Welcome to episode 446 of the AI in Action podcast, the show where we break down the hype and explore the impact that Data Science, Machine Learning and Artificial Intelligence are making on our everyday lives.

Powered by Alldus International, our goal is to share with you the insights of technologists and data science enthusiasts to showcase the excellent work that is being done within AI in North America and Europe.

Today’s guest is Naisha Shah, VP of Data Science at BioAge Labs in California. Founded in 2015, BioAge are on a mission to develop a pipeline of treatments that extend healthy lifespan by targeting the molecular causes of aging. BioAge takes a human-centric, data-driven approach to identify the molecular features of healthy aging and reveal the causes of age-related diseases. By targeting aging with a large and mechanistically diverse portfolio of drugs, they will unlock opportunities to treat or even prevent these diseases in entirely new ways.

Naisha leads a team of data scientists at BioAge that are developing statistical, Machine Learning and AI pipelines to identify targets for new therapeutics to increase healthspan. The team leverages proprietary human cohorts with longitudinal omics and phenotypic data for data-driven insights into mechanisms of aging and age-related diseases. Naisha brings 10+ years of experience in computational analysis of multi-omics, clinical, imaging, EHR, and other phenotypic data to gain insights into human diseases.

In the episode, Naisha will talk about:

Their mission and unique approach at BioAge Labs

Six steps to how their platform works

The role of Data Science at BioAge

An insight into the day-to-day life of the data science team

Challenges to overcome in achieving their mission

How she stays motivated on long-term goals

What the future holds for BioAge Labs

To find out more about all the great work happening at BioAge Labs, check out the website www.bioagelabs.com or follow them on LinkedIn and Twitter @bioagelabs. You can also connect with Naisha directly on Linkedin.

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