Will Advancements in AI Lead to Job Loss in Biotech?
Pictured: Close-up of a microscope / iStock, Kkolosov
On May 1, IBM paused hiring for 7,800 positions that the company believed could be better performed by artificial intelligence, sending shockwaves through the tech industry.
Many biopharma companies are rapidly adopting artificial intelligence (AI) and machine learning (ML) for a number of applications, from preventative healthcare to drug discovery. But whether the biotechnology industry will suffer similar purges as those in tech is still unknown, said Jeff Morton, a biotechnology patent law attorney and partner at Procopio, Cory, Hargreaves, & Savitch.
“The jury’s still out on how AI will impact things,” he told BioSpace. While data analytics may increasingly become more automated, Morton said that ultimately, companies still need to prove drugs or treatments work for patients. This involves complex, creative research, he added, “and I think that will still rely on humans.”
“Most people I’m talking to on a day-to-day basis in biotech are senior scientists” and executives who will likely enjoy more job security as AI becomes increasingly integrated into biopharma, Morton said. But people in other roles or students who are looking to get a job in the biotechnology field might have a different perspective, he said.
The role of AI in biotechnology is broad and heterogeneous, meaning different sectors might be differently affected, Morton said. AI algorithms could potentially find new targets for existing drugs, speed up drug development, sift through clinical and research data, monitor patients and analyze market trends.
While AI in biotech is nothing new, in recent months generative AI has captured media attention, the most notable example being GPT-4, the engine that runs ChatGPT. Generative AI can use existing data to produce original content. GPT-4 has demonstrated an ability to complete a wide variety of tasks and generate new content, including working code and legal briefs.
A Human Touch
Raj Indupuri, CEO of eClinical Solutions, told BioSpace that he expects generative AI to change many roles in biotech, but he is skeptical that AI will replace humans in clinical research and drug development. Companies need human actors to validate algorithmic outputs, especially in the life sciences, he said.
“You still have to verify the things that AI and ML are predicting,” Indupuri said. “The consequences for getting something wrong are significant.”
In other words, because AI makes mistakes and contains bias, it requires validation and thoughtful implementation. Generative AI is particularly difficult to validate, meaning there will need to be human input at multiple steps in the clinical development process for the foreseeable future, Indupuri said.
AI algorithms learn from existing data, then either classify or generate new data based on what they know. However, “clinical development is extremely complex, with minimal commonalities,” said Indupuri. This means that an algorithm would be hard-pressed to generalize and generate an accurate output from data from past successful trials, especially for rare diseases, where the datasets are small.
Therefore, Indupuri said, companies still need research teams to analyze data and make decisions during each step in the drug development process, from initial drug studies to clinical research.
He added that AI can eliminate “inefficiencies” in drug discovery and data analytics. This may result in job losses, he said, but likely “not to the same extent” as in the tech sector.
The Silver Lining
Indupuri added that AI may also create a number of new roles, or simply change old ones. In addition, some people might report higher job satisfaction, as many manual tasks can be “eliminated or transformed by using AI,” he said.
As artificial intelligence use increases, Indupuri and Morton agreed that upskilling—training existing employees to interface with AI and ML technologies—will be necessary to keep up with labor demands in the future.
“There’s quite a bit of retraining going on already,” Morton said.
Still, both he and Indupuri said they believe that AI will play a large role in the biopharma sphere in years to come.
“It seems to me that there is a general consensus that things are going to change, but it’s hard to predict how,” Morton said.