The use of empirical data drives modern businesses. Data is like life’s blood for pharmaceutical companies. To find out what therapies work and don’t, they heavily rely on statistics.
As it turns out, the pharmaceutical industry’s growth and value are being driven by data analytics. Pharmaceutical businesses can gain a competitive advantage by exploiting the power of “big data” and the wealth of information it contains. So, data analytics in pharmacy is the key to success. Perfect. Despite having access to data analytics, most firms feel like they’re groping in the dark. Why?
To get the most out of data analytics, pharma businesses should focus on six critical areas outlined in this article.
First and foremost, drug discovery and development
One of the most important ways a pharmaceutical firm makes money is by researching and developing new drugs. Despite this, it is one of the most demanding, expensive, and time-consuming processes in the world today. Developing a drug and bringing it to market is no easy undertaking, but with the help of analytics, you can speed up the process.
How does Data Analytics help pharmaceutical companies?
Tremendous opportunities abound with the expiration or impending expiration of several popular medications’ patents. These opportunities can be promptly identified using data analytics in the pharmaceutical industry. Predictive algorithms applied to large datasets, such as control group data, scientific publications, and academic research papers, can be used to quickly and more efficiently discover and develop new drugs for the market, thus reducing the time to market.
A clinical trial can take months, if not years, to complete. This multi-stage process requires rigorous historical, demographic, and genetic data analysis. Subsequent drug tests must then demonstrate the drug’s efficacy based on this data collection. Only then can it go on the market. Analytics, if utilized correctly, can speed up this process and improve clinical trials, according to experts.
Many companies can analyze large datasets, including demographic, historical, clinical trials, and remote patient monitoring, in a much shorter period thanks to data analytics. This data can assist pharmaceutical companies in detecting probable adverse effects and specialized patient groups, resulting in lower trial costs, more clinical studies, and a greater number of clinical trials.
With the support of Project Data Sphere, over a dozen international pharmaceutical companies have agreed to exchange cancer research data from the past. Additionally, data analytics plays a significant part.
Developing targeted and tailored treatments
Because no one-size-fits-all system exists in medicine, identifying the underlying causes of individual illnesses is a complex undertaking. Medical sensor data (devices worn by patients) and electronic medical records are used to discover pharmaceutical companies’ root causes of specific diseases.
How can Data Analytics be of use in the following situations?
By analyzing large amounts of unstructured genomic, sensor, and medical record data using big-data analytics software systems (e.g. Hadoop), pharmaceutical companies can better target specific patient groups and develop personalized medications.
Capture the attention of both patients and healthcare providers
Pharmaceutical companies can still gather valuable information about patients’ and HCPs’ interests in a specific drug or treatment even if they leave the safety and security of medical labs. The best place to find and gather this information is on social media. When it comes to promoting growth, one of the most overlooked components is capturing the interest of individuals.
How Data Analytics can be of use in the following situations?
There is a lot of data analytics in social media to collect, sort, and analyze information about drugs that patients and healthcare professionals are passionate about. Additionally, pharma businesses can use this information to track the popularity of a drug or treatment, their competitors’ products, and their brand to keep an eye on the patient and health care professional perceptions of their products and those of their competitors.
Improve patient involvement and satisfaction by learning about their behaviour
Big data can help pharmaceutical businesses obtain insights into patient behavior. Every patient’s treatment is different. Therefore, it can be challenging to know what they get and what they don’t. However, pharmaceutical businesses can use big data to examine patient behavior and develop solutions that can ensure and improve treatment outcomes.
How can data analytics be of use in the following situations?
Pharma businesses can acquire insights into the complicated world of patient behaviour using advanced analytics tools and pertinent data. As an example, data analytics can identify groups of patients who fail to show up for their hospital appointments or forget to take their medication on time. Timely push notifications on a patient’s mobile device can serve as a timely reminder from the hospital or pharmaceutical company.
Keep an eye on your sales and marketing results
Sales and marketing play a critical role in the pharmaceutical industry’s revenue generation machinery. Pharma businesses place a high value on monitoring the performance and efficiency of their sales and marketing pipelines. The larger the company, the more difficult it is to keep track of these results. In today’s digital world, pharmaceutical companies can keep track of their sales and marketing efforts using data-driven apps and dashboards.
Some ways pharmaceuticals companies ensure success with data analytics
Sales and marketing data can be examined in a centralized system, such as the success of the sales pitch, lead generation information, and competition analysis. Filling in these gaps and strengthening the sales and marketing funnel is done using this information.
Pharma firms can benefit significantly from an analytics dashboard. These dashboards may give you a birds-eye perspective of your entire sales and marketing ecosystem, as well as predictive analytics that indicate what you should do next. Pharma businesses should focus on the most pressing data analytics issues. Acquiring knowledge of the tropes of unstructured data collection and then applying that knowledge to the extraction of valuable data
Actual world data usage: Having access to Real World Data (observational data) such as electronic health records, claims, disease registries, and billing activities and deriving valuable insights from these sources. Making smart data from massive data requires the proper infrastructure. Making use of unstructured data necessitates first putting together a sound technological foundation.
The IoT Academy is the one-stop solution for all the data science enthusiasts out there. You can get in touch with the industry experts and can get deep insights into its real-time applications.
