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Rush shares his thoughts on how advanced analytics are making their mark on the pharma industry.
Pharm Exec: Why is the industry relying more and more on new, advanced technology to develop drugs?
Rush: One of the most exciting features of our industry is that science is always driving us forward to use new and better technologies in every facet of our business. The rapid pace of change in data analytics just highlights this bedrock principle.
Developing and manufacturing drugs is a challenging and risky endeavor that demands the best tools we have in the arsenal. It’s hard work involving strict protocols and documented evidence. This evidence, or data, not only informs regulators, but it’s also the backbone upon which consumer trust in the safety and efficacy of drug products is built.
Developing a new medicine also takes a long time and is enormously expensive. Drug makers find themselves driven ethically and practically to minimize those costs and bring more life-saving medicines to more people across the globe.
To enable these goals—safety and efficacy with accessibility and affordability—both governments and industry have pointed to smarter use of advanced data analytics to generate faster and better insights.
Pharm Exec: How can advanced analytics shed light on the safety, purity, and efficacy of drug products to help protect public health?
Rush: Our ability to create data relevant to the safety, purity, and efficacy of drug products is increasing, plus many of our drug products are becoming more sophisticated—for example, cell and gene therapies. Innovation in analytical instruments is making a huge difference by creating new data that informs every decision at every stage of drug discovery and development. However, understanding all we want to know about this data is hard.
As skilled as chemists, biologists, and pharmacologists are at generating insights, we are all human and limited in our capacity to absorb and discern meaning from this avalanche of data. Advanced analytics techniques like machine learning and artificial intelligence can rise to this challenge and interrogate reams of data to see things we can’t, leading scientists to insights we might otherwise miss.
Pharm Exec: What are some of the challenges using advanced analytics?
Rush: One big challenge is that sometimes we need to aggregate and make sense of terabytes of data collected by many scientists and engineers across numerous institutions and companies. For advanced analytics to work optimally, the silos of data need to be broken down and the data must be allowed to flow freely.
Another more abstract challenge is that consumers and regulators need assurance that the advanced analytics have been used in a way that produces data interpretation and insights that are just as trustworthy as those of expert scientists. While this calls for a new way of thinking about the meaning of the term “validated,” most regulators are coming around to see this as a path to getting higher quality safety and efficacy evidence in submissions from pharmaceutical companies.
Pharm Exec: What lessons could pharma learn from the use of advanced analytics in other industries?
Rush: The explosion of digital has provided lessons nearly everywhere, but especially perhaps in consumer industries that are less conservative and regulated than pharma. Particularly in commercial pharma, we are starting to learn how they activate customers with omnichannel approaches enabled by advanced analytics.
Another example is the airline industry, where systems that collect real-time in-flight metrics are used to plan flights and reduce overall fuel consumption, which accounts for 10% to 12% of airline operating expenses. They are monitoring aircraft to predict maintenance issues and shift routes to deliver planes to service centers for maintenance without disruption to flight schedules. Pharma companies will be increasingly able to apply advanced data analytics in similar ways to realize operational benefits.
Pharm Exec: How do you see the use of advanced analytics changing in pharma over the next few years?
Rush: All parts of pharma will be impacted by the increasing use of advanced data analytics over the next few years, with big users including commercial analytics, real-world evidence, and instrument-heavy R&D and manufacturing groups. The drivers for innovation in advanced analytics are clear: to deliver less expensive drug products faster and ensure that time, money, and scientific expertise is spent on molecules with the best chance of success.
We should also expect to see increasing trust from both regulators and consumers in new advanced data analytics approaches for making rapid, data-rich, risk-based decisions. The recent pandemic may also have underscored the ability of the pharma industry to change quickly in collaboration with regulators. If this collaborative spirit holds, we could see rapid progress in using advanced data analytics to help deliver safer, more efficacious drugs to more patients at lower cost than ever before.