Insilico Medicine publishes AI drug discovery chapters in Springer Nature volume

On January 9, 2026, the latest edition of Applied Artificial Intelligence for Drug Discovery was published online as a Springer Nature volume spanning 27 chapters authored by leading international experts. Insilico Medicine made exclusive contributions to two chapters in the volume. The contributions share experience in real-life application of artificial intelligence in early drug target-related tasks including evaluation and give prospects for the future assisted with quantum computing. The chapter titled Artificial Intelligence for Drug Target and Pathway Identification, Assessment, Validation, and Indication Expansion was led by Alex Zhavoronkov PhD, founder and CEO, CBO of Insilico Medicine. It demonstrates the AI-driven biology workflow from data analysis, target prediction and pathway identification to target validation and assessment and finally indication exploration. The chapter also examines future key challenges including data quality and regulatory changes. The chapter titled Drug Discovery with Quantum Machine Learning was led by Alex Aliper PhD, co-founder and president of Insilico Medicine. It presents the roadmap to 2030 starting with quantum machine learning algorithms along with several case studies of successful applications in drug discovery. The book obtained more than 1700 accesses only 10 days after publication. Alex Zhavoronkov said he is proud to see the decade of pioneering research serve as a cornerstone for this fundamental book for anyone interested in AI-driven drug discovery as this completes the cycle from theoretical exploration to academic publication then real-world application and back to industry-level guide.