Innovations in data visualisation for drug discoveryLindsay Edwards DPhil FRSBHead of Digital, Data & AnalyticsGSK Respiratory

Why are we here?

Anscombe’s Quartet

Anscombe’s Quartet

Visualisation in contrast with machine learning

• Visualisation is a key tool to support decision making

• Leverages human pattern recognition (wetware)

• Machine learning / statistics provide an answer (with

confidence bounds): uses hardware

• Visualisation keeps ‘a human in the loop’ (vs Augmenteed

Intelligence)

• Two famous examples of visualisations that supported

important decisions (one good, one bad)…

John Snow and the Broad Street pump

• In August / September 1854 there was a cholera outbreak in central London

• In 19th Century London, cholera had a 50% fatality rate

• At least 616 people died

• John Snow correctly tied the outbreak to a pump on Broad Street and removed the handle, thus halting

the outbreak

• How did he know?

https://www1.udel.edu/johnmack/frec

682/cholera/snow_map.png

The Broad Street pump

The Broad Street pump

• On 28th January 1986, the space

shuttle Challenger exploded, killing

all seven astronauts on board

• The cause was later traced to two

rubber ‘O’-rings that failed at low

temperatures

• This was known to be a risk, but the

launch went ahead anyway

• Why?

• 13 charts were faxed to NASA the

night before by Morton Thiokol (the

‘O’-ring manufacturer)

The Challenger Disaster

Edward Tufte’s plot

In data visualisation…

Improvements in browser technology are driving innovation

“Recently the combination of some powerful visualisation libraries

and a massive improvement in JavaScript’s performance have

opened the way to a new type of visualization, one that is easily

accessible, dynamic and actually encourages exploration and

discovery. The clear distinction between data exploration and

presentation is blurred. ..This is nothing short of a revolution.” - Kyran

Dale

Visualisation & data mining

• How do we effectively visualise high-dimensional data (not just

genomics!)

• How does the way we visualise data impact the decisions that we

make?

If we visualised the data a different way, would we make a different decision?

How sensitive are the decisions we make to the mode of visualisation?

• How can visualisation of our operational data transform our businesses?

• How can we use visualisation to aid the interpretability of machine

learning models?

Some questions for drug discovery