Boston, Massachusetts, August 17, 2026
PhaseV, an artificial intelligence and machine learning company focused on clinical development, has announced findings from a new independent industry survey highlighting significant delays, costs, and workflow complexity across clinical trial data and reporting processes. The survey gathered insights from more than 50 senior executives at global pharmaceutical and biotechnology companies working across clinical operations, biostatistics, statistical programming, and regulatory affairs. The findings show that 88% of sponsors spend five weeks or longer managing critical-path statistical programming and reporting, while fragmented vendors and repeated protocol amendments add further operational burden throughout the clinical development lifecycle. The report points to increasing demand for AI-driven automation to reduce manual handoffs, improve workflow consistency, and accelerate the movement from protocol development through regulatory submission.
Clinical Trial Reporting Creates Major Delays
The survey, titled The State of Clinical Trial Data Handoffs: Spend, Timelines, and Vendor Dynamics, found that delays begin before clinical trials are fully underway. More than half of sponsors, or 51%, reported that pre-trial activities typically require five to eight weeks, covering work such as study synopses, protocols, schedules of assessments, and case report forms. Reporting activities later in the clinical development process can take even longer. According to the survey, 33% of respondents require nine to 12 weeks to complete statistical analysis plans, SDTM and ADaM datasets, tables, listings and figures, and clinical study reports, while another 43% reported timelines of five to eight weeks. These activities are critical to study execution and regulatory reporting, meaning prolonged workflows can create downstream pressure on development schedules and resources. The findings highlight how manual processes can contribute to delays as clinical programs progress toward data analysis and submission.
Vendor Fragmentation and Protocol Changes Add Complexity
The survey also identified vendor fragmentation and repeated protocol amendments as significant contributors to clinical trial workflow complexity. Sponsors reported completing an average of four protocol amendments during a typical Phase II or Phase III trial, creating additional work and increasing the number of activities that must remain aligned across teams and systems. Vendor management further complicates the process, with 76% of sponsors using up to three vendors per trial across the surveyed workflows and another 12% managing four to five vendors. These fragmented arrangements can create multiple manual handoffs between organizations responsible for different components of trial reporting and data workflows. Costs also increase as programs advance, with median post-trial workflow spending among large pharmaceutical and biotechnology respondents rising from approximately $250,000 in Phase I to $900,000 in Phase III. Across a program’s lifecycle, external workflow spending can exceed $3 million, according to the survey findings.
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AI Automation Targets Clinical Development Bottlenecks
PhaseV said the survey results demonstrate an industry need for more connected and automated clinical development workflows. Its AI Conductor platform uses the company’s causal AI and machine learning technology to automate clinical trial documentation and statistical programming from protocol development through regulatory submission. The platform is designed to generate protocols, statistical analysis plans, ADaM and SDTM datasets, tables, listings and figures, and other submission-related assets while maintaining alignment across documents and stakeholders. By connecting activities that traditionally involve multiple manual steps and vendors, PhaseV aims to reduce repetitive work, improve consistency, and support regulatory readiness. The company said it has supported more than 80 clinical trials for over 50 global sponsors, including eight of the top 20 pharmaceutical companies, and its platform is supported by a data lake containing more than 10 million patient-level records. For cGxP.wire readers, the survey is significant because it highlights persistent challenges in clinical trial data management, statistical programming, regulatory documentation, vendor coordination, and AI-enabled automation. As pharmaceutical and biotechnology companies face pressure to control development costs and shorten timelines, connected digital workflows could become increasingly important across the clinical development lifecycle.
Source: PhaseV press relese
