Is personal physiology-based rapid prediction digital twin for minimal effective fentanyl dose better than standard practice: a pilot study protocol

Introduction
Patients with advanced cancer frequently suffer from chronic, severe disabling pain. Opioids such as morphine and fentanyl are commonly used to manage this pain. Transdermal drug delivery systems are important technologies for administering drugs in a non-invasive, continuous and controlled manner. Due to the narrow therapeutic range of fentanyl, individualised dosing is essential to avoid underdosing or overdosing. Standard clinical calculation tools for opioid rotation however do not include important patient characteristics that account for interindividual variability of opioid pharmacology.

Methods and analysis
We developed a clinical protocol to optimise individual fentanyl dosing in patients with advanced cancer switching from oral or intravenous opioids to transdermal fentanyl by using a physics-based digital twin (DT) that is fed by important clinical and physiological parameters. Individual tailoring of transdermal fentanyl therapy is an approach with the potential for personalised and effective care with an improved benefit-risk ratio. However, clinical validation of physics-based digital twins (PBDT) dosing is crucial to proving clinical benefit.
Therapeutic drug monitoring will allow to validate the accuracy of PBDT predictions. Additional monitoring for breathing dynamics, sequential pain levels and fentanyl-related adverse events will contribute to evaluating the performance of PBDT-based dosing of transdermal fentanyl. The primary objective of the study is to develop an experimental protocol to validate DT-guided fentanyl dosing in patients with advanced cancer. This clinical study will bring individualised opioid dosing closer to clinical practice.

Ethics and dissemination
Study documents have been approved by the responsible Ethics Committee and study initiation is planned for late summer 2024. Data will be shared with the scientific community no more than 1 year following completion of the study and data assembly.

Leggi
Settembre 2024

Digital wound monitoring with artificial intelligence to prioritise surgical wounds in cardiac surgery patients for priority or standard review: protocol for a randomised feasibility trial (WISDOM)

Introduction
Digital surgical wound monitoring for patients at home is becoming an increasingly common method of wound follow-up. This regular monitoring improves patient outcomes by detecting wound complications early and enabling treatment to start before complications worsen. However, reviewing the digital data creates a new and additional workload for staff. The aim of this study is to assess a surgical wound monitoring platform that uses artificial intelligence to assist clinicians to review patients’ wound images by prioritising concerning images for urgent review. This will manage staff time more effectively.

Methods and analysis
This is a feasibility study for a new artificial intelligence module with 120 cardiac surgery patients at two centres serving a range of patient ethnicities and urban, rural and coastal locations. Each patient will be randomly allocated using a 1:1 ratio with mixed block sizes to receive the platform with the new detection and prioritising module (for up to 30 days after surgery) plus standard postoperative wound care or standard postoperative wound care only. Assessment is through surveys, interviews, phone calls and platform review at 30 days and through medical notes review and patient phone calls at 60 days. Outcomes will assess safety, acceptability, feasibility and health economic endpoints. The decision to proceed to a definitive trial will be based on prespecified progression criteria.

Ethics and dissemination
Permission to conduct the study was granted by the North of Scotland Research Ethics Committee 1 (24/NS0005) and the MHRA (CI/2024/0004/GB). The results of this Wound Imaging Software Digital platfOrM (WISDOM) study will be reported in peer-reviewed open-access journals and shared with participants and stakeholders.

Trial registration numbers
ISRCTN16900119 and NCT06475703.

Leggi
Settembre 2024