Novel Strategies for the Treatment of Lung Cancer: An In-depth Analysis of the Use of Immunotherapy, Precision Medicine, and Artificial Intelligence to Improve Prognoses

Abstract: Therapeutic hurdles persist in the fight against lung cancer, although it is a leading cause of cancer-related deaths worldwide. Results are still not up to par, even with the best efforts of conventional medicine, thus new avenues of investigation are required. Examining how immunotherapy, precision medicine, and AI are being used to manage lung cancer, this review shows how these tools can change the game for patients and increase their chances of survival. In the fight against cancer, immunotherapy has demonstrated encouraging results, especially in cases of small cell lung cancer [SCLC] and non-small cell lung cancer [NSCLC]. A key component in improving T cell responses against tumours is the use of immune checkpoint inhibitors, which include PD-1/PD-L1 and CTLA-4 blockers. Cancer vaccines and CAR T-cell therapy are two examples of adoptive cell therapies that might be used to boost the immune system's ability to eliminate tumours. In order to improve surgical results and decrease recurrence, neoadjuvant immunotherapy is being investigated for its ability to preoperatively reduce tumours. Precision medicine tailors treatment based on individual genetic profiles and tumour features, boosting therapeutic efficacy and avoiding unwanted effects. For certain types of non-small cell lung cancer [NSCLC], targeted treatments based on mutations in genes including EGFR, ALK, and ROS1 have shown excellent results. When it comes to optimizing treatment regimens, biomarker-driven approaches guarantee that the patients most likely to benefit from particular medicines are selected. Artificial intelligence [AI] is revolutionizing lung cancer care through increased diagnostic accuracy, prognostic assessments, and therapy planning. Machine learning algorithms examine enormous information to detect trends and forecast outcomes, permitting individualized treatment techniques. AI-driven imaging tools enable early diagnosis and monitoring of disease progression, while predictive models assist in evaluating therapy responses and potential toxicity. The convergence of these advanced technologies holds promise for overcoming the constraints of conventional therapy. Combining immunotherapy with targeted treatments and utilizing AI for precision medicine delivers a multimodal approach that tackles the heterogeneous and dynamic nature of lung cancer. The incorporation of these new tactics into clinical practice demands cross-disciplinary collaboration and continuing study to develop and confirm their effectiveness. The synergistic application of immunotherapy, precision medicine, and AI constitutes a paradigm shift in lung cancer management. These discoveries provide a robust basis for individualized and adaptable therapy, potentially altering the prognosis for lung cancer patients. Ongoing research and clinical studies are vital to unlocking the full potential of these technologies, paving the way for enhanced therapeutic outcomes and improved quality of life for people battling this tough disease.