PATENT CLAIM ANALYSIS

Application Number: 15882507
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-06
Patent Classification: ["424", "181100"]

Abstract:
The present invention concerns improved methods and compositions for preparing SN-38 conjugates of proteins or peptides, preferably immunoconjugates of antibodies or antigen-binding antibody fragments. More preferably, the SN-38 is attached to the antibody or antibody fragment using a CL2A linker, with 1-12, more preferably 6-8, alternatively 1-5 SN-38 moieties per antibody or antibody fragment. Most preferably, the immunoconjugate is prepared in large scale batches, with various modifications to the reaction scheme disclosed herein to optimize yield and recovery in large scale. Other embodiments concern optimized dosages and/or schedules of administration of immunoconjugate to maximize efficacy for disease treatment and minimize side effects of administration.

Claim (Index 11):
The method of  claim 1 , wherein the antibody moiety is selected from the group consisting of LL1 (anti-CD74), LL2 (anti-CD22), RFB4 (anti-CD22), RS7 (anti-EGP-1), PAM4 (anti-MUC5AC), KC4 (anti-mucin), A19 (anti-CD19), A20 (anti-CD20), MN-14 (anti-CEACAM5), MN-15 (anti-CEACAM6), MN-3 (anti-CEACAM6), R1 (anti-IGF-1R), Mu-9 (anti-CSAp), Immu 31 (anti-AFP), CC49 (anti-TAG-72), J591 (anti-PSMA), HuJ591 (anti-PSMA), AB-PG1-XG1-026 (anti-PSMA dimer), D2/B (anti-PSMA), G250 (anti-carbonic anhydrase IX) and hL243 (anti-HLA-DR).

Metadata:
- Claim Count in Document: 62.0
- Percentile: 86.0
- Lexical Diversity: 1.57534
- Patent Class: 424.0
- Transitional Phrase Type: closed
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15161806', '14789375', '15196586', '14255508', '15441653']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.8775729115427672
- 35 USC 102 Novelty (BERT): 0.6991863723178415
- Combined Prediction Score: 0.8597342576202747
- Mean Citation Score: 772.606094
- Max Citation Score: 786.84924
- Similarity Product: 715.3473405441785

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

Dataset: test