iDRUG - intelligent drug discovery
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iDrug -The Age of Intelligent Drug Discovery
Sean Ekins
collabchem.com
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• Being ahead of the curve• Internet of Things– lab is wireless, control
everything from office• Personalized drug discovery from home• Beyond Apps – drug discovery workflows • One drug – many diseases = new blockbuster• Portals – data and predictions together• Who needs robots – can we automate more• Anyone can do a this – even you!
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http://goo.gl/UujRX
Ballel et al., Fueling Open-Source drug discovery: 177 small-molecule leads against tuberculosis ChemMedChem 2013.
GSK screened 2M compounds – 3 yrs beforeBayesian predictions for 14,000 cpds exposed 11 / 15 (73%) correct when paper was published Further prospective validation example
http://goo.gl/UujRX
http://goo.gl/UujRX
Bayesian models identified GSK TB hits 3 years earlier
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Predicted targets of GSK TB hits months earlier using TB Mobile
GSK report hits Dec 2012
24th Jan 2013 http://goo.gl/9LKrPZ
GSK predict targets Oct 2013
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The Internet of Things – your house is under control from anywhere – but what about your lab?
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What if our databases did more than house data – controlling its creation
• Enable connections to vendors– Assay Depot, CROs etc
• Facilitate outsourcing, insourcing data, cpds• Control lab equipment remotely, data upload• Control lab staffing, resources, plan useage• Why own the lab when someone else can –
but you control it (wherever it is)
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DYOD – design your own drugs
• Thanks to our genome screening all will have an idea of what enzymes, transporters we are deficient in
• We will know which drugs are metabolized by which enzymes and which transporters and involved
• Why not tailor drugs • What tools do we need?• How to predict enzymes, transporters?
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Transporters are the next big thing
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All Apped out?Prepare for apps to be around for a long time– Its what we do with them that matters
• Drug discovery Workflows– Connectivity– Shareability– Ease– Use across devices
• New drug discovery tools may go straight to apps and ignore desktop– E.g. green solvents app
• Desktop – diminishing importance– We better prepare for that
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Clark et al.,Submitted
App workflows
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One drug– many diseases – repurposing
• Disease A may have a market of $400M• Disease B may have a market of $600M• Alone they may not be big enough to entice a
pharma• Together it’s a $1bn dollar drug• Can we find examples 1 drug – many diseases
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TB and malaria
• 2 different diseases – combined deaths ~3-4M/yr R&D budget ~$1Bn
• 1 mycobacteria• 1 parasite• Shared targets• Screening data in TB• Actives vs different diseases• What if people are unaware of compounds with
dual activity?
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A computational window into data and models
Should there be more ?
Make them accessible to anyone
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Optimal Human properties
Optimal Mouse properties
Optimal TB entry properties
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Drug discovery is repetitive and there are 1000s of diseases
Drug discovery is high risk
Do we need robots or just smarter programs that discover the ideas we test?
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• Imagine having time / resources to mine datasets
• Imagine having time / resources to keep repeating vs different diseases
• Challenge is not creating the data but finding hidden value
• Anyone can do this, if the tools are available – experience not necessary
En route to treasure?
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iDrug Discovery