AI in Pharma and Biomedicine – Analysis of the Top 5 Global Drug Companies


The applications of AI in pharma are building momentum, but we wanted to look beyond the hype and find the underlying trends that matter in business.

A TechEmergence study on healthcare industry executives currently using AI revealed that over 50 percent anticipate broad scale AI adoption by 2025 and nearly half of participants expect that initial AI applications will target “chronic conditions.” With an estimated 50 percent of Americans suffering from at least one chronic condition, the pharmaceutical segment of the healthcare industry is poised to be impacted by the expected trend of AI adoption.

It seems that no sources have taken a comprehensive look at artificial intelligence applications at the top pharmaceutical and biotechnology companies – and that’s exactly what we set out to do with this article.

In this article we aim to answer questions that business leaders are asking today:

  • What types of machine learning applications are currently in use and in development at the top pharmaceutical and biotechnology companies, such as Johnson & Johnson and Pfizer?
  • Are there any common trends among their innovation efforts – and how could these trends affect the future of the pharmaceutical drug industry?
  • How much has been invested in machine learning and emerging tech innovation across leading pharmaceutical companies?

This article aims to present a comprehensive look at the implementation of machine learning by the five leading pharmaceutical and biotechnology companies ranked by total 2016 revenue.

Through facts and figures we aim to provide pertinent insights for business leaders and professionals interested in how these top five pharmaceutical and biotechnology companies are being impacted by AI.

Before presenting the applications at each of the top five companies, we’ll take a look at some common themes that emerged from our research in this sector.

AI in Pharma – Insights and Facts Up Front

Some of you will be eager to read this entire article and dive into individual use-cases, others are just looking for a handful of trends to consider. In this short “insights up front” section, we’ll dive into the general trends that we found at a high level. Readers with a deeper interest can read beyond this section into the individual use-cases from the top 5 drug companies.

In 2016, total U.S. prescription drug expenditures were estimated at $450 billion. The most recent data from the CDC provides context with a reported 48.9 percent of individuals in the U.S. taking at least one prescription drug within the last 30 days.

Bringing a new pharmaceutical drug to market takes about 12 years and can reach upwards of $1 billion in R&D expenditures, industry leaders are now seeking more efficient methods of approaching this process and machine learning is emerging as a potential solution.

The current machine learning initiatives of the top five pharmaceutical and biotechnology companies, reveal trends in the following areas:

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