Advanced in silico drug design strategies for mitigating transplant rejection: a status update

Current immunosuppressive regimens in solid organ transplantation (SOT) have markedly improved short-term graft survival. However, the adverse effects of these drugs, together with incomplete control of rejection, underscore the need for new, more selective therapies. In silico approaches offer a useful and underexploited avenue in SOT.

This review summarizes in silico strategies used to discover drugs for the prevention of allograft rejection. The authors discuss the identification of therapeutic targets using omics data, followed by computational drug repositioning approaches and the main principles of computer-aided drug design (CADD). They also highlight applications to immune targets that are relevant to transplantation. Finally, the authors examine emerging advances in quantitative systems pharmacology (QSP) and virtual clinical trials and their potential use in SOT. The literature was identified through searches of PubMed and Scopus for articles published between 2015 and 2025, from the last 10 years in SOT and, when necessary, on work in related immune-mediated diseases.

In silico approaches already offer a framework to prioritize safer and more selective immunomodulators in SOT. However, integration across omics-based target discovery, CADD, computational repurposing and QSP is still uncommon in this field. Building multidisciplinary consortia and adopting more standardized analytical workflows will be essential to unlock their full translational potential.