PATENT CLAIM ANALYSIS

Application Number: 16175357
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-02
Patent Classification: ["424", "143100"]

Abstract:
The present invention provides apelin receptor (APLNR) modulators that bind to APLNR and methods of using the same. The invention includes APLNR modulators such as antibodies, or antigen-binding fragments thereof, that inhibit or attenuate APLNR-mediated signaling. The invention includes APLNR modulators such as antibodies, or antibody fusion proteins thereof, that activate APLNR-mediated signaling. According to certain embodiments of the invention, the antibodies or antigen-binding fragments or antibody fusion proteins are fully human antibodies that bind to human APLNR with high affinity. The APLNR modulators of the invention are useful for the treatment of diseases and disorders associated with APLNR signaling and/or APLNR cellular expression, such as cardiovascular diseases, angiogenesis diseases, metabolic diseases and fibrotic diseases.

Claim (Index 7):
The isolated antibody, antibody-fusion protein or antigen-binding fragment of any one of  claims 1  to  6 , wherein the antibody, antibody-fusion protein or antigen-binding fragment comprises a HCVR/LCVR amino acid sequence pair selected from the group consisting of: SEQ ID NOs: 2/10, 18/26, 34/42, 50/58, 66/74, 82/90, 98/106, 114/122, 130/138, 146/154, 162/170, 178/186, 194/202, and 210/218.

Metadata:
- Claim Count in Document: 14.0
- Percentile: 97.0
- Lexical Diversity: 2.20339
- Patent Class: 424.0
- Transitional Phrase Type: closed
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14717914', '15480199', '15038202', '15146730', '14821652']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.8189711022766719
- 35 USC 102 Novelty (BERT): 0.6781112108837491
- Combined Prediction Score: 0.8048851131373796
- Mean Citation Score: 580.765096
- Max Citation Score: 724.49567
- Similarity Product: 651.0782614490354

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