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As data is widely available and digital tools provide opportunities to optimize patient and consumer relationships pharma companies are leveraging data analytics.
FREMONT, CA: The pharmaceutical companies market has been growing exponentially worldwide and is expected to reach $1.170 billion by the end of 2021. Most of this growth has depended on the empirical data that has presented significant challenges over the last decade. The usage of data analytics in order to combine via available big data can provide valuable insight to the pharma companies concerning the necessities, contradictions, usage, market trends, and sales performance.
Here are three ways how the leading pharma companies are already using data analytics.
Using big data to design targeted medications for patients, doctors, researchers, and reviewers
Today, many start-ups use AI and ML-based technology to assess the massive volumes of data on healthcare, clinical trials, and drug reviews from numerous sources.
For instance, companies have dedicated cloud databases that gather data from significant patent offices, regulatory bodies, clinical trials, and other authentic sources. Pharma companies can access the verified data on diagnosis, medication, treatment and prognosis for making informed decisions within shorter periods.
Using patient data for personal chronic disease management
The increasing usage of wearable technology that monitors the vital stats and people’s preference for syncing data from their devices to the cloud can facilitate the development of programmes for tailored chronic disease management. Chronic diseases can range from diabetes to heart problems that are becoming more common by the day. Pharma companies can use this data from the patient healthcare records to provide tailored management solutions and healthcare tips to the registered patients regularly.
However, the lack of a dedicated HER system is currently making it extremely challenging for the healthcare professionals and also the pharmaceutical companies to gain access to the patient history, case studies, and healthcare references.
Utilizing unstructured data to accelerate drug discovery and development
The cost of bringing a new drug to the market can reach $5 billion according to an analysis. Fast-tracking drug discovery and development can minimize cost. Combing via unstructured data of patents, clinical trials, and scientific publications efficiently is only possible by applying predictive analysis to the search parameters.