[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100546577":3},{"organization":4,"outcomesModule":7,"designInfo":14,"detailedDescription":13,"studyPopulation":17,"armGroups":13,"interventions":18,"overallOfficials":22,"centralContacts":26,"locations":13,"responsibleParty":36,"collaborators":38,"id":42,"slug":13,"hasResults":43,"nctId":44,"briefTitle":45,"officialTitle":45,"acronym":46,"eligibilityCriteria":47,"healthyVolunteers":43,"sex":48,"minAge":49,"maxAge":13,"enrollmentInfo":50,"targetDuration":13,"studyType":53,"phases":13,"briefSummary":54,"conditions":55,"keywords":13,"overallStatus":57,"whyStopped":13,"lastUpdateSubmitDate":58,"lastUpdatePostDateStruct":59,"startDateStruct":62,"completionDateStruct":64,"leadSponsor":66,"locationsCount":13},{"fullName":5,"class":6},"Institute of Cancer Research, United Kingdom","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":13},[9],{"measure":10,"description":11,"timeFrame":12},"To determine the reliability and performance of the process and AI tool","Success rate of digitization of H\\&E slides \\& Turnaround time for biomarker report within standard patient pathways","6 months",null,{"allocation":13,"interventionModel":13,"interventionModelDescription":13,"primaryPurpose":13,"observationalModel":15,"timePerspective":16,"maskingInfo":13},"COHORT","PROSPECTIVE","Patients with triple negative breast cancer requiring neoadjuvant systemic therapy",[19],{"type":6,"name":20,"description":21,"armGroupLabels":13,"otherNames":13},"AI-analysis on diagnostic and surgical specimens","The analysis will report a list of AI-based biomarkers to assess the tumour-immune spatial microenvironment as well as final spatial immune-ecology prognostic (SIPA) reports for every patient.",[23],{"name":24,"affiliation":5,"role":25},"Navita Somaiah","PRINCIPAL_INVESTIGATOR",[27,32],{"name":28,"role":29,"phone":30,"phoneExt":13,"email":31},"Rei Kow","CONTACT","02034376805","rei.kow@icr.ac.uk",{"name":33,"role":29,"phone":34,"phoneExt":13,"email":35},"Lone Gothard","02086613460","lone.gothard@icr.ac.uk",{"type":37,"investigatorFullName":13,"investigatorTitle":13,"investigatorAffiliation":13,"oldNameTitle":13,"oldOrganization":13},"SPONSOR",[39],{"name":40,"class":41},"Case45 Ltd","UNKNOWN","100546577",false,"NCT06396754","Deployment and Clinical Evaluation of an AI-powered Digital Oncology Biomarker Tool to guidE Treatment in TNBC","AIDOBE","Inclusion Criteria:\n\n* Age ≥18 years\n* Confirmed diagnosis of triple negative breast cancer (non-metastatic)\n* Planned for neo-adjuvant systemic therapy\n* Written consent to generic Tissue for Research donation\n\nExclusion Criteria:\n\n* Patients declined consent for generic Tissue for Research donation","ALL","18 Years",{"count":51,"type":52},50,"ESTIMATED","OBSERVATIONAL","TILs have been shown to be predictive for response to neo-adjuvant chemotherapy in patients with TNBC in multiple studies (Level-1B evidence for clinical validity as per REMARK criteria). TNBC patients with excellent survival outcome and low incidence of metastasis can be identified using a manual TIL score.\n\nFurthermore, a fully end-to-end blinded evaluation of the same algorithm to be used in this study achieved \\>90% accuracy for predicting disease free survival (DFS) and overall survival (OS) in the pooled analysis of seven adjuvant phase-III TNBC trials.",[56],"Triple Negative Breast Cancer","NOT_YET_RECRUITING","2026-03-23",{"date":60,"type":61},"2026-03-27","ACTUAL",{"date":63,"type":52},"2026-08-01",{"date":65,"type":52},"2027-07-31",{"name":5,"class":6}]