The AI Revolution Comes to Drugs

Developing a drug is a complex process that often fails. It begins by identifying a target, such as a protein or gene, associated with a disease. Researchers then search for a molecule that can either block or enhance the target’s activity safely. This can involve screening as many as 1 million compounds before selecting just one or two promising candidates. Software can help to identify such molecules. But generative artificial intelligence (AI) can dream up entirely new ones to test. BCG, a consultancy, estimates that about 65 AI-inspired molecules are currently being tested on humans.

Artificial Intelligence: Thriving or Teetering?

The artificial intelligence (AI) industry was caught between euphoria and caution. Alphabet (Google), Amazon, Meta and Microsoft raced to invest, spending nearly $200 billion on AI infrastructure. Nvidia, the leader in AI-chip production, reaped gigantic rewards. Sales of such chips are expected to have doubled in 2024, driving its valuation to nearly $3.4 trillion. Demand for AI servers surged: firms such as Dell and HPE reportedly doubled their sales. But cracks began to show. The soaring energy costs of training and running generative AI models raise questions about long-term economic viability.