Phenotypic Response Surface for Personalized Immunosuppression Dosing
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Solution Overview
Problem
Current immunosuppression dosing strategies in transplant patients rely on population-based data, failing to account for individual variability in drug metabolism and immune response, leading to risks of infection, toxicity, and graft rejection.
Innovation Solution
The use of an artificial intelligence-based complex systems approach called phenotypic personalized medicine (PPM) to optimize immunosuppression dosing by generating a Phenotypic Response Surface (PRS) based on individual patient data, including donor-derived cell-free DNA fraction as a biomarker for allograft injury.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If population-based dosing protocols are used, then standardization and ease of implementation are improved, but individual patient variability in drug metabolism and immune response is not accounted for, leading to over- or underimmunosuppression
Solution Approach 1:
The patent changes the dosing parameter from fixed population-based protocols to dynamic, personalized dosing based on measured phenotypic parameters. The system measures multiple phenotypic parameters (drug concentrations, immune markers, metabolic rates) and adjusts dosing parameters accordingly to achieve optimal immunosuppression for each individual patient.
Solution Approach 2:
The patent implements a feedback mechanism where patient responses to immunosuppression are continuously monitored through phenotypic measurements. This feedback loop allows the system to adjust dosing regimens based on actual patient responses, correcting for individual variability in drug metabolism and immune response over time.
2Reliability
If increased immunosuppression is administered, then graft rejection is prevented, but risk of infection and toxicity increases
Solution Approach 1:
The patent applies local quality by tailoring the immunosuppression intensity to the specific needs of each patient and even to different time points. Rather than uniform high-dose immunosuppression, the system adjusts dosing locally based on individual phenotypic characteristics and real-time patient response, providing just enough suppression to prevent rejection while minimizing toxicity.
Solution Approach 2:
The patent transitions from static dosing protocols to dynamic dosing that adapts to changing patient conditions. The system continuously monitors phenotypic parameters and adjusts immunosuppression levels dynamically, increasing when rejection risk is high and decreasing when infection risk emerges, thereby balancing graft protection with patient safety.
3Reliability
If drug combinations acting on multiple targets are used, then immunosuppression efficacy is improved, but complexity of dosing optimization and ADME variability increases
Solution Approach 1:
The patent manages combination drug dosing by measuring phenotypic parameters that reflect the integrated effect of multiple drugs on their various targets. Rather than attempting to optimize each drug independently, the system measures downstream phenotypic outcomes and adjusts the combination dosing parameters to achieve the desired overall immunosuppressive effect, simplifying the optimization process.
Solution Approach 2:
The patent uses phenotypic measurements as intermediary indicators of drug efficacy and toxicity. These phenotypic markers serve as mediators that translate the complex interactions of multiple drugs on multiple targets into measurable outcomes, allowing the system to optimize combination dosing based on actual biological response rather than theoretical drug interactions.
Data Source
AI summary
The art does not provide systematic and reproducible methods to personalize dosing of multiple immunosuppressive medications after transplantation. This invention provides a method to systematize multi-drug immuno suppression management in tissue and organ transplantation using an artificial intelligence-based complex systems approach. In embodiments of this invention, immunosuppression drug dose, blood drug concentrations, donor-derived fraction of cell free DNA (dd-cfDNA %), and aspartate aminotransferase are used to indicate allograft status or a proxy for allograft status, to generate a phenotypic response surface to produce individual treatment modalities and dosages using empirically determined unique coefficients. This surface is used to calculate appropriate immunosuppression drug doses associated with the desired outcome for that patient. Embodiments of this disclosure are directed to identifying optimized combinations of inputs for the complex system of the immunosuppressed transplant patient in order to avoid transplant rejection while avoiding unnecessary toxicity and maintaining a robust enough immune response to fight infection.