The astonishing progress of combinatorial chemistry, the development of high throughput screening techniques, parallel computing, and quantum mechanics modeling approaches, among many other cutting-edge innovations, has derived in a Big Data explosion.
In parallel, the advent of structural biology, the omics revolution, and the extraordinary progress of computational science and communication technologies, have enables to face the most concerning challenges associated with the Big Data revolution: complexity, high scaling, speedy growth, source diversity, structure level, and uncertainty. 
Artificial intelligence (AI)-driven platforms hold the promise to smartly embody and reshape the most remarkable advances simultaneously reaching their apogee in the present era to energize the medical diagnostics industry with novel, smart approaches to digital pathology. 

The real potential of artificial intelligence (AI) to revolutionize digital pathology is just beginning to be noticed. 
AI-driven technology capabilities range from the acceleration of the computational analysis of atomic and molecular properties in the tissue, the bases of de novo diagnostics strategies, and drug response comparison, to the optimization of companion diagnostics methodologies and post-treatment surveillance policies.