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The journey to developing a successful drug, theoretically, may appear linear: you discover the right drug, find the suitable patient and administer it at the right time. The reality, however, often deviates from this straightforward path. Aligning these three variables remains notoriously difficult, often leading to elongated timelines strewn with failures, sometimes extending over a decade with costs often in the billion-dollar range.In recent years, the use of AI in drug discovery and development has grown swiftly, marking a significant shift in how we understand, discover and develop new drugs. The technology promises to chip away at timelines and save the industry billions of dollars eventually. But those promises aren’t exactly new. Even before ChatGPT became popular, many drug developers were working with high-end algorithms to “try to really hone in on databases,” said Andrew…