The Fifth Elephant 2017

On data engineering and application of ML in diverse domains

Data in drug discovery

Submitted by Shefali Lathwal (@shefalilathwal) on Friday, 9 June 2017

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Technical level

Beginner

Section

Full talk for data engineering track

Status

Submitted

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Total votes:  +2

Abstract

Data is being used to solve some of the greatest challenges in medicine today. Advances in technology mean that scientists have access to data that was impossible to acquire just 5 years ago. Modeling and analysis are driving improved understanding about how our bodies work. This in turn is helping scientists find cures for deadly diseases. Curing diseases now requires combined efforts of data scientists, software developers, computational biologists and experimentalists.

Our talk will focus on the role of data in biology and medicine. We will walk through the process of discovering a new drug and how data is embedded at every step of this process.

Our aim is to introduce engineers & data scientists to a new domain and encourage them to contribute to the advancement of science and human health.

Outline

  1. Introduction to the problem
    • Brief overview of drug discovery process
    • What do data in drug discovery mean?
  2. Story: From an idea to a pill
    • A broken car with billions of parts - biology works at many levels and the origin of a disease is narrowed down
    • What is wrong with the radiator? - After identifying the origin of the disease, the kind of defect needs to be investigated
    • How do you fix the car? - Model the biological system, use the data to create a biological story and treat
  3. The age of data in biology and medicine
    • Data is being acquired at unprecendented levels
    • Scientists need you to solve these problems - success is at the crossroads of computer science, maths, biology, and design

Requirements

Curiosity to learn, passion to make an impact

Speaker bio

Swetabh Pathak: Swetabh leads technology and operations at Elucidata. He wants to build a new kind of company which leverages technology to drive drug discovery. Prior to co-founding Elucidata, he has been a founding member at start-ups in technology and affordable STEM education. He completed his undergraduate and masters degrees in Mathematics and Computer Science from IIT Delhi.

Shefali Lathwal: Shefali leads research efforts on metabolic flux at Elucidata. She is passionate about using technology to help people and challenging herself to learn new things along the way. She holds a Ph.D. and M.S. in Chemical Engineering from MIT, and B.Tech. & M.Tech. in Chemical Engineering from IIT Delhi.

Slides

https://docs.google.com/a/elucidata.io/presentation/d/1_GI9s3FVH0jQN-vUQvItVNQgNmse2_GJ0xqFAo3bYFw/edit?usp=sharing

Preview video

https://youtu.be/rLZlllBb3Hk

Comments

  • 1
    Zainab Bawa (@zainabbawa) Reviewer a year ago

    The slides are not open. Please make the slides public to view.

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