The Radiotherapy Planning Assistant uses convolutional neural networks and dose-calculation models to automate contouring and beam optimization, aiming to standardize care quality across diverse settings and reduce patient wait times.

An international ARCHERY trial demonstrates that AI can design high-quality radiotherapy plans for cervical, prostate, and head-and-neck cancers, enabling faster and potentially more widely accessible treatment.

The AI tool automates identifying target structures and optimizing radiation beam plans, substantially reducing reliance on highly specialized staff and cutting planning timelines from hours or weeks to about one hour.

The Radiotherapy Planning Assistant, developed by MD Anderson Cancer Center, was evaluated in a multicountry trial funded by NIH, the Rising Tide Foundation, and the UK Medical Research Council.

Experts note radiotherapy is a central cancer treatment benefiting roughly 40% of cases, but access gaps persist, especially in low- and middle-income countries with limited radiotherapy resources.

Funding and collaboration come from NIH (US), Rising Tide Foundation, and UK Medical Research Council, with coordination by the UCL Innovative Clinical Trials Unit and centers spanning Africa, Asia, the Middle East, and Europe.

Experts regard this as a landmark validation of AI in oncology, with the potential to improve access, efficiency, and cost-effectiveness of radiotherapy, particularly in regions facing workforce shortages.

Key figures Ajay Aggarwal and Mahesh Parmar emphasize AI’s potential to save lives by increasing radiotherapy access and reducing waiting times, aligning with global cancer elimination goals.

Aggarwal and Parmar highlight the trial’s scale and generalizability, suggesting it advances beyond prior smaller studies.