JMIR Publications

ABSTRACT

Background:

Although effective, current CAR-T production methods — centralized, manual, and complex — are cost-intensive, time-consuming, and prone to variability. AIDPATH proposes a decentralized, automated alternative that integrates patient-specific data, optimizes resource use, and potentially improves cell viability, manufacturing efficiency, and patient outcomes.

Objective:

The aim of this study was to compare AIDPATH-produced CAR-T therapy to both Cilta-Cel and standard of care (SoC) for triple-class refractory multiple myeloma (MM) patients, over a 40-year time horizon in Germany from the hospital perspective.

Methods:

A partitioned survival model reflecting 3 health states (progression-free disease, progressed disease, and death) was used. The analysis used clinical trial data for Cilta-Cel, real-world data for SoC, and estimated parameters for AIDPATH, due to the developmental status of the platform. The primary outcome was the incremental cost effectiveness ratio, secondary outcomes included sensitivity and scenario analyses.

Results:

AIDPATH was dominant compared to both Cilta-Cel and SoC. Most costs for CAR-T therapies were driven by acquisition and adverse events. Sensitivity analyses showed the results were most influenced by discount rates and assumptions about progression-free survival. Scenario analyses, including reduced adverse events and shorter vein-to-vein time for AIDPATH, further supported its cost-effectiveness.

Conclusions:

This is the first study to assess the cost-effectiveness of CAR-T product generated with AI support in Germany from the hospital perspective. AIDPATH was found to be a cost-effective alternative to both Cilta-Cel and SoC, making it a promising option for future implementation. While further data are needed, this study provides valuable guidance for health care stakeholders, reimbursement discussions, and future research.