Predicting Cancer Treatment Responses with AI Tool PERCEPTION
If you’re a cancer researcher looking to build artificial intelligence (AI) models that predict cancer treatment response, there’s a new resource available! A team led by Dr. Eytan Ruppin and Dr. Alejandro Schäffer developed an AI-driven tool called PERsonalized single-Cell Expression-based Planning for Treatments in ONcology (PERCEPTION).
You can access the tool and guides for using it via GitHub.
You can use PERCEPTION to predict:
- the success of targeted cancer drug treatments against cultured and patient-derived cell lines.
- cancer drug treatment response in patients with either breast, myeloma, or lung cancer.
- the development of resistance to treatment.
Although PERCEPTION studies didn’t show perfect accuracy, the findings show that the tool works better than earlier methods. Researchers also say the accuracy of the technique will improve as single-cell RNA sequencing data becomes more widely available.