From multiscale biophysics to digital twins of tissues and organs: future opportunities for in silico pharmacology

TL;DR

This paper reviews the progress in multiscale biophysical modeling of tissues and discusses how digital twins can revolutionize in silico pharmacology by enabling personalized medicine and improved drug development.

Contribution

It provides a comprehensive review of current multiscale tissue models and outlines a roadmap for developing digital twin solutions for pharmacology.

Findings

Significant progress in modeling epithelial, cardiac, and brain tissues.

Digital twins can enhance drug testing and personalized medicine.

Future models require higher fidelity and multiscale integration.

Abstract

With many advancements in in silico biology in recent years, the paramount challenge is to translate the accumulated knowledge into exciting industry partnerships and clinical applications. Achieving models that characterize the link of molecular interactions to the activity and structure of a whole organ are termed multiscale biophysics. 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. The collection of different multiscale models for different tissues and organs can compose digital twin solutions towards becoming a service for researchers, clinicians, and drug developers. 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 basic fundamentals and opportunities towards their accurate development enabling the quantum leaps of future precise and personalized medical software.