When we think of drugs used for more than one different disease (e.g. a drug that’s not just used for 2 different cancers) we can probably list them on one hand. These are usually the result of a happy coincidence or happy experiment more likely. We can call it repurposing. Repositioning, rebranding, reuse or whatever.. But it raises another question at a time when costs of development are so high and drug approvals have stagnated for well over a decade Or for many decades.
What if from the out set we could design, find and develop one drug that simultaneously could be approved and used for 2 or more very different diseases. We would perhaps save some money at least on the preclinical side we would hope and maybe a little on the tox side for a completely NDA.
What made me think more seriously about this was our recent analysis of the money going into neglected diseases, it is pretty clear from this that it’s not going to cover many clinical studies, in our wildest imaginations without some really novel approaches being used. So then I thought what if we could find a drug that could be efficacious against 2 neglected diseases. I am pretty sure this Is not a novel idea, but can we find any attempts? Certainly you will see scientists look at conserved targets across organisms and test compounds. But there are not examples in which a small molecule is very active against 2 distinct organisms and their targets. Or is there? Could it be that we just have not looked? Could it be that the data is out there but the mining has not been done. I recently wondered whether simply looking at enough datasets in each case for two different organisms would turn up compounds that overlapped. I reasoned that at least 4 datasets for each would be a good start. In an N = 1 experiment I found 15 sub MicroM inhibitors for 2 very different neglected diseases. Does this prove that a drug targeting 2 diseases could be initiated from what we already know? Possibly? Is this something doable yes. I am only scraping the surface. My selection of targets was biased to examples with recent public datasets. I now want to see if we can identify the targets or at least propose them for each organism. would it be a surprise if they were different targets? apologies for the slight vagueness but my plan is to ultimately publish this elsewhere so all will be revealed in due course.
I am pretty sure that after spending a day at the SLAS meeting in San Diego and listening to the various debates like phenotypic vs target screening and hearing continually the difficulties in pharma, perhaps we could be comparing different datasets more frequently and looking at the shared compounds. In order to do this you need the data, database tools that enable such comparisons and probably a degree of patience. Just leaves you wondering if anyone has time for that.
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