It's time to use machine learning and AI to improve commercial strategies

Pharma’s new possibilities with machine learning and artificial intelligence

By Leilani C. Latimer
VP of global marketing, partnerships, and commercial operations
Zephyr Health

An excerpt from the PharmaVOICE article “Artificial Intelligence and Machine Learning

The field of artificial intelligence (AI) research was founded at Dartmouth College during the summer of 1956. Fast-forward more than 60 years to the year 2018 and we are seeing expansive growth in the development of AI, referred to in the business as the “Summer of AI.”

Right now there are exciting and tangible opportunities for commercial teams (brand leaders, marketers, sales) in pharma to leverage machine learning and AI to improve everything in their go-to-market strategies, from product launch to product value proposition, to customer engagement.

As pharma evolves from being product-centric to being market- and patient-centric, it needs to map a more targeted sales strategy for relevant stakeholders to improve sales while delivering value to end patients. To do this, and to ensure commercial viability, companies must be able to aggregate, process, and interpret high volumes of diverse, unstructured, and difficult-to-integrate data sources — something that is no longer possible with manual systems.

With machine learning solutions, companies can access and activate large amounts of data, constantly improving their ability to target the right customers, via the right channels. Using data intelligently to power go-to-market strategies has to be a priority if commercial teams want to stay ahead of the competition and increase both their reach and their precision.

Interoperability remains one of the industry’s biggest challenges to adopting AI. There are numerous solutions for different needs, but often there is no single person or group tasked with looking across the commercial enterprise to determine how to bring these unique and valuable offerings together. For Life Sciences companies to successfully adopt AI solutions, they need a supporting change management framework that incorporates strategy, culture, people, and process along with the technology itself.

To read the full article on PharmaVOICE, click here.