Drug discovery is changing rapidly with the adoption of tools like artificial intelligence (AI) and more biologically relevant 3D culture-based assays. Compounded with tools like precision medicine and drug screening technology incorporating 3D cell culture, there is a wealth of untapped potential to be discovered and applied.

AI systems are becoming more prevalent in multiple stages of drug development. Drug developers are using AI systems to identify promising drug targets, predict the bioactivity and toxicity of new molecules, plan syntheses of novel compounds, design and prioritize drug leads, and look for potential ways to repurpose existing drugs. Keeping abreast of these innovations is essential in today's drug development world.

These tools are helping scientists predict protein structures and understand how drug candidates might bind to a protein of interest. Machine learning and physics-based computational drug design are being used to digitally screen billions of compounds.

Other AI platforms aim to help drug developers identify safety concerns and focus their laboratory and clinical trial efforts on the compounds most likely to succeed. For example, a research team in China developed a platform that uses deep neural networks to help drug developers predict which of their lead compounds is likely to have off-target effects on any of 391 kinases.

In conclusion, with the proliferation of AI systems and tools, many opportunities for research directions have arisen. Its utilization, in tandem with other strategies such as precision medicine and 3D cell culture, require levels of collaboration in order to facilitate future drug discovery processes and contribute to important programs such as cancer research.