Leveraging AI in clinical trials critical to the advancement of pharmaceuticals
COVID-19 has radically altered the clinical trial landscape in Australia.
Prior to the pandemic, there was significant potential to roll out a significant number of projects at one time. In fact, in 2019 there were over 1800 ongoing trials taking place within Australia.1 Public attitude regarding willingness to participate in clinical trials comes down to Australia’s sophisticated healthcare system and the skilled workers in the country.
Australia’s investigators and clinical trial networks are among the best in the world.2 In fact, four emerging opportunities have been identified by these networks for Australia, which include digital health; specifically, increasing the adoption of digital health and artificial intelligence (AI) in clinical trials.
However, there are challenges that need to be overcome to make scientific and medical research in Australia more efficient. One way that researchers can overcome these hurdles is by increasing the uptake of technology such as AI. This is especially critical now as sponsors and medical researchers find ways to continue with trial studies during COVID-19 while still adhering to strict regulations and patient privacy laws.
Where the hurdles lie ahead
In addition to the challenges that clinical trials face, there is also a long journey before they can be considered a success. Researchers must ensure that all regulations are followed, and that patient privacy is met throughout the entire process. Another challenge that researchers face when trying to put a vaccine or treatment through clinical trials is getting enough study participants in the trial to ensure it’s safe and effective.
With each trial conducted, strict parameters are put in place to ensure the voluntary participants in the research won’t lead to data getting thrown out. To ensure this, each participant is thoroughly screened, and a decision is made on whether they are the correct match for a specific trial. This very time-intensive process of trying to manually match people to what clinical trial is best for them can lead to the extension of timelines for research and trials.
In a recent survey of clinical trial sites, respondents identified patient recruitment and enrolment as their top two concerns.3 Patient recruitment has also been called the “biggest challenge” in clinical trials.4 In fact, an MIT study on clinical trial success rates found that the overall probability of success for all drugs and vaccines is 13.8%.5 On top of that, a worrying trend that researchers are seeing is, when factoring in the challenges brought on by COVID-19 through lockdowns and social distancing, Australia saw a decline in clinical trial participation.
How AI can expedite clinical trials
Traditionally when people think about the use of AI in clinical trials, they usually imagine data analytics after data is already collected. However, where AI can really add value to clinical trials is in the pre-trial phase. Trials leveraging AI technology and big data in the planning phases can optimise trial design and help researchers identify target patient populations, allowing for more efficient matching of trials to patients.
An example of where this could have been used was only recently shown in China during the trials for effective COVID-19 vaccines. Researchers started a clinical trial but realised midway through the patient recruitment process that incidence rates were lower than expected. The trial had to be cancelled due to shortage of patients.6 Rising costs, evolving standards of care, and decreased participant recruitment and retention all mean that making the right decisions earlier is more important than ever. Identifying optimal countries and sites with the help of AI and big data can help in balancing speed, cost and quality.
Utilising Integrated Evidence like Acorn AI can give clinical development leaders and their trials the best chance at success; from a better designed trial, to a more robust control arm, to stronger positioning of a drug for commercialisation — the rich context and evidence required in a rapidly evolving clinical development landscape.
Technology is the key to unlocking cures
Even as the world begins to come out of lockdowns from COVID-19, more research will need to be done to evolve the vaccine. As the Australian Government puts more financial support towards clinical trials and research through tax relief incentives, it is important that the small, medium and large vaccine researchers continue to invest in technology to further enhance medical trials in Australia.
Technology, and specifically AI, will be critical as we speed up and make clinical trials more streamlined and effective.
- Oliver, P. (2021, May 14). Clinical Trial Sites Share Frontline Insights into COVID-19 Impact. Medidata Solutions. https://www.medidata.com/en/life-science-resources/medidata-blog/clinical-trial-sites-share-frontline-insights-into-covid-19-impact
- Rutter, K. (2018, October 9). Why patient recruitment is the biggest challenge in clinical trials – INDUSTRY VOICES. Informa Connect. https://informaconnect.com/patient-recruitment-challenge-clinical-trials-industry-voices/
- Wong, C. H., Siah, K. W., & Lo, A. W. (2018). Estimation of clinical trial success rates and related parameters. Biostatistics, 20(2), 273–286. https://doi.org/10.1093/biostatistics/kxx069
- Zhuang, P. (2020, April 17). China cancels coronavirus clinical trials due to shortage of patients. South China Morning Post. https://www.scmp.com/news/china/society/article/3080453/china-cancels-coronavirus-clinical-trials-due-shortage-patients
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