Enhancing Clinical Translation of Cancer Using Nanoinformatics

Simple Summary Two fields of artificial intelligence and nanomedicine are very effective tools in moving towards the goal of personalized medicine. Combination of these fields, i.e., nanoinformatics, enables better access to patient data as well as better nanomaterials design. An ongoing challenge in all forms of drug administration for cancer patients is that drug synergy at any point in treatment is time-dependent, dose-dependent, and patient-specific. Moreover, high heterogeneities of intra-tumor and interpatient make it hard to rationally design diagnostic and dug delivery systems, as well as analyze their results. Integration of artificial intelligence methods (especially data mining, neural networks, and machine learning) can fill these gaps by using classification algorithms and pattern analysis to improve the accuracy of diagnosis, drug delivery, and treatment. In this study, the basic concepts in artificial intelligence are explained and the contributions of nanoinformatics in cancer treatment are reviewed. Application of drugs in high doses has been required due to the limitations of no specificity, short circulation half-lives, as well as low bioavailability and solubility. Higher toxicity is the result of high dosage administration of drug molecules that increase the side effects of the drugs. Recently, nanomedicine, that is the utilization of nanotechnology in healthcare with clinical applications, has made many advancements in the areas of cancer diagnosis and therapy. To overcome the challenge of patient-specificity as well as time- and dose-dependency of drug administration, artificial intelligence (AI) can be significantly beneficial for optimization of nanomedicine and combinatorial nanotherapy. AI has become a tool for researchers to manage complicated and big data, ranging from achieving complementary results to routine statistical analyses. AI enhances the prediction precision of treatment impact in cancer patients and specify estimation outcomes. Application of AI in nanotechnology leads to a new field of study, i.e., nanoinformatics. Besides, AI can be coupled with nanorobots, as an emerging technology, to develop targeted drug delivery systems. Furthermore, by the advancements in the nanomedicine field, AI-based combination therapy can facilitate the understanding of diagnosis and therapy of the cancer patients. The main objectives of this review are to discuss the current developments, possibilities, and future visions in naoinformatics, for providing more effective treatment for cancer patients.