# A hybrid, iterative approach, to support the development of fit-for-purpose sensor-derived measures

## TL;DR

This paper suggests a new method to develop digital health tools that consider both patient needs and data quality to speed up drug development.

## Contribution

The novel contribution is a hybrid approach integrating patient-centric and data-centric elements for developing fit-for-purpose DHTs.

## Key findings

- A hybrid methodology can streamline DHT approval by combining patient and data considerations.
- The approach fosters collaboration among stakeholders and improves clinical integration of DHTs.
- Emphasizing patient relevance and data feasibility enhances drug development efficiency.

## Abstract

Digital Health Technologies (DHTs) hold immense potential for transforming drug development. Although innovation in the DHT space has been rapid, the approval process for these technologies remains slow due to fragmented efforts from industry and researchers, as well as regulatory challenges. In this position paper, we propose a hybrid methodology and approach for developing fit-for-purpose DHTs for assessment by integrating both patient-centric and data-centric elements. By emphasizing patient relevance while considering device and data feasibility, we can advance the development of patient-centric digital measures efficiently without compromising measurement precision. Ultimately, this hybrid approach aims to streamline the approval process, foster collaboration among stakeholders, and accelerate the integration of DHTs into clinical practice, thereby enhancing the overall efficiency and effectiveness of drug development.