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 How Can Data Management Help the Pharmaceutical Industry?
How Can Data Management Help the Pharmaceutical Industry?

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Pharmaceutical companies generate hundreds of terabytes of data each year, across all stages of R&D.

 

Pharmaceutical and biotechnology companies rely on cross-industry and cross-departmental collaboration to develop new treatments, improve patient care, and increase profits for drug manufacturers. Approximately 80% of this data is unstructured and comes from a variety of sources, many of which use a variety of data processing techniques and devices. The result is a complex and scattered web of unstructured data that leads to inconsistencies in data management, security threats, wasted storage costs, time and resources. Given the vast amounts of data generated every day, it is also difficult to implement new technologies and digitally transform an organisation. Cloud computing is one of those in-demand technologies that can help organisations save money by moving data from file to object storage. Did you know that 83% of pharmaceutical companies are already using the cloud to improve collaboration? However, it's important to know that cloud adoption can easily fail if data is not effectively analysed, secured, managed and migrated to the cloud.

 

In short, pharmaceutical data management is not just about organising clinical data, but also consolidating, analysing and optimising it, especially as companies look for ways to reduce data storage costs and move to object storage by leveraging the cloud.

The most difficult step, however, is making sense of vast amounts of unstructured data - What and where exactly is the data? Who has access to it? Is it secure and legal? How can it be improved?

 

Here are some examples of how data can assist the pharmaceutical industry in weathering the storm:

 

Concentrate on accelerating growth: One way to look at the growth of the pharmaceutical industry is the frequency with which patients fill and refill their prescriptions. Pharmaceutical drugs, vaccines and medical treatments have been in high demand in recent years due to economic disruptions such as the Covid 19 pandemic. Did you know that it takes over ten years and $2.6 billion to develop a single drug for the market? The cost of bringing a new drug to market is rising, and as patents for blockbuster drugs expire, the pharmaceutical industry is trying to speed up the process. By analysing vast datasets of scientific publications, academic research papers, and control group data, companies can use data analytics to accelerate new drug discovery. The vast amounts of data can then be analysed using predictive algorithms. To improve financial performance, innovation in drug discovery is essential.

 

Effectiveness of clinical trials: Conducting clinical trials is a time-consuming and costly process, so pharmaceutical companies want to make sure they have the right mix of patients. In addition, it is often difficult to find patients willing to participate in the trials. Each year, they spend more than a billion dollars conducting clinical trials for new drugs, but data analytics can help reduce these costs significantly. Data analytics identifies and analyzes various data points, including demographic and historical data, remote patient monitoring information, and data from previous clinical trials. This allows them to streamline the entire process and find trial sites with the most patients to speed disease diagnosis, create control groups, and conduct clinical trials more efficiently.

 

Ensuring data security - Pharmaceutical companies generate and store enormous amounts of business-critical data and PHI. If this data falls into the wrong hands, it can lead to business disruption, breach of trust, penalties, and reputational damage. It is a major challenge to identify, structure and secure all this unstructured data. One bright spot is that there are a few unified data management platforms in the market that are able to isolate data containing personal or company-sensitive information in secure storage and reduce exposure and risk. They not only monitor data usage, but also track access to specific files to identify potential misuse and mitigate risks before they occur. Pharmaceutical companies cannot afford penalties or other cost increases in the current economic environment. A robust security system is therefore essential.

 

Ensuring compliance: Compliance regulations are constantly changing and becoming more stringent. Failure to comply with them can lead to civil and criminal actions that can damage a company's reputation and result in large fines. To support the strictest definition of data privacy, data management and analytics can help identify fields associated with regulatory requirements. This discovery helps identify a data set with the highest likelihood of meeting that definition. In addition, immutable logs can show auditors the processes used to identify risks and the steps taken by and for the organisation to address them. As mentioned earlier, a penalty would reduce the overall cost structure and cause significant damage - an absolute no-go given the impending economic downturn.

 

 





 


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