The Pharmaceuticals industry is critical in today’s world. Ever since the Covid-19 pandemic, the industry has expanded into one of the most developed sectors and continues to gain importance. It is continuously working on creating and using newer technologies for drug trials to ensure that the treatments are safe and effective for patients and in line with evolving market demands.
Pharmaceutical and biotech companies are not significantly impacted by economic shocks and recessions. For instance, as a share of GDP, US national healthcare expenditures grew in past recessions, such as those in the early 90s and early 2000s, as well as the global financial crisis of 2007-09. Take the COVID-19 pandemic for instance. Much like every industry worldwide, it presented some significant challenges for drug developers too, particularly in maintaining clinical research continuity, however, their resilience and agility were unmatched. Their rapid response helped lessen the impact of the pandemic and aid the world with lifesaving drugs. There is a good chance that this resilience will continue through the coming economic crisis as well simply because a bad economy won’t stop patients from taking their medicine.
How can data management help the pharmaceutical industry during a looming recession?
Every year, throughout all R&D phases, pharmaceutical companies amass hundreds of terabytes of data. Pharmaceutical and biotech firms rely on inter-industry and interdepartmental cooperation to create new treatments, improve patient care, and boost profits for drug manufacturers. 80% of this data is unstructured and comes from various sources, many of which employ different data handling techniques and equipment. The result is a complicated and distributed web of unstructured data leading to data management discrepancies, security threats, wasted storage costs, time, and resources. Also, when it comes to implementing new technology and transforming an enterprise digitally, it is difficult given the massive amounts of data generated every day. Cloud computing is one such technology that is in high demand and can help enterprises incur significant cost savings by moving data from file to object storage. Did you know 83% of pharmaceutical companies already use the cloud to strengthen their collaborations? However, cloud adoption can get easily derailed if data is not analyzed, secured, governed, and migrated effectively.
In a nutshell, pharmaceutical data management goes beyond simply organizing clinical data; it also includes consolidating and analyzing, and optimizing it, especially when enterprises are exploring ways to reduce data storage costs and move to object storage by utilizing the cloud.
However, the most difficult step is making sense of the massive amounts of unstructured data – What and where is the data? Who has access? Is it secured and compliant? How can it be optimized?
Here are some of the ways that data can help the pharmaceutical industry weather the storm:
- Focus on driving growth: One way to look at the pharma industry’s development is to consider that patients are constantly filling and refilling their prescriptions. In recent years, economic disrupters like the Covid-19 pandemic only accelerated the demand for pharmaceutical drugs, vaccines, and medical treatments. Did you know that developing a single drug for the market takes over ten years and 2.6 billion? Introducing a new drug into the market is becoming increasingly expensive, and with patents for blockbuster drugs expiring, the pharmaceutical industry is attempting to speed this process up. Companies can use data analytics to accelerate the discovery of drugs by analyzing vast datasets of scientific publications, academic research papers, and control group data. These enormous amounts of data can then be analyzed using predictive algorithms. It is important to remember that improvements in financial performance will only be driven by innovation in drug discovery.
- Efficacy of Clinical Trials: Pharmaceutical companies want to ensure they have the right mix of patients for clinical trials because it is a costly and time-consuming practice. Furthermore, it is often difficult to find patients who are willing to participate in trials. It costs them more than a billion dollars each year to conduct clinical trials for new drugs, but data analytics can help reduce these costs significantly. Data analytics helps identify and analyze various data points: demographic and historical data of participants, remote patient monitoring information, and data from previous clinical trials. This will help them optimize the entire process and identify test sites that will have a large number of patients to speed up disease diagnosis, design control groups, and run clinical trials more efficiently.
- Ensuring robust data security: The pharmaceutical industry generates and stores vast amounts of business-sensitive and PHI data. This data in the wrong hands can result in operational disruptions, breach of trust, penalties, and reputational damage. The challenge is most of this data is unstructured and difficult to identify, structure, and secure. The silver lining however is that there are several unified data management platforms in the market that can reduce exposure and risk of rogue data usage by isolating data that has personal or business-sensitive information into secure storage with limited access. Additionally, they keep track of data usage in general and monitor accesses to particular files, in order to identify potential misuse and proactively mitigate risk with data security remediations. In the current scenario, the pharmaceutical industry cannot afford a penalty or any other cost escalation. Robust security is the key.
- Streamlining compliance: Compliance regulations are constantly changing and becoming more stringent. Failing to adhere to them can lead to civil and criminal lawsuits that can harm a company’s reputation and result in high payouts. Data management and analytics can help identify fields associated with regulatory requirements to support the strictest definition of data privacy. This discovery helps identify a data set with the highest probability of adherence to that definition. Additionally, immutable logs can demonstrate to auditors the processes that identify risks and the steps taken to remediate by and for the business. As mentioned above, a penalty will dwindle the overall cost structure and create significant havoc – an absolute no-no given the impending economic downturn.
How can Data Dynamics empower the pharmaceuticals sector to be recession-proof with intelligent data and storage lifecycle management?
With Data Dynamics’ scalable, unified unstructured data management platform, data is streamlined and secured, data classification is effective, and safeguarded with absolute compliance and efficiency. The platform encompasses four modules – Data Analytics, Mobility, Security, and Compliance. Each module has been customized to meet the industry’s needs and is helping pharmaceutical companies modernize their data management ecosystems efficiently and effectively.
With Data Dynamics, organizations can eliminate the use of individual point solutions with siloed data views. Instead, they can utilize a single software platform to structure their unstructured data, unlock data-driven insights, secure data, ensure compliance and governance and drive cloud data management.
Following are our five most significant differentiators that help leading organizations thrive in an increasingly volatile environment:
- A platform approach to data management vs. competitors with ‘single value’ tools
- Multipetabyte and multi-location enterprise scalability
- Insights into enterprise data to enable informed decisions – What and where is the data? Who has access? Is it secured and compliant?
- Intelligent, compliant, and secured data migrations
- A customized deployment based on the unique requirements of each client
- In-year ROI on software investment
Ultimately, the company’s vision is to help enterprises achieve data democratization so that users, no matter their technical background, can instantly access, understand, and derive maximum insights from unstructured data sprawls.
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