PATENT CLAIM ANALYSIS

Application Number: 16210523
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-04
Patent Classification: ["506", "016000"]

Abstract:
The invention describes a method for the identification of compounds which bind to a target component of a biochemical system or modulate the activity of the target, by compartmentalizing the compounds into microcapsules together with the target, such that only a subset of the repertoire is represented in multiple copies in any one microcapsules; and identifying the compound which binds to or modulates the activity of the target. The invention enables the screening of large repertoires of molecules which can serve as leads for drug development.

Claim (Index 1):
A method for analyzing nucleic acids, the method comprising:\n providing a sample comprising nucleic acid to a microfluidic device comprising at least one microfluidic channel; forming on the microfluidic device a plurality of aqueous microcapsules surrounded by an oil, each of the plurality of microcapsules comprising a portion of the nucleic acid and reagents for an enzyme-catalyzed reaction; conducting the enzyme-catalyzed reaction on the nucleic acid in the microcapsules while the microcapsules are on the microfluidic device; and detecting a reaction product within at least one of the microcapsules, wherein the detection comprises detecting a fluorescent dye.

Metadata:
- Claim Count in Document: 23.0
- Percentile: 98.0
- Lexical Diversity: 1.59649
- Patent Class: 506.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15855612', '11238258', '13208614', '11665099', '15331445']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5179373196089249
- 35 USC 102 Novelty (BERT): 0.5298420052328787
- Combined Prediction Score: 0.5191277881713202
- Mean Citation Score: 324.874054
- Max Citation Score: 361.44986
- Similarity Product: 299.14917612304686

Labels:
- Claim Label 101: 1
- Claim Label 102: 0
- Claim Label 103: 0
- Claim Label 112: 0
- Combined Label: 0
- Label 101 Adjusted: 1

Dataset: test