PATENT CLAIM ANALYSIS

Application Number: 16171596
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-02
Patent Classification: ["702", "019000"]

Abstract:
Described herein are techniques for more precisely identifying antibodies that may have a high affinity to an antigen. The techniques may be used in some embodiments for synthesizing entirely new antibodies for screening for affinity, and for more efficiently synthesizing and screening antibodies by identifying, prior to synthesis, antibodies that are predicted to have a high affinity to the antigen. In some embodiments, a machine learning engine is trained using affinity information indicating a variety of antibodies and affinity of those antibodies to an antigen. The machine learning engine may then be queried to identify an antibody predicted to have a high affinity for the antigen.

Claim (Index 61):
The at least one non-transitory computer-readable storage medium of  claim 58 , wherein the first characteristic is affinity of an amino acid sequence for the target and the second characteristic is affinity or lack of affinity for a second target.

Metadata:
- Claim Count in Document: 53.0
- Percentile: 97.0
- Lexical Diversity: 2.15094
- Patent Class: 702.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['11414742', '11566120', '13929338', '10153159', '11473745']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1768282686456605
- 35 USC 102 Novelty (BERT): 0.5003256656295081
- Combined Prediction Score: 0.2091780083440453
- Mean Citation Score: 195.733258
- Max Citation Score: 201.81108
- Similarity Product: 132.0339179185009

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

Dataset: test