The Saudi Food and Drug Authority reviewed the potential of employing artificial intelligence and in silico clinical trials to accelerate drug development and support regulatory decisions during an international summit in Seoul, while emphasizing the importance of rigorous scientific validation before adopting predictive models.
Saudi Food and Drug Authority participation in the Seoul regulatory summit
The concept of in silico clinical trials and the limits of statistical prediction
Rare disease challenges and validation requirements for biological models
The distinction between research opportunities and official regulatory approval
Shared international standards and upcoming regulatory steps
Frequently asked questions
Saudi Food and Drug Authority participation in the Seoul regulatory summit
Dr. Hisham bin Saad Aljadhey, CEO of the Saudi Food and Drug Authority (SFDA), discussed artificial intelligence and computer simulation applications during the International Coalition of Medicines Regulatory Authorities (ICMRA) summit hosted in the South Korean capital, Seoul. According to a report published by the Saudi Press Agency on November 6, 2026, his presentation addressed the concept of “in silico clinical trials” and how computer-based evidence can complement and support established scientific methodologies for drug evaluation, particularly in cases where gathering clinical evidence through traditional methods is difficult.
The official Saudi Press Agency page confirmed the report’s publication date as November 6, 2026, though it did not display the exact original publication time in a directly verifiable manner.
The concept of in silico clinical trials and the limits of statistical prediction
In silico clinical trials, scientifically known as digital laboratory simulations, rely on computer simulations to model specific aspects of biological or clinical processes within the human body. Depending on the nature of the medical application, these simulations can explore how a specific drug interacts with a biological system, predict potential therapeutic responses, or help design a more efficient clinical study.
Although artificial intelligence methods can provide significant assistance in discovering complex patterns or building mathematical models, achieving a statistically convincing prediction does not automatically prove a drug’s safety or its actual therapeutic efficacy in real patients, as real-world clinical trials remain an essential standard in medical evaluation.
Rare disease challenges and validation requirements for biological models
Clinical evidence requires precise scientific interpretation that accounts for the nature of the disease, the type of treatment, the volume of available data, and sources of scientific uncertainty. Rare diseases pose a specific and complex challenge for regulators and researchers alike, given that small patient populations limit the feasibility of conducting large-scale traditional clinical trial designs.
In such cases, computer simulation may provide highly useful supplementary information; however, its regulatory role remains contingent upon verification and validation processes, and the extent to which its software assumptions reflect the reality of actual patients. Any simulation model can generate misleading confidence if important and influential biological factors are absent.
The distinction between research opportunities and official regulatory approval
Dr. Hisham Aljadhey reviewed the promising potential of artificial intelligence and computational methods in accelerating the pace of drug development and supporting sound regulatory decision-making. These statements fall within the framework of exploring available research and regulatory opportunities, and do not constitute an official announcement that the Kingdom of Saudi Arabia has absolutely approved all AI-generated clinical evidence or replaced traditional patient studies with digital simulation. Furthermore, the presentation does not certify the launch of a new approved therapeutic product.
Shared international standards and upcoming regulatory steps<nThe international context of these discussions takes on added importance because drug regulators are tasked with evaluating scientific evidence generated across diverse healthcare systems, populations, and research institutions worldwide. Standardizing reporting formats and guidelines can help scientific assessors understand instances where results are transferable and generalizable, while technical documentation, transparent validation, and uncertainty management procedures remain critical and indispensable elements.
This report, issued on November 6, relates directly to the general regulatory sector in Saudi Arabia. However, given that the source is a report on a conference presentation, it is scientifically classified one tier below peer-reviewed published research and completed operational achievements. Upcoming developments worth monitoring include the issuance of published regulatory guidance from the Saudi Food and Drug Authority, the establishment of pilot evaluations, the publication of peer-reviewed studies validating models, and the release of official decisions defining how simulation evidence is utilized.
Frequently asked questions
Question: What did the Saudi Food and Drug Authority discuss at the Seoul summit?
Answer: Its CEO, Dr. Hisham Aljadhey, discussed deploying artificial intelligence and in silico clinical trials to accelerate drug development and support regulatory evaluation during the International Coalition of Medicines Regulatory Authorities summit.
Question: What are in silico clinical trials?
Answer: They are trials that use computer simulation and artificial intelligence to model biological processes and predict drug interactions with the human body, proving particularly useful in studying rare diseases with limited patient numbers.
Question: Has Saudi Arabia canceled traditional clinical trials in favor of artificial intelligence?
Answer: No, the authority’s discussion focuses on exploring research and regulatory opportunities to integrate computational evidence with traditional methods, and the authority has not announced replacing patient trials or adopting all computer-generated evidence.
Question: What conditions are necessary to adopt computer simulation in drug evaluation?
Answer: They require comprehensive technical documentation, transparent scientific validation, and consistent international standards ensuring that computer model assumptions reflect patients’ true biological factors without omitting influential variables.
