PATENT CLAIM ANALYSIS

Application Number: 16010847
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-12
Patent Classification: ["514", "021800"]

Abstract:
A method of treating liver inflammation in an individual caused by excess fat deposition, sometimes called “fatty liver disease”, which may be caused by metabolic syndrome, insulin resistance, or gut microbial dysbiosis, and which may lead to the serious and potentially life-threatening condition of non-alcoholic steatohepatitis (NASH) comprising the steps of preparing a composition composed of an all-D amino acid peptide and a pharmaceutically acceptable carrier. The D peptide has the general structure: A-B-C-D-E in which A is Ser, Thr, Asn, Glu, Ile. B is Ser, Thr, Asp, Asn, C is Thr, Ser, Asn, Arg, Lys, Trp, D is Tyr, and E is Thr, Ser, Arg, Gly. And wherein all amino acids in the D peptide are the D stereoisomeric configuration and said peptide composition is administered in a therapeutically effective dose wherein said composition acts to suppress inflammation underlying steatohepatitis. The D peptide may be esterified, glycosylated, or amidated at E to enhance tissue distribution by promoting egress from the circulation and penetration into the liver.

Claim (Index 7):
The method of disease treatment as defined in  claim 5  wherein said chemokine receptor antagonist interacts with multiple chemokine receptors.

Metadata:
- Claim Count in Document: 10.0
- Percentile: 94.0
- Lexical Diversity: 1.85321
- Patent Class: 514.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14263347', '13024324', '15936686', '13392548', '15035571']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7382101349935034
- 35 USC 102 Novelty (BERT): 0.5205008501917235
- Combined Prediction Score: 0.7164392065133254
- Mean Citation Score: 234.41061200000004
- Max Citation Score: 288.18106
- Similarity Product: 208.24954020742047

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

Dataset: test