As a manufacturer of medicines, your company would be always on the lookout for coming up with new formulations and drugs which you can add to your product range. But even if you have a great new product, you wouldn’t be allowed to sell it unless it was approved by FDA, the US Food and Drug Administration, through its Center for Drug Evaluation and Research. The process involves the following three aspects :
This is a painstaking process involving, multiple trials and intense scrutiny before your drug is approved for sale. That is why the rate of declines is on the rise, and the pipeline of new products isn’t moving at great speed.
Almost every aspect of lives has become data-driven today. Some employers have begun analyzing social media interactions of applicants to help them decide who would fit their company’s culture best. Radio Taxi aggregators have picked up something which airlines have been doing for years, and now analyze real-time data of demand for their cabs in different parts of a city, and implement dynamic or surge pricing for their cabs. Several banks are analyzing spend and deposit data of their clients to design customized ‘push’ promotional campaigns for certain sets of customers and moving away from designing ‘one size fits all’ products.
How could a pharmaceutical company like yours ride this trend of using big data to its advantage, especially in the matter of obtaining FDA approvals? Let us discuss a few possible ways :
These are just a few ways in which technology and software solutions could help pharmaceutical companies present a better submission to the FDA, thereby improving the chances of acceptance and approval. With the rapid digitization of so many aspects today, it is imperative that the process of developing new drugs and obtaining FDA approval should also embrace the latest technology so that the rates of FDA approvals can be accelerated. There are several technology companies who would be willing to help your company take that step forward, provided you are willing to bolster the science of medicine with the science of data.