Predicting transdermal fentanyl delivery using physics-based simulations for tailored therapy based on the age.

Area of Science:

• Pharmacology
• Biomedical Engineering
• Computational Modeling

Background:

• Transdermal fentanyl patches offer sustained pain relief but require careful monitoring due to fentanyl's narrow therapeutic range.
• Optimizing fentanyl delivery is crucial for balancing effective analgesia with avoiding adverse effects like respiratory depression.

Observation:

• A physics-based digital twin was developed, integrating drug uptake, pharmacokinetic, and pharmacodynamic models.
• The digital twin simulated the effects of fentanyl transdermal patches in a virtual patient population aged 20-80 years.

Findings:

• Increasing patient age correlated with decreased maximum transdermal fentanyl flux (11.4%) and blood concentration (7.0%).
• Conversely, older patients experienced a 45.2% increase in pain relief.
• Age-tailored therapy, adjusting patch application frequency, significantly improved pain relief (30%) and pain-free duration (315%) in younger patients.

Implications:

• Patient-specific digital twins can guide personalized pain management strategies, optimizing fentanyl patch therapy.
• Integrating real-time feedback into digital twins enhances treatment safety and efficacy, potentially improving respiratory function alongside analgesia.
• This approach highlights the potential of digital twin technology for advancing precision medicine in chronic pain management.