Insights in Translational Systems Biology and In Silico Trials

Translational systems biology and in silico trials are becoming increasingly important for translating mechanistic biomedical knowledge into personalized clinical care. By integrating systems pharmacology, biomedical engineering, digital health, and clinical medicine, these approaches can connect cellular and molecular mechanisms with patient-level outcomes. However, substantial questions remain regarding how reliably virtual patient cohorts can predict drug efficacy, safety, disease progression, and treatment response, and how computational evidence should complement conventional clinical trials. Recent advances in quantitative systems pharmacology, mechanistic disease modeling, digital twins, biomarker integration, and computational trial design have demonstrated the potential of these methods to address complex biological and clinical problems. Nevertheless, challenges persist in model interoperability, data quality, uncertainty quantification, clinical validation, reproducibility, and regulatory acceptance. Further investigation is needed to establish robust workflows that translate computational predictions into clinically actionable and trusted evidence.This Insights in collection aims to provide an overview of recent advances in translational systems biology and in silico trials, while identifying the scientific, computational, clinical, and regulatory priorities that will shape the field. It seeks to explore how mechanistic cellular models can be connected with virtual physiological patients to support drug discovery, personalized dosing, clinical trial design, biomarker evaluation, and regulatory decision-making. Contributions may also examine the validation of computational models against experimental and clinical data, the integration of heterogeneous biomedical datasets, and the development of standards for reliable and reproducible computational medicine.To gather further insights into the translation of mechanistic and computational models into clinical practice, this Insights in collection will focus on approaches that support predictive, validated, and clinically relevant applications of systems biology and in silico trials. We welcome articles addressing, but not limited to, the following themes:• Design, validation, and execution of in silico clinical trials• Quantitative systems pharmacology models for drug discovery, efficacy, safety, and dosing• Generation and modeling of virtual patient cohorts for predictive and personalized medicine• Systems-level clinical translation of biomarkers and diagnostic datasets• Mechanistic modeling of disease progression and therapeutic intervention• Digital twins of human organs, patients, and physiological processes• Integration of multimodal clinical, molecular, imaging, and real-world data• Model uncertainty, sensitivity analysis, interoperability, and reproducibility• Clinical validation and benchmarking of computational models• Regulatory frameworks, standards, and qualification pathways for computational medicineThis collection welcomes contributions reflecting on current developments and plotting pathways for upcoming research, from Editorial Board Members of the section, from authors they refer, and, on invitation, from a number of external researchers whose work is shaping the direction of the field. Authors are encouraged to engage critically with their fields, identify the current challenges, and propose novel solutions that advance our understanding of complex biological systems. Topic editors: Susan Mertins, Mohammadreza Nikmaneshi Source: https://www.frontiersin.org/research-topics/84676/insights-in-translational-systems-biology-and-in-silico-trials