Article | “Machine Learning Drug Discovery Applications – Pfizer, Roche, GSK, and More”

To fully understand why drug companies are turning to AI requires a basic knowledge of how drugs are discovered and approved, so we’ll start with a simple overview of the drug discovery and approval process (if you’re an industry veteran, feel free to skip this section and scroll directly the AI use cases of the “big 5” drug makers).

Basics of Drug Discovery and Approval In simple terms, each potential drug is filtered through a system of a dozen progressively more expensive and involved tests/trials to determine if the potential drug is both safe and effective.

The below video from Pharmaceutical Research and Manufacturers of America (PhRMA) provides a concise overview of the process in the video below: The drug company will learn about a new biological discovery that provides insight into how the human body or harmful bacteria functions.

The company will then examine numerous compounds to find ones that may act on a specific discovery.

In the lab they will do basic tests for toxicity, to determine if the compound can be absorbed properly, to study how it might be metabolized etc.

Only compounds that pass these early tests will potentially move on to clinical trials so they can get government approval.

There are three phases of clinical trials, with each step requiring a larger number of volunteers and with more stringent criteria to pass.

The process takes several years and only a fraction of drugs make it through.

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