Meghan Oates-Zalesky , Author at MadeAi

Scaling Scientific Data Review Without Adding Manual Bottlenecks

BlogJuly 31, 202642Views 0Likes 0Comments

Background: Scientific Data Review Evidence volumes are rising, but review teams are not. In 2010, the scientific community published roughly 75 trials and 11 systematic reviews daily, and this pace has only accelerated. Today, more than 200 new systematic review protocols are registered in PROSPERO every day, illustrating how demand for evidence synthesis has outpaced…

Deploying AI in Drug Discovery: Moving Past the Hype

White PaperJuly 28, 202655Views 0Likes 0Comments

Drug discovery is evolving rapidly, but successful AI adoption requires more than powerful models. It demands validated evidence, robust governance, and realistic expectations. AI empowers life sciences teams to accelerate drug discovery through evidence synthesis and expert human validation, delivering faster scientific insights while maintaining transparency, traceability, and regulatory-grade quality. Download Deploying AI in Drug…

How AI is Scaling Patient-Reported Outcomes into Structured, Submission-Ready Evidence

BlogJuly 28, 202644Views 0Likes 0Comments

Scaling Patient-Reported Outcomes In the world of clinical research and drug development, patients’ own voices matter more than ever. Patient-reported outcomes (PROs) capture how people actually feel, their symptoms, quality of life, side effects, and daily functioning. Yet turning these often messy, free-text or survey responses into clean, structured data that regulators can trust has…

How AI Helps HEOR Teams Build HTA-Ready Evidence Dossiers

BlogJuly 23, 202658Views 0Likes 0Comments

HTA-Ready Evidence Dossiers HTA (Health Technology Assessment)-ready evidence dossiers represent a critical deliverable for HEOR teams seeking market access and reimbursement for new therapies. These documents compile clinical, economic, and real-world evidence to meet strict requirements from health technology assessment bodies such as NICE, CADTH, or HAS. HTA-ready evidence dossiers demand more data, tighter timelines,…

Key Considerations for AI + RWE Implementation

When AI and RWE Converge: Accelerating Evidence for Rare Disease and Innovative Therapies

BlogJuly 15, 202662Views 0Likes 0Comments

Why Evidence for Rare Disease Matters AI and real-world evidence (RWE) are reshaping the path from laboratory discovery to regulatory approval. Their convergence matters most for patients who can't afford to wait. For patients with rare diseases, waiting for treatment can mean years of uncertainty. In the United States, a rare disease is generally defined…

Systematic Literature Review vs. Meta-Analysis: Choosing the Right Approach

BlogJuly 8, 202683Views 0Likes 0Comments

SLR vs. Meta-Analysis: An Overview You've just received a research question from your stakeholders. They want to understand the effectiveness of a new therapeutic intervention across the published literature. Naturally, your next thought is: should we conduct a systematic literature review (SLR) or a meta-analysis? In healthcare and life sciences, this question sits at the…

Meghan Oates-Zalesky

Scaling Scientific Data Review Without Adding Manual Bottlenecks

Deploying AI in Drug Discovery: Moving Past the Hype

How AI is Scaling Patient-Reported Outcomes into Structured, Submission-Ready Evidence

How AI Helps HEOR Teams Build HTA-Ready Evidence Dossiers

When AI and RWE Converge: Accelerating Evidence for Rare Disease and Innovative Therapies

Systematic Literature Review vs. Meta-Analysis: Choosing the Right Approach

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