# Sensor extended imaging workflow for creating fit for purpose models in basic and applied cell biology

## TL;DR

The paper proposes using an engineering-inspired sensor-extended imaging workflow to create more realistic and predictive cell models for biology research and drug development.

## Contribution

Introduces a sensor-extended imaging workflow to bridge the gap between in vitro cell models and human physiology for translational research.

## Key findings

- Traditional cell biology methods are limited in mimicking human physiology and drug responses.
- An iterative sensor-extended workflow can expand the solution space for physiologically relevant cell models.
- Interactive, context-dependent design approaches are needed for better translational in vitro models.

## Abstract

While various engineering disciplines spent years on developing methods and workflows to increase their R&D efficiency, the field of cell biology has seen limited evolution in the fundamental approaches to interact with living cells. Perturbations are mostly of chemical nature, and physiologically relevant contexts and stimuli are left with limited attention, resulting in a solution space constrained within the boundaries of presently manageable perturbations. To predict in the laboratory how a drug will work in a human patient, cell biology must have a closer look at life and strive to mimic the human being in all his complexity. By implementing an iterative process from perturbation to measurement and vice versa, the authors suggest using a sensor-extended imaging workflow to implement product development practices to cell biology, opening a physiologically relevant solution space for the development of truly translational and predictive fit for purpose in vitro cell models.

In this Perspective, the authors argue that it is time for biology to expand the traditional approach of observation with an engineering approach that transforms the nature of the underlying experiments to interactive context-depended design problems.