For pharmaceutical and biopharma companies, building quality into your products from an early stage is a key factor in regulatory approval and market success. Design of Experiments (DOE) is an essential tool for achieving both regulatory compliance and faster time to market.
Over the last several years, the use of artificial intelligence (AI) in the pharma and biomedical industry has gone from science fiction to science fact. Increasingly, pharma and biotech companies are adopting more efficient, automated processes that incorporate data-driven decisions and use predictive analytics tools. The next evolution of this approach to advanced data analytics incorporates artificial intelligence and machine learning.
In the midst of a global COVID-19 pandemic, a top priority for many pharma and biopharma companies is to get a vaccine developed, produced and delivered to the public as quickly as possible. Ushering a vaccine through rigorous testing protocols and regulatory approvals is not an easy (or quick) effort, but incorporating advanced data analytics could help accelerate the process. Data analytics has proven effective in speeding vaccine development both by enabling more efficient Design of Experiments (DOE) and by creating rapid-scale production rollout processes.
Digital transformation in biopharma promises to deliver exponential results and make new discoveries and solutions to complex problems a reality, but it requires companies to make big changes to get there—changes in processes as well as adoption of new technologies. For some companies and facilities, this is a bigger leap than for others. Depending on the level of digitalization and integration that currently exists within a company, the process can take from months to years.
Digital transformation in biopharma, like other industries, is accelerating as Pharma 4.0 and Industry 4.0 begin to take shape in companies of all sizes. But knowing that digital transformation is inevitable is one thing, successfully managing the transition process is another. What are the steps biopharma companies should be taking to ensure a smooth digital transformation?
From employing artificial intelligence (AI) to identify drug candidates to using big data to support continuous process manufacturing, the prospects for digital transformation in the biopharma industry are huge. Yet, biopharma and life sciences lag behind many other industries when it comes to digital transformation.