Design specifications for biomedical virtual twins in engineered adoptive cellular immunotherapies.

Area of Science:

• Immunotherapy
• Computational Biology
• Oncology

Background:

• Virtual twins (VTs) are emerging as powerful tools for personalized decision support in immuno-oncology.
• Current VTs lack the capability to model the unique biological characteristics of engineered adoptive cellular immunotherapies (eACIs).
• This limitation hinders the integration of advanced cellular therapies with predictive modeling.

Purpose of the Study:

• To define the essential design specifications for virtual twins tailored to engineered adoptive cellular immunotherapies (eACI-VTs).
• To establish a framework for modeling the intricate interactions between eACI cell products and individual patient physiology.
• To advocate for the use of eACI-VTs in clinical decision-making for eACIs.

Main Methods:

• Outlining minimal design specifications for eACI-VTs.
• Focusing on modeling the complex interplay between cell product properties and patient physiological parameters.
• Conceptualizing the integration of eACI-VTs into clinical workflows.

Main Results:

• Proposed minimal design specifications for virtual twins capable of modeling engineered adoptive cellular immunotherapies.
• Demonstrated the potential of eACI-VTs to capture the unique aspects of cell product behavior within a patient's system.
• Highlighted the necessity of such models for accurate prediction and patient-specific treatment guidance.

Conclusions:

• eACI-VTs are crucial for accurately modeling engineered adoptive cellular immunotherapies in immuno-oncology.
• These specialized VTs can provide essential patient-individual decision support for complex cell-based treatments.
• Developing and implementing eACI-VTs can facilitate the broader adoption and effective use of engineered cellular immunotherapies.