Clinical trial · Observational
Creating an Innovative AI-based Technology TCRact for Designing and Optimizing T-cell Receptors (TCR) for Use in Cancer Immunotherapies
Creating an Innovative AI-based (Artificial Intelligence) IN SILICO TECHNOLOGY TCRact to Launch a NEW SERVICE for Designing and Optimizing T-cell Receptors (TCR) for Use in Cancer Immunotherapies
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The PROJECT OBJECTIVE is to create an innovative AI-based (Artificial Intelligence) IN SILICO TECHNOLOGY for the design and optimization of T-cell receptors (TCRs) capable of recognizing specific tumor antigens presented on Human Leukocyte Antigen (HLA). The technology will be based on bioinformatics (including molecular modelling) and artificial intelligence (including predictive, generative and optimization models). PROJECT TASKS are dedicated to the implementation of individual technological components (including the database necessary for their preparation) and to performing IN VITRO evaluation rounds to optimize the technology. Integration, within an IN SILICO TECHNOLOGY, of processes which currently require huge amounts of in vitro laboratory experiments that are necessary for bringing new TCR-based cancer immunotherapies into clinical trials: * finding appropriate TCRs targeting cancer neoantigen presented on a HLA molecule (pHLA) * testing for potential TCR toxicity (targeting self antigens presented on healthy tissues) * optimization of pHLA:TCR binding affinity and toxicity.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Cancer | Malignant Neoplasm | ALIAS | 0.90 |
| Colon Cancer | Malignant Colon Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Collection of blood (PBMC), biopsy (FFPE) and stool samples. | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- COLON CANCER
- description
- This cohort will consist of 100 patients with Colon Cancer.
- interventionNames
- Other: Collection of blood (PBMC), biopsy (FFPE) and stool samples.
Primary outcomes (3)
- measure
- Finding appropriate TCRs targeting cancer neoantigen presented on a HLA molecule (pHLA)
- timeFrame
- Inclusion
- measure
- Testing for potential TCR toxicity (targeting self antigens presented on healthy tissues)
- timeFrame
- Inclusion
- measure
- Optimization of pHLA:TCR binding affinity and toxicity
- timeFrame
- Inclusion
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Clinical diagnosis of advanced resectable colorectal cancer (Active stage II, III or IV) * Histopathologically confirmed as adenocarcinoma * Age 18 or over * Being able to understand and sign the Informed Consent Form (ICF) * Qualification for resection within 3 months from W0 or condition after primary tumor resection, not longer than 5 years from surgery Exclusion Criteria: * Mucinous colorectal adenocarcinoma * Canal and anal edge cancer, * Adenocarcinoma of the appendix, * Patients treated with neoadjuvant therapy or radiation therapy in the 3 months prior to study enrollment. * Patients treated with systemic chemotherapy in the 3 months prior to study enrollment. * Histopathological diagnosis other than adenocarcinoma * Remission * History of inflammatory bowel diseases * Pregnancy * HIV infection * Active infection with hepatitis B and C viruses * Leukocytopenia
References
Publications (1)
- DERIVEDBujak J, Klek S, Balawejder M, Kociniak A, Wilkus K, Szatanek R, Orzeszko Z, Welanyk J, Torbicz G, Jeckowski M, Kucharczyk T, Wohadlo L, Borys M, Stadnik H, Wysocki M, Kayser M, Slomka ME, Kosmowska A, Horbacka K, Gach T, Markowska B, Kowalczyk T, Karon J, Karczewski M, Szura M, Sanecka-Duin A, Blum A. Creating an Innovative Artificial Intelligence-Based Technology (TCRact) for Designing and Optimizing T Cell Receptors for Use in Cancer Immunotherapies: Protocol for an Observational Trial. JMIR Res Protoc. 2023 Jul 13;12:e45872. doi: 10.2196/45872. PMID 37440307