Nav: Home

Review evaluates how AI could boost the success of clinical trials

July 17, 2019

In a review publishing July 17 in the journal Trends in Pharmacological Sciences, researchers examined how artificial intelligence (AI) could affect drug development in the coming decade.

Big pharma and other drug developers are grappling with a dilemma: the era of blockbuster drugs is coming to an end. At the same time, adding new drugs to their portfolios is slow and expensive. It takes on average 10-15 years and $1.5-2B to get a new drug to market; approximately half of this time and investment is devoted to clinical trials.

Although AI has not yet had a significant impact on clinical trials, AI-based models are helping trial design, AI-based techniques are being used for patient recruitment, and AI-based monitoring systems aim to boost study adherence and decrease dropout rates.

"AI is not a magic bullet and is very much a work in progress, yet it holds much promise for the future of healthcare and drug development," says lead author and computer scientist Stefan Harrer, a researcher at IBM Research-Australia.

As part of the review and based on their research, Harrer and colleagues reported that AI can potentially boost the success rate of clinical trials by:
  • Efficiently measuring biomarkers that reflect the effectiveness of the drug being tested
  • Identifying and characterizing patient subpopulations best suited for specific drugs. Less than a third of all phase II compounds advance to phase III, and one in three phase III trials fail-not because the drug is ineffective or dangerous, but because the trial lacks enough patients or the right kinds of patients.
  • Start-ups, large corporations, regulatory bodies, and governments are all exploring and driving the use of AI for improving clinical trial design, Harrer says. "What we see at this point are predominantly early-stage, proof-of-concept, and feasibility pilot studies demonstrating the high potential of numerous AI techniques for improving the performance of clinical trials," Harrer says.
The authors also identify several areas showing the most real-world promise of AI for patients. For example:
  • AI-enabled systems might allow patients more access to and control over their personal data.
  • Coaching via AI-based apps could occur before and during trials.
  • AI could monitor individual patients' adherence to protocols continuously in real time.
  • AI techniques could help guide patients to trials of which they may not have been aware
  • In particular, Harrer says, the use of AI in precision-medicine approaches, such as applying technology to advance how efficiently and accurately professionals can diagnose, treat and manage neurological diseases, is promising. "AI can have a profound impact on improving patient monitoring before and during neurological trials," he says.
The review also evaluated the potential implications for pharma, which included:
  • Computer vision algorithms that could potentially pinpoint relevant patient populations through a range of inputs from handwritten forms to digital medical imagery.
  • Applications of AI analysis to failed clinical trial data to uncover insights for future trial design.
  • The use of AI capabilities such as Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP) for correlating large and diverse data sets such as electronic health records, medical literature, and trial databases to help pharma improve trial design, patient-trial matching, and recruiting, as well as for monitoring patients during trials.
The authors also identified several important takeaways for researchers:
  • "Health AI" is a growing field connecting medicine, pharma, data science and engineering.
  • The next generation of health-related AI experts will need a broad array of knowledge in analytics, algorithm coding and technology integration.
  • Ongoing work is needed to assess data privacy, security and accessibility, as well as the ethics of applying AI techniques to sensitive medical information.
Because AI methods have only begun to be applied to clinical trials in the past 5 to 8 years, it will most likely be another several years in a typical 10- to 15-year drug-development cycle before AI's impact can be accurately assessed.

In the meantime, rigorous research and development is necessary to ensure the viability of these innovations, Harrer says. "Major further work is necessary before the AI demonstrated in pilot studies can be integrated in clinical trial design," he says. "Any breach of research protocol or premature setting of unreasonable expectations may lead to an undermining of trust-and ultimately the success-of AI in the clinical sector."
This work was supported by IBM Research. All authors declare no conflicts of interest and no disclosures.

Trends in Pharmacological Sciences, Harrer et al.: "Artificial Intelligence for Clinical Trial Design"

Trends in Pharmacological Sciences (@TrendsinPharma), published by Cell Press, is a monthly review journal that contains succinct articles on the most exciting recent developments in pharmacology and toxicology research. Topics covered in the journal range from molecular to behavioral pharmacology, and from current techniques to theoretical pharmacology. Visit: . To receive Cell Press media alerts, please contact

Cell Press

Related Clinical Trials Articles:

Review evaluates how AI could boost the success of clinical trials
In a review publishing July 17, 2019 in the journal Trends in Pharmacological Sciences, researchers examined how artificial intelligence (AI) could affect drug development in the coming decade.
Kidney patients are neglected in clinical trials
The exclusion of patients with kidney diseases from clinical trials remains an unsolved problem that hinders optimal care of these patients.
Clinical trials beginning for possible preeclampsia treatment
For over 20 years, a team of researchers at Lund University has worked on developing a drug against preeclampsia -- a serious disorder which annually affects around 9 million pregnant women worldwide and is one of the main causes of death in both mothers and unborn babies.
Underenrollment in clinical trials: Patients not the problem
The authors of the study published this month in the Journal of Clinical Oncology investigated why many cancer clinical trials fail to enroll enough patients.
When designing clinical trials for huntington's disease, first ask the experts
Progress in understanding the genetic mutation responsible for Huntington's disease (HD) and at least some molecular underpinnings of the disease has resulted in a new era of clinical testing of potential treatments.
New ALS therapy in clinical trials
New research led by Washington University School of Medicine in St.
Telemedicine helps improve participation in clinical trials
Videos and creative uses of other visuals provide a novel way to obtain informed consent during clinical trials to improve participants' understanding and retention of trial information, according to a study by Nemours Children's Health System presented at the American Thoracic Society (ATS) Annual Conference.
Not enough women included in some heart disease clinical trials
Women are underrepresented in clinical trials for heart failure, coronary artery disease and acute coronary syndrome but proportionately or overrepresented in trials for hypertension, atrial fibrillation and pulmonary arterial hypertension, when compared to incidence or prevalence of women within each disease population, according to a study in the Journal of the American College of Cardiology.
BU: Obese patients underrepresented in cancer clinical trials
A new review by Boston University School of Public Health researchers found that less than one-fifth of participants in cancer-related clinical trials are obese.
Are women really under-represented in clinical trials?
Several studies have reported a lack of gender diversity in clinical trials, with trials including mostly adult males; however, a recent review of publicly available registration data of clinical trials at the US Food and Drug Administration for the most frequently prescribed drug classes found no evidence of any systemic significant under-representation of women.
More Clinical Trials News and Clinical Trials Current Events

Trending Science News

Current Coronavirus (COVID-19) News

Top Science Podcasts

We have hand picked the top science podcasts of 2020.
Now Playing: TED Radio Hour

Climate Mindset
In the past few months, human beings have come together to fight a global threat. This hour, TED speakers explore how our response can be the catalyst to fight another global crisis: climate change. Guests include political strategist Tom Rivett-Carnac, diplomat Christiana Figueres, climate justice activist Xiye Bastida, and writer, illustrator, and artist Oliver Jeffers.
Now Playing: Science for the People

#562 Superbug to Bedside
By now we're all good and scared about antibiotic resistance, one of the many things coming to get us all. But there's good news, sort of. News antibiotics are coming out! How do they get tested? What does that kind of a trial look like and how does it happen? Host Bethany Brookeshire talks with Matt McCarthy, author of "Superbugs: The Race to Stop an Epidemic", about the ins and outs of testing a new antibiotic in the hospital.
Now Playing: Radiolab

Speedy Beet
There are few musical moments more well-worn than the first four notes of Beethoven's Fifth Symphony. But in this short, we find out that Beethoven might have made a last-ditch effort to keep his music from ever feeling familiar, to keep pushing his listeners to a kind of psychological limit. Big thanks to our Brooklyn Philharmonic musicians: Deborah Buck and Suzy Perelman on violin, Arash Amini on cello, and Ah Ling Neu on viola. And check out The First Four Notes, Matthew Guerrieri's book on Beethoven's Fifth. Support Radiolab today at