We previously discussed the role of artificial intelligence within the drug discovery and clinical trial process. Let’s break down how AI plays a role in commercialization and the different ways AI can be implemented into the marketing processes to effectively and quickly get new products to market. In a white paper written by Pratap Khedkar and Saby Mitra, AI is attributed to boosting pharmaceutical sales through customer affinity prediction, customer journey design, next best actions and suggestions, patient switch propensity and adherence, KOL mapping and influence networks.

AI in Marketing

Customer affinity prediction uses AI by collecting data from individuals to predict whether they would be interested in a product.  They target them with advertisements through a multitude of channels with a prediction accuracy rate as high as 85%. Customer journey design takes affinity prediction a step further and helps marketing organizations employ complex customer centric campaigns that can increase sales by up to 2%. While this percent increase may seem small, it can translate into millions of dollars in revenue. Next best actions and suggestions work in real time and suggest options to further market a product particularly to a very important category of customers and healthcare professionals. By targeting the individuals who prescribe and sell drugs, a larger population of patients can be reached. Patient switch propensity and adherence is estimated to add up to $100 million in sales.  This is done by understanding the relationship between diagnoses, treatments, procedures and prescriptions and making predictions about new diagnoses and patients switching to competitor’s products.

Change in Sales

It is crucial to recognize that while AI has helped rapidly change the industry, there are changes that need to be made in order to continue to maximize sale’s potential. ZS’s AccessMonitor survey reports the US pharmaceutical salesforce has decreased by about 25% over the last 10 years and sales reps’ interactions with physicians has decreased about 34%. This change in the sales landscape can be attributed to the increase in AI and further stresses the fact that even while implementing AI, human cognitive intelligence is still absolutely vital in areas such as creativity, problem solving and reasoning. To combat this decline, pharmaceutical companies must prioritize building an AI-enabled organization by helping their employees implement AI into their activities while also acknowledging the drawbacks. Some companies have even created new roles like Chief Data Officer to help implement AI technologies. Training employees of all levels how to extrapolate and interpret the data that comes from the AI algorithms will increase sales while continuing to utilize human intelligence. AI technologies can perform some tasks that previously employees had to but can never replace the employees who are the heart of an organization.

In conclusion, the push for AI has the potential to positively influence the discovery process, clinical development and the commercialization phase of the drug discovery process. Pharmaceutical companies can cut costs, decrease discovery timelines and increase the number of patients reached with the help of AI when used ethically. For more information please visit the PharmaOut blog.

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