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In this review, we summarize the current status of personalized drug selection based on genomic and molecular profiling and highlight the challenges how we can further utilize the individual genomic information. However, identifying patients likely to benefit from io and monitoring treatment response remains challenging. Additionally, ai facilitates the discovery of novel therapeutic targets, such as neoantigens, enabling the development of personalized immunotherapies.
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In this review, we present a brief explanation of the available technologies, the benefits of using these technologies in predicting immunotherapy response in lung cancer, and the expected future. This article explores how personalized medicine improves patient outcomes by identifying specific biomarkers that predict responses to immunotherapy, thereby increasing survival rates and minimizing adverse effects. Targeted therapies, immunotherapy, and liquid biopsy techniques have significantly improved patient outcomes while minimizing adverse effects compared to conventional treatments.
