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Artificial Intelligence in Pharmaceuticals: Revolutionizing Healthcare

This is a governed preview built from the book’s published description and learning points. It is not presented as a chapter when no chapter sample is available in the website source.

AI is used in pharmaceuticals for drug discovery, trial design, patient matching, treatment personalisation, and the regulatory work behind medical progress. It stays with the decisions, constraints, and side-effects shaping Pharmaceuticals, especially where lab promise meets regulation.

What does this preview cover?

It covers the main use cases, the workflow and data changes behind them, the claims worth taking seriously, and the governance questions that show up once AI starts steering decisions in Pharmaceuticals.

What questions does the full book tackle?

• Where AI is already being used in healthcare today — and where lab promise meets regulation.
• The meaningful detail runs through trials, regulation, and lab friction.
• Key themes including diagnosis, monitoring, decision support, workflow.
• The limits, risks, and awkward questions worth asking before you sign off on the sales pitch.

Because decisions in Pharmaceuticals affect outcomes, safety, workload, and trust. Once AI enters the loop, sloppy assumptions get expensive very quickly.