How can ‘big’ data help drug candidates through the pipeline? And who does the data belong to? LSIPR spoke to NuMedii chief executive Gini Deshpande.
R&D in the pharmaceutical industry is having a tough time. As blockbuster drugs fall foul of the so-called ‘patent cliff ’, and the cost of healthcare continues to rise, many big pharma companies, including Merck, Novartis and AstraZeneca, have resorted to laying off R&D staff to cut costs.
Pushing pipeline drugs through to the approval stage as quickly as possible is as crucial as ever, but the business of bringing new therapies to market from discovery to bathroom cabinets is an expensive and risky endeavour.
While it’s difficult to calculate the full cost of bringing a new drug to market, Forbes estimates that given the low success rate of drug candidates making it to market (95 percent of candidates fail to show their safety and efficacy, it says) on average, pharmaceutical companies will spend about $5 billion on each successful medicine.
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NuMedii, big data, drug discovery, de-risking, IP strategy