Key points are not available for this paper at this time.
With many advancements in in silico multiscale biology in recent years, the paramount challenge is to translate the accumulated knowledge into exciting industry partnerships and clinical applications. Historically, the pharmaceutical industry has worked well with in silico models by leveraging their prediction capabilities for drug testing. However, the needed higher fidelity and higher resolution of models for efficient prediction of pharmacological phenomenon dictates that in silico approaches must account for the verifiable multiscale biophysical phenomena, as a spatial and temporal dimension variation for different processes and models. Our paper has two main goals: 1) To clarify to what extent detailed single- and multiscale modeling has been accomplished thus far, we provide a review on this topic focusing on the biophysics of epithelial, cardiac, and brain tissues; 2) To discuss the present and future role of multiscale biophysics in in silico pharmacology as a digital twin solution by defining a roadmap from simple biophysical models to powerful prediction tools. Digital twins have the potential to pave the way for extensive clinical and pharmaceutical usage of multiscale models, and our paper shows the fundamentals and opportunities for their accurate development, enabling the quantum leaps of future precise and personalized medical software.
Barros et al. (Mon,) studied this question.