Why Are We Still Doing Industrial Age Drug Discovery For Neglected Diseases in The Information Age?

Sean Ekins

Collaborations In 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

The Old School vs New School screening

• 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

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 PAPERS

NOT 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 trees To the air.. And do it virtually

Time for the New New School

Models replace testing

Testing = confirming

Predict in vivo and in vitro in parallel

MULTIDIMENSIONAL

Save resources

TO BE CONTINUED…

Joel S. Freundlich

Antony J. Williams

Alex M. Clark