Generative AI Poised to Revolutionize Cancer Drug Trials, Addressing Recruitment Failures and Costly Development
The development of new cancer drugs is an arduous and expensive process, often exceeding a billion US dollars and taking nearly a decade, with a high rate of failure. A primary reason for these failures is recruitment issues in clinical trials, a problem exacerbated by the increasing fragmentation of cancer entities into molecularly-defined subgroups in the era of precision oncology. This leads to multiple trials competing for a shrinking pool of eligible patients. Generative artificial intelligence (AI) is emerging as a potential solution by creating synthetic data that is indistinguishable from real data. This AI can generate medical images, text from electronic health records, and tabular data, including laboratory parameters, genetics, and outcomes. Unlike digital twins, which are digital replicas of individual patients, synthetic data statistically mimics feature distributions to create new samples without being exact copies of original training data. This technology aims to address the challenges of ... 
