How Data Analytics can Impact the Cost of Drugs
A 2016 article in Nature Reviews Drug Discovery says the number of drugs invented per billion dollars of R&D money invested, is reduced by half every nine years. This pattern is being seen for the past half a century.
Some other statistics that will make you sit up are:
· Only one out of every 10,000 discovered compounds becomes an approved drug for sale;
· Only three out of every 20 approved drugs bring in enough revenue to cover developmental costs;
· Only one out of every three approved drugs can create enough income to cover the development costs of prior failures;
On an average it takes 7–20 years and close to 500 million dollars to bring in any new drug into the market.
Technically, this also means that there is a vast amount of data in the form of experiments, clinical trials and other research data. The Pharmaceuticals Industry is the perfect working-ground for slicing and dicing data and coming up with some meaningful information and useful patterns. This will help in making informed and accurate decisions that will reduce the number of R&D cycles and hence make drugs cheaper.
For effective use of data analytics tools and technologies in the pharmaceutical industry, there has to be more collaboration in terms of sharing data. Data from all sources like customer, physician, hospitals, distributors, insurance companies will all have to come together if we can get the right data set to be able to perform some fruitful data analytics. As smarter and miniature sensors, devices, mobile apps are being built and used by ‘Pharma’ consumers it has never been easier to get real time data from customers. Pharmaceutical companies are increasingly collecting and analyzing this data to help reduce R&D and make drugs more effective.
The Pharmaceuticals Industry needs a model where data can be shared/collated without the fear of data breach or data security being compromised.
Data Analytics in the Pharmaceuticals Industry:
Incedo works extensively with the Pharmaceuticals Industry. Incedo’s array of services in the (https://www.incedoinc.com/lifesciences) MDM in pharma Pharmaceuticals space include Sales and Marketing, Operational areas as well as Research and Development. With a multitude of ‘Pharma’ clients, (https://www.incedoinc.com/workatincedo) Incedo understands the scenarios in which data analytics will bring about predictive outcomes.
To elaborate — Can we look at all the possible ‘side effects data’ in order to predict if the compound will provoke adverse reaction even before it reaches the trial stage?
By looking at the virtual databases of molecular and clinical data is it possible to filter out likely candidates with the help of criteria based on chemical structure, diseases/targets, genetic breakdown etc.?
To maximize the benefits from Data Analytics in the Pharmaceuticals Industry, a lot of changes need to happen including but not limited to enforcing physicians and hospitals to have electronic health records, collection of data from various collection points, having the right models built by working closely with the relevant academic institutions, having policies and laws in place to restrict the amount a company can spend on R&D and thereby making drugs cheaper. Another challenge in the Pharmaceuticals Industry is transforming the culture as doctors and hospitals tend to adopt technology very cautiously and rightly as stakes are very high. The industry is dealing with life-saving and disease curing drugs.
(https://www.incedoinc.com/whatwedo)Incedo Inc. understands that the (https://www.incedoinc.com/lifesciences) Data Management in Pharma industry is in a state of constant transformation. Many areas are changing like — the way we doctors communicate and interact with patients, the way R&D is done on drugs, the ways patients get to know about potential risks and diseases upfront. As the world is coming to terms with driverless cars and the modes of communication across the globe, there is also a fundamental shift in the way drugs are manufactured. This shift will ensure reduced costs of drugs with the help of reduced cycle time of clinical trials.