Advanced Non-small-cell Lung Cancer Harbouring Uncommon EGFR Mutations: a Single-arm, Prospective, Phase 2 Study

Sponsor

Source record

Chinese Academy of Medical Sciences

Phase

Source record

Phase 2

Modality

AI-normalized

small molecule

Target

AI-normalized

Epidermal Growth Factor Receptor (EGFR) with a focus on uncommon mutations

Indication / condition

AI-normalized

Non-small Cell Lung Cancer

Intervention

Source record

Icotinib

Source & freshness

Source record

NCT ID

NCT02961270

Original source

ClinicalTrials.gov

Source last updated

Nov 11, 2016

Ingested at

Jun 19, 2026

Internal sync

Jun 19, 2026

Model version

trialsignal-ai-v1

Normalized confidence

96%

Validation status

validated

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View original source fields

NCT ID

NCT02961270

Title

Clinical Activity of Icotinib in Patients With Advanced Non-small-cell Lung Cancer Harbouring Uncommon EGFR Mutations: a Single-arm, Prospective, Phase 2 Study

Sponsor

Chinese Academy of Medical Sciences

Status

UNKNOWN

Phase

Phase 2

Condition raw

Non-small Cell Lung Cancer

Condition normalized

Non-small Cell Lung Cancer

Modality raw

small molecule

Modality normalized

small molecule

Target raw

Epidermal Growth Factor Receptor (EGFR) with a focus on uncommon mutations

Target normalized

Epidermal Growth Factor Receptor (EGFR) with a focus on uncommon mutations

Interventions

Icotinib

Public preview

Source record

Icotinib, a first-generation EGFR TKI, is being evaluated for its efficacy in treating advanced non-small cell lung cancer (NSCLC) patients with uncommon EGFR mutations. This study addresses a significant unmet medical need, as current EGFR inhibitors primarily target common mutations (e.g., 19 del and 21 L858R). The market for NSCLC therapies is substantial, with increasing demand for targeted therapies that can address diverse mutation profiles. If successful, icotinib could capture a niche segment of the NSCLC market, particularly in regions with high prevalence of uncommon mutations. Competitive implications include potential differentiation from existing therapies and the opportunity to establish a first-mover advantage in this specific patient population. Diligence considerations should focus on the drug's safety profile, efficacy data, and potential regulatory pathways in various markets.

AI-generated analysis supports research triage only. Verify source records, publications, sponsor disclosures and IP databases before making diligence decisions. Model: trialsignal-ai-v1.

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