PATENT CLAIM ANALYSIS

Application Number: 16006129
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-12
Patent Classification: ["702", "019000"]

Abstract:
Techniques for determining whether a subject is likely to respond to an immune checkpoint blockade therapy. The techniques include obtaining expression data for the subject, using the expression data to determine subject expression levels for at least three genes selected from the set of predictor genes consisting of BRAF, ACVR1B, MPRIP, PRKAG1, STX2, AGPAT3, FYN, CMIP, ROBO4, RAB40C, HAUS8, SNAP23, SNX6, ACVR1B, MPRIP, COPS3, NLRX1, ELAC2, MON1B, ARF3, ARPIN, SPRYD3, FLI1, TIRAP, GSE1, POLR3K, PIGO, MFHAS1, NPIPA1, DPH6, ERLIN2, CES2, LHFP, NAIF1, ALCAM, SYNE1, SPINT1, SMTN, SLCA46A1, SAP25, WISP2, TSTD1, NLRX1, NPIPA1, HIST1H2AC, FUT8, FABP4, ERBB2, TUBA1A, XAGE1E, SERPINF1, RAI14, SIRPA, MT1X, NEK3, TGFB3, USP13, HLA-DRB4, IGF2, and MICAL1; and determining, using the determined expression levels and a statistical model trained using expression data indicating expression levels for a plurality of genes for a plurality of subjects, whether the subject is likely to respond to the immune checkpoint blockade therapy.

Claim (Index 20):
The method of  claim 18 , wherein training the statistical model comprises iteratively adding regression variables for respective genes to the statistical model, at least in part by:\n identifying a candidate gene in the subset of genes; augmenting a current statistical model with a regression variable for the candidate gene to obtain an augmented statistical model; evaluating performance of the augmented statistical model; and determining to add the regression variable for the candidate gene to the current statistical model based on results of evaluating the performance.

Metadata:
- Claim Count in Document: 37.0
- Percentile: 94.0
- Lexical Diversity: 2.10784
- Patent Class: 702.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16006555', '16006572', '16006279', '16006340', '14399669']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.168487264450047
- 35 USC 102 Novelty (BERT): 0.5132595018969958
- Combined Prediction Score: 0.2029644881947418
- Mean Citation Score: 197.765114
- Max Citation Score: 229.69983
- Similarity Product: 138.5311874921358

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

Dataset: test