Artificial intelligence has started to transform how new medicines are discovered and developed. For someone with a basic understanding of AI, it helps to see where it fits in the drug development process.

AI is already being used in early discovery to screen millions of molecules, predict which ones are likely to work, and even design entirely new ones. In clinical trials, it helps identify the right patients faster and monitors their health in more precise ways. In manufacturing, AI detects issues before they become problems and improves quality control.

To make AI successful in this industry, good data is critical. Data needs to be complete, unbiased, and standardized. Experts must work closely with AI tools to interpret results and ensure ethical decisions. Bias is a serious concern because if historical data is flawed or unrepresentative, AI can reinforce inequities or lead to wrong conclusions. Human oversight remains essential at every stage to avoid mistakes and build trust.

Some remarkable advances have already happened thanks to AI. Tools like AlphaFold solved protein structures, which helps scientists understand disease mechanisms. AI-designed molecules have entered clinical trials faster than ever before.

Looking ahead, AI could make drug development faster, more precise, and more affordable. But competition is heating up as countries around the world invest in AI-driven life sciences. Generics and biosimilars will still play a role in lowering costs, and AI may even help optimize these processes too.

The future of life sciences will depend on how well we combine technology, human expertise, and global collaboration to bring better medicines to patients everywhere.