  This paper examines how pharmaceutical Artificial Intelligence advancements
may affect the development of new drugs in the coming years. The question was
answered by reviewing a rich body of source material, including industry
literature, research journals, AI studies, market reports, market projections,
discussion papers, press releases, and organizations' websites. The paper
argues that continued innovation in pharmaceutical AI will enable rapid
development of safe and effective therapies for previously untreatable
diseases. A series of major points support this conclusion: The pharmaceutical
industry is in a significant productivity crisis today, and AI-enabled research
methods can be directly applied to reduce the time and cost of drug discovery
projects. The industry already reported results such as a 10-fold reduction in
drug molecule discovery times. Numerous AI alliances between industry,
governments, and academia enabled utilizing proprietary data and led to
outcomes such as the largest molecule toxicity database to date or more than
200 drug safety predictive models. The momentum was recently increased by the
involvement of tech giants combined with record rounds of funding. The
long-term effects will range from safer and more effective therapies, through
the diminished role of pharmaceutical patents, to large-scale collaboration and
new business strategies oriented around currently untreatable diseases. The
paper notes that while many reviewed resources seem to have overly optimistic
future expectations, even a fraction of these developments would alleviate the
productivity crisis. Finally, the paper concludes that the focus on
pharmaceutical AI put the industry on a trajectory towards another significant
disruption: open data sharing and collaboration.
