Shashidar Reddy Abbidi

Join Skye Hodson, VP of Clinical Solutions, on Thursday, August 20, 2026, at 11 a.m. ET to learn how trusted data and targeted AI can improve clinical trial design, planning, and execution. The session covers drivers of trial complexity, AI-supported protocol design, data-informed site selection, effective patient recruitment strategies, and alignment with evolving regulatory expectations, including ICH GCP E6(R3).

By Shashidar Reddy Abbidi, senior clinical data manager Clinical trials have become data ecosystems, as single studies now draw information from EDC systems, central laboratories, imaging vendors, wearable devices, electronic health records, safety systems, and specialized external vendors. For clinical data managers, this growth has created an opportunity to generate richer evidence faster. It has also exposed a persistent operational bottleneck: data friction.

Authors Karnaditya Rana, Shashidar Reddy Abbidi, Debashree Sinha, Shalmali Joshi Author Abstract The quick growth of clinical data in oncology research has made it difficult to extract and manage data which needs to be processed for clinical trials. The medical field considers manual curation to be the highest standard but its use has become restricted because of time and financial requirements and difficulties with different people judging the same material.