For decades the pharmaceutical industry has flourished on the discovery of new small molecule drugs. A paradigm change is now under way: as the best-selling drugs from the trailing end of this long-sustained wave of innovation loose their patent protection, they are not replaced to any extent that could be called sufficient – not economically, certainly not in terms of meeting of unmet medical need, not even in terms of chemical creativity. The much cited “patent cliff” is not the reason that the industry has reached this tipping-point; its a symptom. Small molecule drug discovery has degenerated into thrashing around for new molecules that can still be patented, and at the same time show some benefit (however incremental) over what is already known. If large pharma companies spend so much more on marketing and litigation than on drug discovery and development, this is symptomatic too.
Enter drug repurposing. People are now taking hard, bioinformatics-driven looks at well-selling drugs that are late in their life cycle — might they do something entirely unexpected? A sensible idea, and it has become a business model for dozens of small companies already.
We at H.M. Pharma Consultancy believe that certain other data sources are largely neglected in these repurposing efforts. So we are developing models where cutting-edge mining, extraction and assembly of all publicly available data come together: drug side effects, contextual information in the peer review and patent literature, and so on — all come together. In essence, its comprehensive open-source intelligence.
Isn’t somebody doing this already? Sure, its happening, at regulatory authorities such as the FDA and the EMEA. But their focus is on safety, and therefor defensive. Its also happening at large pharma companies, but mostly to build line extensions for their own drugs — also an essentially defensive angle. Our model is designed to take the offensive. Also, it does not focus on top-selling drugs — more likely, the opposite. The Failed Drug Database and our ThirdSpace application-focused patent database modules are designed for these datamining efforts. What we need now is partners, and financing.
If you believe that viable answers to pharmaceutical productivity can be found in creative, machine-assisted excavation of information that “is already somewhere out there,” though buried in published information that has never been properly analyzed from the perspective of alternate medical uses, please contact us at office@hmpharmacon.com — we have some interesting concepts.