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Angeline Dhas

Angeline Dhas is the Head of Product at MadeAi, with over 12 years of experience in healthcare, evidence generation, and life sciences technology. She specializes in the design and delivery of AI-powered solutions that streamline systematic literature reviews (SLRs), HEOR evidence generation, market access, and value dossier development. Her expertise spans end-to-end evidence workflows, including protocol design, literature screening, data extraction, evidence synthesis, and submission-ready documentation. Angeline’s work has helped organizations accelerate review timelines, improve consistency in evidence assessment, and support faster decision-making across medical affairs, HEOR, market access, and clinical development functions.

3 articles published
AI in Evidence Generation

ISPOR 2026: Beyond the Battle of the Bots, the Future of AI in Evidence Generation

AI in Evidence Generation was the quiet headline at ISPOR 2026 in Philadelphia this May. Most exhibit-hall chatter, though, was still about which chatbot gives the "smartest" answer. MadeAi presented four posters at ISPOR 2026. They covered literature review methodology, GenAI validation, drug repurposing, and social media listening for CSL Behring. Together, they tell a…

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AI-Augmented Literature Reviews

ISPOR 2026: AI-Augmented Reviews—A Multi-Project Analysis of Speed, Accuracy, and Workflow

AI-augmented literature reviews are transforming evidence generation across life sciences. This blog explores multi-project analysis of AI-assisted literature reviews. It examines improvements in review speed, screening accuracy, traceability, and workflow efficiency while maintaining rigorous human oversight for submission-ready outcomes. For teams in health economics and outcomes research (HEOR), regulatory affairs, and evidence generation, systematic literature…

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Identifying Drug Repurposing Opportunities with AI Literature Review

ISPOR 2026: Identifying Drug Repurposing Opportunities with AI Literature Review

AI-Assisted Drug Repurposing What if the next breakthrough treatment is already available today, hidden within existing drugs and waiting to be discovered? This question drives the growing field of AI-assisted drug repurposing, a smart and cost-effective strategy that looks for new therapeutic uses for approved medications. Unlike traditional drug development, which can cost billions and…

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