Pharma teams are turning to AI because the pressure is real.  Discovery timelines stretch past 10 years, clinical failure rates hover around 90%, and quality issues still trigger costly investigations and delays.  The challenge isn’t finding AI tools – there are countless on the market – it’s knowing which ones solve the problem you have.  […]