One scientist will be able to generate more ideas and insights than a team of 100 could in the past.

One scientist will be able to generate more ideas and insights than a team of 100 could in the past.

In biotech that means:

Drug discovery: Today, discovering a new drug takes more than a decade. Many, if not most, diseases have no known treatments. AI can sift through tons of biological information to identify drug candidates and predict their effectiveness.

Manual data curation: Scientists spend most of their lives doing tedious, routine work. They pipette from one tray to another, manually curate data, and a lot more. AI can help with routine work while the scientist can think through the next experiment… the implications… the hypothesis, etc.

Biomarker discovery: AI can better detect patterns in genomic data to predict diseases based on genetic profiles, environment, and other factors.

Wearables: AI can track and summarize data from a bunch of sensors that reveal the impact of lifestyle, nutrition, and environment.

Personalized medicine: The current status quo relies on a one-size-fits-all approach. AI can identify personalized treatment options that are most likely to be effective for any given individual.

Clinical decision support: Analyze electronic health records and provide doctors with real-time recommendations for patient care. 

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