The implementation of precision medicine is riddled with problems that require complex optimizations. For genetic disorders, the success of precision medicine depends on the optimization sensitivity and specificity of multidimensional clinical and biological data. For neurodevelopmental disorders (NDD), the complexities are even greater due to the phenotypic and genotypic heterogeneity. Traditional algorithms for certain problems (i.e. gene-gene interactions, drug design) in neurodevelopmental disorders cannot produce optimal solution and demands an alternative efficient approach. Artificial intelligence (AI) algorithms are now capable of efficiently optimizing such multidimensional datasets. The capability of AI has been shown and replicated in many other disciplines in medicine (i.e. cancer, medical imaging). Much hope is now pinned on the opportunity to quantify risk from patterns of genomic variation, including the functional characterization of genes and variants, through the application of AI for problems in neurodevelopmental disorders.

In this review, we discuss the fundamental machinery of AI algorithms (deep neural network and evolutionary algorithms) that can potentially have significant impact resolving problems related to broader neurodevelopmental disorders. We have discussed in depth the key unresolved issues in NDD and how AI can impact by modeling solutions related to new gene discovery, gene-gene interactions, phenotypic-genotypic heterogeneity, and drug discovery. We have discussed how artificial intelligence alongside with genomics can be at the center of precision medicine solutions for neurodevelopmental disorders. This paper discussed the application of AI within the context of neurodevelopmental disorders complexities. We have pointed out what is feasible for AI to achieve and the challenges that is far too complex to implement. We have portrait some scenarios where integrating AI with other emerging cutting edge technologies (i.e. CRISPR/Cas9, brain organoid, antisense therapy) might create massive impact in neurodevelopmental disorders diagnosis and therapeutics. 

References: 

Artificial intelligence for precision medicine in neurodevelopmental disorders, M Uddin, Wang and Woodbury-Smith, npj Digital Medicine volume 2, Article number: 112 (2019).

https://www.nature.com/articles/s41746-019-0191-0