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This study is trying to develop a computational model to find out which patients are likely to benefit from immune therapy

To develop NEAR AI, a model to predict response to immune checkpoint inhibitor therapy in Non Small Cell Lung carcinoma (NSCLC).

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2022/11/047205
Enrollment
200
Registered
2022-11-11
Start date
Unknown
Completion date
Unknown
Last updated
2025-10-13

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: C349- Malignant neoplasm of unspecifiedpart of bronchus or lung

Interventions

None listed

Sponsors

Kerala Startup Mission
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: 1. Non small cell carcinoma lung of any histology who have received treatment with immune checkpoint inhibitor therapy between 2017-2021. 2. Patients should have taken regular treatment as per prescribed protocol for at least 3 months or till first radiological response assessment by iRESIST, whichever is later. 3. Drug treatments include Pembrolizumab/Nivolumab/Durvalumab/Atezolizumab either in combination with chemotherapy or as single agents. 4. Stage IV or recurrent disease. 5. Any line of treatment is included 6. Combination with radiation is included 7. Hematoxylin – Eosin slide with/without corresponding FFPE block of tumor biopsy tissue is available. 8. Clinical record of response to ICI therapy is available.

Exclusion criteria

Exclusion criteria: 1. Documented infectious pneumonia during first 3 months of therapy.

Design outcomes

Primary

MeasureTime frame
Primary outcome is development of computational model that predicts responders to immune checkpoint inhibitors with 80% sensitivity.Timepoint: Assessment of response will be at 3 months of starting ICI therapy in retrospective cohort.

Secondary

MeasureTime frame
NilTimepoint: NA

Countries

India

Contacts

Public ContactDr Durga Prasan

64 Codon Pvvt. Ltd

durgaprasan@64codon.com8139873641

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026