Digital Quantitative Detection via Compartment Partitioning

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Solution Overview

Problem

Conventional quantitative detection methods are inefficient in accurately detecting low-abundance biological specimens and weak molecular interactions, often requiring numerous manual steps, leading to errors and reduced sensitivity and specificity, making them unsuitable for industrial applications.

Innovation Solution

The method involves partitioning a mixture of a target and probes into countable compartments, allowing for parallel measurements and optical detection, enabling precise quantification by distinguishing between different probes and determining the presence of the target through Poisson distribution analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional quantitative detection methods are used, then detection can be performed, but detection sensitivity and accuracy for low-abundance targets deteriorates

Engineering Contradiction:
Improvedetection sensitivityVSAvoidtarget abundance
Core Design Contradiction:
Measurement precisionVSQuantity of substance

Solution Approach 1:

The detection mixture is partitioned into numerous discrete compartments (e.g., droplets, wells), transforming a continuous measurement problem into discrete countable units. This segmentation enables digital detection where each compartment independently captures target-probe interactions, significantly improving sensitivity for low-abundance targets through statistical amplification across many partitions.

Inventive Principle:
Principle #1Segmentation

2Productivity

If manual detection steps are used, then detection can be performed, but detection speed and productivity deteriorates

Engineering Contradiction:
Improvedetection speedVSAvoidmanual steps
Core Design Contradiction:
ProductivityVSEase of operation

Solution Approach 1:

The system enables automated detection where compartments are automatically partitioned, probed, and read without extensive manual intervention. The digital nature of the assay allows for automated data collection and analysis across thousands of compartments simultaneously, eliminating bottlenecks associated with manual processing and significantly increasing throughput.

Inventive Principle:
Principle #25Self-service

3Reliability

If numerous detection steps are used, then comprehensive detection can be achieved, but time consumption and error probability increases

Engineering Contradiction:
Improvedetection accuracyVSAvoiddetection time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

Multiple detection functions are merged into a single digital assay format. The partitioning approach allows simultaneous performance of target capture, signal generation, and detection across all compartments in parallel. This consolidation eliminates sequential processing steps, reducing both time consumption and opportunities for human error while maintaining comprehensive detection capabilities.

Inventive Principle:
Principle #5Merging (Combining)

4Reliability

If manual or semi-automatic evaluation is used, then flexibility is maintained, but reproducibility and detection consistency deteriorates

Engineering Contradiction:
ImprovereproducibilityVSAvoidautomatic evaluation
Core Design Contradiction:
ReliabilityVSExtent of automation

Solution Approach 1:

Manual evaluation processes are replaced with automated optical detection and digital data analysis systems. The compartmentalized format enables machine-readable signals that can be automatically quantified and analyzed, eliminating variability introduced by manual assessment and ensuring consistent, reproducible results across different operators and laboratories.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach significantly accelerates detection speed, improves sensitivity and reproducibility, and allows for robust statistical analysis, even at low target concentrations, by accurately counting compartments and eliminating false positive counts.

Implementation Method 1

Compartments might be made of droplets formed by a phase boundary, preferably in which a first fluid is surrounded by a second fluid, as it might be the case in a water-oil emulsion system

Methodology Applied
Scientific EffectPhase separation/Emulsion: Emulsion

Implementation Method 2

The determination of the quantities referred to in claim 1 is done preferably by measurement, for example counting... Counting of the compartments can be done optically

Methodology Applied
Scientific EffectOptical detection:

Data Source

PatentEP4242656A1Quantitative detection method and corresponding device
Publication Date: 2023.09.13 ACTOME GMBH
  • EP4242656A1 patent drawingFigure 1~2
  • EP4242656A1 patent drawingFigure 3~4
  • EP4242656A1 patent drawingFigure 5~7

AI summary

The invention generally suggests a quantitative detection method (1) for a target (2), whereby the target (2), a first probe (3), and a second probe (4) are mixed, wherein the first and second probes (3, 4) bind to the target (2) and wherein a presence of the first probe (3) can be distinguished from a presence of the second probe (4), wherein the mixture (5) of the target (2) and the first and second probes (3, 4) is partitioned in countable compartments (6), wherein a quantity relating to a number of compartments (6), a quantity relating to a number of compartments (6) where at least the first probe (3) is present, a quantity relating to a number of compartments (6) where at least the second probe (4) is present and a quantity relating to a number of compartments (6) where both the first probe (3) and the second probe (4) are present are determined and wherein a quantity relating to a number of compartments (6) that contain the target (2) is determined automatically from the determined quantities (Fig. Fig. 6).