PATENT CLAIM ANALYSIS

Application Number: 16128421
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-01
Patent Classification: ["424", "277100"]

Abstract:
Disclosed herein is a system and methods for determining the alleles, neoantigens, and vaccine composition as determined on the basis of an individual's tumor mutations. Also disclosed are systems and methods for obtaining high quality sequencing data from a tumor. Further, described herein are systems and methods for identifying somatic changes in polymorphic genome data. Finally, described herein are unique cancer vaccines.

Claim (Index 11):
The method of  claim 6 ,\n wherein the machine-learned presentation model includes a neural network model configured to receive a peptide sequence of the neoantigen and generate a set of dependency scores for each class I MHC allele in the set of class I MHC alleles, and wherein applying the machine-learned presentation model to the peptide sequence of the neoantigen comprises:\n applying the neural network model to the peptide sequence to generate the set of dependency scores for the neoantigen, and \n selecting one or more dependency scores from the set of dependency scores that are associated with the one or more class I MHC alleles of the subject.

Metadata:
- Claim Count in Document: 29.0
- Percentile: 97.0
- Lexical Diversity: 1.47917
- Patent Class: 424.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15466729', '15210489', '15170919', '13640989', '15791301']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7721891399870697
- 35 USC 102 Novelty (BERT): 0.6222374655478639
- Combined Prediction Score: 0.7571939725431491
- Mean Citation Score: 388.519416
- Max Citation Score: 745.2901
- Similarity Product: 491.8491062409223

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