AI in the Life Sciences – What’s all the Hype?


Robert RuthAIBy Robert Ruth, Vice President & Managing Director, Ashton Tweed

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The advancement and implementation of artificial intelligence (AI) has been a hot topic for years, but some eye-catching studies have recently been grabbing the attention of the life sciences industry. Early this year, Google’s DeepMind team published that its AI can outperform doctors in spotting breast cancer and, therefore, that it can provide an independent, automated, and immediate second opinion (FierceBiotech). But what does this mean in the big picture? First, let’s look at the full potential of AI in our industry.


Due to its speed, accuracy, and predictive qualities, AI can be utilized in several incredible ways that provide quick, quality work while cutting costs and producing less failures. GEN reported six applications that will be most meaningful in the near term:


  1. Diagnosis and Disease Identification
  2. Personalized Medicine
  3. Drug Discovery and Manufacture
  4. Clinical Trials
  5. Radiotherapy and Radiology
  6. Electronic Health Records


Despite the overwhelming positive impact that this revolution could have on the complex process of bringing therapeutics and diagnostics to market, notably during initial drug discovery, there are some reservations. Namely, the challenge of keeping patient data secure. However, as IT professionals make progress in protecting our information, other concerns about what this means for the life sciences work force have been voiced. If Google’s DeepMind can outperform doctors, who’s to say that one day it will stop providing second opinions and start providing initial diagnoses or recommendations to patients? Will machine learning replace human jobs while companies opt to hire software engineers and data experts in their place?


Forbes delved into this topic last year, comparing drastically different predictions from top sources – some which project apocalyptic job loss while others anticipate milder numbers. However, Forbes ends on a positive note, citing:


“A December 2018 Dun & Bradstreet survey of AI World Conference and Expo attendees found that 40% percent of respondents’ organizations are adding more jobs as a result of deploying AI within their business and only 8% are cutting jobs due to AI implementation.

Mining data from more than 50 million job postings, ZipRecruiter found that AI created three times as many jobs as it destroyed in 2018. The fastest growing jobs AI has created from 2017 to 2018 include Senior Data Scientist with an annual growth of 340% (resulting in average salaries of $257,000 according to Burtch Works), Mobile Application Developer (186%) and SEO Specialist (180%). AI is creating “a surge in new career opportunities,” says the ZipRecruiter report.”


So, perhaps industry leaders should be more concerned with hiring than firing. Naturally, this is a high growth area for Big Pharmas looking to expand into this space and for start-ups launching new technology platforms. But it also presents an opportunity for current professionals to build new capabilities upon their existing backgrounds. A 2018 Life Science Workforce Trends Report (CSBI) asked life science executives across the country which key developments were driving their talent needs, and “rapid technology and business innovation” was one of the top five trends that dominated their discussion. As one of their top three areas of growth, interviewees identified growing needs for technical expertise in IT functional areas, including “data analytics, bioinformatics, 3D printing, IT security, data quality/integrity, artificial intelligence.” The report quotes, “Changes will require dramatically different skill sets over time… In 10–15 years we will see a lot less wet lab research and see it replaced by much more computer modeling and in silico chemical design for drug research.”


It’s clear that AI can provide solutions for everything from discovery to approval and even to commercialization, and the rise of Chief Data and Digital Officers in the industry proves that companies intend to find broader and more innovative ways to apply this powerful tool. What has been your experience so far as this exciting trend unfolds? What challenges do you foresee ahead? Share your thoughts in the comments below!


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