From In Silico Hypothesis to Validation: The Role of Real-World Evidence in the Preliminary Verification of AI-Generated Drug-Repositioning Candidates: A Comprehensive Review

The integration of AI-based analytics with RWE provides a promising framework for the preliminary verification of computational predictions, potentially informing the translational pathway toward clinical practice. However, the effectiveness of this approach remains dependent on data quality and the specific therapeutic context, requiring further standardization of clinical data.

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Publication Details

Journal
Journal of Clinical Medicine
Published
2026-04-07
DOI
https://doi.org/10.3390/jcm15072801
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

From In Silico Hypothesis to Validation: The Role of Real-World Evidence in the Preliminary Verification of AI-Generated Drug-Repositioning Candidates: A Comprehensive Review

Krzysztof Wójcik, Karolina Jankowska, Anna Bielecka, Michał Gałuszewski et al.
Journal of Clinical Medicine
Artificial Intelligence in Healthcare and Education
article

From In Silico Hypothesis to Validation: The Role of Real-World Evidence in the Preliminary Verification of AI-Generated Drug-Repositioning Candidates: A Comprehensive Review

Krzysztof Wójcik, Karolina Jankowska, Anna Bielecka, Michał Gałuszewski, Jan Olszewski
article en

Abstract

The integration of AI-based analytics with RWE provides a promising framework for the preliminary verification of computational predictions, potentially informing the translational pathway toward clinical practice. However, the effectiveness of this approach remains dependent on data quality and the specific therapeutic context, requiring further standardization of clinical data.

Journal of Clinical MedicineVol. 15(7)
Medical University of Silesia (PL)
Industry, innovation and infrastructure
Openalex Percentile: Top 26%
Artificial Intelligence in Healthcare and Education
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