How do you speed up oncology literature screening while ensuring validated results?
In this case study, MadeAi partnered with Roche to accelerate primary screening for PD-L1+ NSCLC studies using a GenAI-enabled, protocol-driven approach. By translating PICOS criteria into 12 algorithmic inclusion tags and combining AI-driven screening with parallel manual validation, the team achieved 95.5% AI-to-manual agreement and 95.98% exclusion sensitivity.
See how AI-driven screening, protocol-based logic, and validation workflows came together to enable faster, more cost-effective SLR execution.
Meet the Presenters
Kavin Xavier
Vice President – AI Solutions, CapeStart
With years of experience designing AI solutions for life sciences, Kavin leads CapeStart’s AI innovation roadmap.
Siva Karthick
Machine Learning Tech Lead, CapeStart
Siva specializes in model fine-tuning and evaluation, focusing on real-world deployment of AI in healthcare and pharma.
