The company includes the technology in drug development, improving efficiency, and other areas.
Over the past few years, AI has become one of the most discussed technologies. The algorithm and machine-learning software makes it possible for data to be sorted, analyzed, and arranged on much fast timelines than previously thought possible. For the pharmaceutical industry, this has made the technology very valuable, due to the high amount of varied pieces of data that the industry relies upon.
Johnson & Johnson recently published a blog post detailing six of the ways that it incorporates AI into its various processes.
Jim Swanson, executive vice president and chief information officer at Johnson & Johnson, said in the post, “In the next few years AI is going to play an even bigger role. The technology is currently being used to help our employees detect disease at earlier stages, accelerate drug discovery, assist with clinical trial recruitment, map a patient’s anatomy before a procedure and help surgeons predict the best tool for surgery.”
The six ways listed in the press release are:
In the post, Shan Jegatheeswaran, global vice president of medtech digital at Johnson & Johnson, said, “Surgeons are a lot like high-performance athletes. New and learning surgeons want to see how they performed and learn from their performances and how others performed. But it’s a lot of work to sit and watch hours of footage from the full procedure and cut it down to clips.”
He continued, “Once you get enough of these enriched surgical videos, there is potential to explore algorithms on the behaviors, tactics and movements that could in the future provide further information to care teams.”
Chris Moy, scientific director of oncology, data science, and digital health, R&D, at Johnson & Johnson Innovative Medicine added, “Drug discovery is an extremely challenging process with only a small percentage of lead compounds moving into clinical trials and an even smaller percentage becoming approved medicines. By applying AI, we can advance the most promising drug candidates into clinical development, with the goal of improving the probability of successfully bringing a drug to market and rapidly getting new treatments to the patients who need them the most.”
“Historically, many clinical trials have largely taken place at major academic medical centers, but we know that not all patients have access to these centers,” added Nicole Turner, senior director of global development, data science & digital health, R&D, Johnson & Johnson Innovative Medicine. “Our goal is to leverage the power of AI to bring trials to more patients, rather than waiting for patients to come to us.”
In the same post, Johnson & Johnson Services director of supply chain digital and data science and operations research Vishal Varma said, “It’s our responsibility to make sure patients and customers have reliable access to the transformational therapies our company creates. AI is helping us build a stable, efficient, and resilient supply chain so we can deliver on that obligation.”
Key Findings of the NIAGARA and HIMALAYA Trials
November 8th 2024In this episode of the Pharmaceutical Executive podcast, Shubh Goel, head of immuno-oncology, gastrointestinal tumors, US oncology business unit, AstraZeneca, discusses the findings of the NIAGARA trial in bladder cancer and the significance of the five-year overall survival data from the HIMALAYA trial, particularly the long-term efficacy of the STRIDE regimen for unresectable liver cancer.
Fake Weight Loss Drugs: Growing Threat to Consumer Health
October 25th 2024In this episode of the Pharmaceutical Executive podcast, UpScriptHealth's Peter Ax, Founder and CEO, and George Jones, Chief Operations Officer, discuss the issue of counterfeit weight loss drugs, the potential health risks associated with them, increasing access to legitimate weight loss medications and more.
AbbVie’s Emraclidine Fails to Reduce Schizophrenia Symptoms Compared to Placebo
November 11th 2024Results from the Phase II EMPOWER trial found that emraclidine failed to meet its primary endpoint of reducing Positive and Negative Syndrome Scale scores after six weeks of treatment for schizophrenia.