Reimagining IEP with Evidence AI Analyst: From siloed tasks to intelligent orchestration

Integrated Evidence Planning (IEP) has never lacked rigor. What it has lacked is coherence. 

For years, IEP has been executed through structured templates, static plans, and cross-functional discussions focused on aligning studies, analyses, and publications to an asset milestone. The intent was sound. The execution was disciplined. Yet outcomes often fell short when evidence met real-world decision-making. 

Assets achieved regulatory approval, only to encounter unexpected HTA objections. 
Teams entered expert discussions knowing the evidence existed, but struggled to assemble it in time. 

Critical signals were visible in hindsight, but missed when they mattered. 

These are not failures of science, capability, or strategy. They are failures of evidence orchestration. 

This white paper examines how IEP is evolving and why AI powered evidence planning is becoming central to its next phase. 

What this white paper covers 

• Why IEP breaks down when evidence is treated as a static plan rather than a living system 
• How fragmentation across clinical, RWE, HEOR, medical insights, and publications obscures decision-critical signals 
• Why traditional planning cycles cannot keep pace with shifting regulatory, payer, and competitive expectations 
• How AI for planning enables evidence to be searched, synthesized, and interpreted across systems 

This paper is written for leaders and evidence teams who recognize that the challenge today is not generating more data, but making sense of what already exists. 

Download the white paper