The US pharmaceutical industry is valued at $602.19 billion (as of 2023) and only continues to grow. The breadth of the pharmaceutical industry comes with a heightened responsibility to deliver safe, effective medications to millions of people. This is not an issue that can be left up to chance—and with the advance of data analytics for pharma, it no longer has to be.
From optimizing internal operations, reducing inefficiencies in clinical processes, and driving innovation through predictive analytics, pharma analytics is continually contributing to the betterment of the industry as a whole.
What is Pharma Analytics?
Pharma analytics is the use of data analytics to make improvements, increase positive clinical trial outcomes, and accelerate production.
Pharmaceutical companies have long held vast amounts of data—from clinical trials, patient health records, and market insights. So, how can they properly leverage their data? Pharma analytics enables machine learning to forecast outcomes and respond more quickly to demand. The end result is an increased ability to enable both business optimization and patient outcomes.
Pharma Analytics in Research & Development
Pharma analytics is also useful for innovation before medications reach the market. From identifying potential drug candidates faster to optimizing trial design, pharma data analytics is reducing costs while increasing the chances of success.
Optimizing the Pharmaceutical Supply Chain
Disruptions to today’s supply chains are often swift, delaying life-saving treatments from reaching patients in need. Predictive analytics in the pharmaceutical industry, however, enables companies to anticipate possible supply chain risks, ideally resulting in better planning and supply-loss prevention.
Enhancing Salesforce Efficiency
CRM platforms and pharmaceuticals don’t go hand-in-hand at first glance, but this connection is actually highly important for pharma data analytics.
A platform like Salesforce allows companies to employ data governance protocols, track provider engagement, segment customers, and identify future opportunities. Salesforce creates data visibility, which in turn enables pharmaceutical companies to make better informed, holistic decisions for their company at large.
Improving Clinical Trial Recruitment & Success
Clinical trials are crucial for advancing the development of critical treatments and medicine, but they are also complex, expensive, and often struggle to recruit eligible patients.
Pharma analytics enables companies to identify suitable and willing patients more quickly, which leads to a smoother and more efficient process for everyone involved.
As predictive analytics continues to grow, a few areas making rapid advances are:
Drug discovery and development
Machine learning models aid early and often in the drug research and development cycle, reducing the time spent on trial and error testing.
Market forecasting and risk management
Great visibility into market trends and patient needs is allowing companies to anticipate demand and manage drug-lifecycle predictions. While this is advantageous from a go-to-market strategy perspective, it is also advantageous for patients. A better market system will make it easier for patients to consistently and quickly access the medications they need.
Risk Management
Predictive analytics can help companies proactively identify and address compliance and data governance risks, supply chain vulnerabilities, and potential room for improvement in trials.
While the benefits of pharma analytics are numerous, challenges do exist. Maintaining patient data security and confidentiality is paramount, and becomes increasingly difficult when multiple parties are using information for analytics. Practices like maintaining ethical standards and focusing on well-trained AI models are just as (if not more) important than enjoying the benefits listed above.
Your pharma analytics program will only be as strong as your healthcare data foundation. Data governance is not just a nice-to-have in healthcare—it is a full necessity. From HIPPA to FDA guidelines, ensuring accurate and secure data at all times will make every step in pharma analytics smoother and more trustworthy.
Once your organization has laid a robust data governance and compliance foundation, it is time to develop a strong pharma analytics strategy. This strategy will depend largely on the size and specific goals of your organization, but every good analytics strategy will include:
Pharma analytics is not a trend—it is a crucial element and driver of current outcomes in the healthcare industry. Embracing data science and predictive analytics enables pharmaceutical companies to improve their operations, increase clinical trial success, and ensure regulatory compliance.
Kenway Consulting’s team of data governance, data analysis, and Salesforce experts is well-versed in the healthcare industry. Contact us today if your organization is ready to explore all that pharma analytics has to offer.
What is pharma analytics?
Pharma analytics refers to the use of data analysis and generative tools to predict and inform pharmaceutical professionals on future market trends and possible patient outcomes.
What role does data science play in the pharmaceutical industry?
Data science opens up deeper insights from complex data so that pharma professionals can make faster, more informed decisions.
What are the benefits of big data analytics in pharmaceutical research?
Benefits include faster drug development, clinical trial success, and more robust data governance frameworks.
How do pharmaceutical companies ensure data security and compliance in analytics?
Adherence to regulations like HIPPA safeguards pharmaceutical companies from governance breaches. Additionally, developing a company-specific governance framework greatly aids teams in their ability to easily follow governance best practices and ensure regulatory compliance.