Life sciences companies face mounting challenges that are driving the urgent exploration of advanced technologies like artificial intelligence (AI). The costs of research and development, coupled with increasingly complex regulatory landscapes, put immense pressure on profit margins.

Traditional drug discovery and development processes are often slow and inefficient, with high failure rates—in fact, 90% of clinical drug development fail before innovations reach patients1 . In Good Manufacturing Practices (GMP)-compliant pharmaceutical manufacturing, unexpected downtime due to repairs or longer-than-anticipated maintenance or product changeovers can negatively impact productivity. Issues managing the supply chain for raw materials can also cause delays in the production of drug batches, with implications for meeting customer deadlines. Poor digital connectivity between the different systems and processes within a manufacturing facility—as well as between laboratories and downstream production infrastructure—can hinder the ability of life sciences companies to analyze data about performance and make informed decisions to improve operational efficiency.