miRNA Expression Profiling for Cell Therapy Predictability
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Solution Overview
Problem
Cell therapies face variability in performance and predictability due to differences in cell phenotype and target tissue characteristics, affecting efficacy and efficiency, and there is a need for improved methods to predict functional outcomes for selection decisions in cell applications.
Innovation Solution
The use of non-coding RNA, specifically microRNA (miRNA) expression data to identify and predict cellular functional effects by correlating miRNA expression profiles with known cellular functions, enabling selection of donor cells or cell batches for enhanced therapeutic efficacy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cell therapy is applied to treat biological conditions, then therapeutic efficacy is improved, but performance variability and unpredictability increase due to differences in cell phenotype and target tissue characteristics
Solution Approach 1:
The patent applies preliminary action by profiling miRNA expression in cells before they are used for therapy. This allows prediction of functional outcomes in advance, enabling selection of cells with desired characteristics and preparation of appropriate dosing regimens before actual therapeutic application, thereby improving predictability while accounting for cellular variability
Solution Approach 2:
The patent implements feedback by establishing a system where miRNA expression profiles are measured, functional outcomes are predicted, and cell selection/dosing is adjusted based on these predictions. This closed-loop approach allows optimization of therapeutic outcomes by using predicted responses to guide further decisions, improving reliability despite phenotypic variability
2Productivity
If conventional cell therapy approaches are used, then treatment is provided, but efficacy and efficiency are considerably affected by performance variability
Solution Approach 1:
The patent applies parameter changes by shifting from conventional cell counting metrics to miRNA expression profiling as the selection criterion. This parameter change enables prediction of functional outcomes and allows optimization of cell selection and dosing to achieve consistent efficacy and improved efficiency across different cell batches and donors
3Loss of information
If cell selection and dosing are made without functional prediction, then treatment administration is simplified, but therapeutic outcome predictability is reduced
Solution Approach 1:
The patent introduces miRNA expression profiling as an intermediary mechanism that bridges the gap between cell characteristics and therapeutic outcomes. This intermediary allows prediction of functional responses without requiring direct measurement of all possible cellular interactions, maintaining operational simplicity while reducing information loss about therapeutic potential
Data Source
AI summary
Non-coding RNA, such as miRNA, expression data derived from a cell population is used to infer the propensity of that cell population for a cellular functional effect for a pre-determined purpose, which effect is temporally, procedurally or interventionally separated from the cell population from which the expression data is derived. Thereby, the cellular functional effect of a cell population can be predicted in order to improve decisions and selections to be made relating to the use of cells, e.g. from cells deriving from different donors or batches, for use in bioprocess application or cell therapeutics, in order to enhance productivity, efficiency and/or efficacy.