Post on 06-Jan-2016
description
Why Are We Still Doing Industrial Age Drug Discovery For Neglected Diseases in The
Information Age?
Sean Ekins
CollaborationsIn Chemistry,Fuquay Varina, NC
Some Technologies change faster than we do
But Drug Discovery has not changed much in 40 years
Because change happens slowly
Drug discovery is a very slow race… that needs a kickstart
And of course no treatments for neglected diseases are blockbusters
Still valuing the 70’s BLOCKBUSTER model but its changing
Produce few of …
The Old School vs New Schoolscreening
• New School - Many hurdles before in vivo - lots of data Yet HTS started in the 1980’s!!
• Old school – go in vivo at outset – little data
• New database technologies work well for New school but ..Old School type data ?
Drug Discovery Archeology
• Still a heavy emphasis on “testing” “doing “ rather than ‘learning’
• Mining data and historic data will increase in value
• Data becomes a repurposing opportunity
• How do we position databases for this?
• What about neglected diseases?
Now neglected diseases has big data too
A computational window into data and models
Should there be more ?
But what about small data?
• In some cases its all we have• In vivo data is not high throughput
• Small data builds networks DATA
V
http://smalldatagroup.com/
Ponder et al., Pharm Res In Press 2013
Tested >300,000 molecules Tested ~2M>1500 active and non toxic Published 177
Big Data: Screening for New Tuberculosis Treatments
How many will become a new drug?How do we learn from this big data?
«Tuberculosis» 333 papers in PubMed«Malaria» 301 papers in PubMed
Small data: Mouse In vivo model data
Can combining Big and Small data (in vitro, in vivo) help us find better compounds, faster ?
Avoid testing as many molecules
Connecting data/tools like a TB Spider
In vitro data In vivo data
Target data
ADME/Tox data & Models
Drug-like scaffold creation
TB Prediction Tools TB Publications
Where are the New TB drugs to be found?
In vivo actives (yellow)
Optimal Human properties
Optimal Mouse properties
Optimal TB entry properties
Filling the toolbox
• Who has the data?• Who has the models?• Who has molecules?
Drug Discovery Toolbox
Hunting for the in vivo data
It’s out there.. be patient
30 years with little TB mouse in vivo data
TB
MoDELS RESIDE IN PAPERSNOT ACCESSIBLE…THIS IS UNDESIRABLE
Hunting High and Low for new molecules to test
We need to search sources..From the Oceans…
To the ground To the treesTo the air..And do it virtually
Time for the New New School
Models replace testingTesting = confirmingPredict in vivo and in vitro in parallelMULTIDIMENSIONALSave resources
TO BE CONTINUED…
Joel S. FreundlichAntony J. WilliamsAlex M. Clark