In silico clinical trials in drug development: a systematic review
Journal:
arXiv
Published Date:
Mar 11, 2025
Abstract
In the context of clinical research, computational models have received
increasing attention over the past decades. In this systematic review, we aimed
to provide an overview of the role of so-called in silico clinical trials
(ISCTs) in medical applications. Exemplary for the broad field of clinical
medicine, we focused on in silico (IS) methods applied in drug development,
sometimes also referred to as model informed drug development (MIDD). We
searched PubMed and ClinicalTrials.gov for published articles and registered
clinical trials related to ISCTs. We identified 202 articles and 48 trials, and
of these, 76 articles and 19 trials were directly linked to drug development.
We extracted information from all 202 articles and 48 clinical trials and
conducted a more detailed review of the methods used in the 76 articles that
are connected to drug development. Regarding application, most articles and
trials focused on cancer and imaging related research while rare and pediatric
diseases were only addressed in 18 and 4 studies, respectively. While some
models were informed combining mechanistic knowledge with clinical or
preclinical (in-vivo or in-vitro) data, the majority of models were fully
data-driven, illustrating that clinical data is a crucial part in the process
of generating synthetic data in ISCTs. Regarding reproducibility, a more
detailed analysis revealed that only 24% (18 out of 76) of the articles
provided an open-source implementation of the applied models, and in only 20%
of the articles the generated synthetic data were publicly available. Despite
the widely raised interest, we also found that it is still uncommon for ISCTs
to be part of a registered clinical trial and their application is restricted
to specific diseases leaving potential benefits of ISCTs not fully exploited.
