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. 

Comments

Popular posts from this blog

decouple carbon emissions from economic growth.

10 Steps to Financial Health in the New Year

Protect your heart with natural vitamin A