PATENT CLAIM ANALYSIS

Application Number: 16267546
Application Type: Utility
Filing Date: 2019-02
Publication Date: 2019-06
Patent Classification: ["340", "542000"]

Abstract:
For patients who exhibit or may exhibit primary or comorbid disease, pharmacological phenotypes may be predicted through the collection of panomic data over a period of time. A machine learning engine may generate a statistical model based on training data from training patients to predict pharmacological phenotypes, including drug response and dosing, drug adverse events, disease and comorbid disease risk, drug-gene, drug-drug, and polypharmacy interactions. Then the model may be applied to data for new patients to predict their pharmacological phenotypes, and enable decision making in clinical and research contexts, including drug selection and dosage, changes in drug regimens, polypharmacy optimization, monitoring, etc., to benefit from additional predictive power, resulting in adverse event and substance abuse avoidance, improved drug response, better patient outcomes, lower treatment costs, public health benefits, and increases in the effectiveness of research in pharmacology and other biomedical fields.

Claim (Index 19):
The method of  claim 16 , further comprising:\n comparing or having compared SNPs in the biological sample to the set of SNPs within the warfarin response pathway; and assigning scores to the SNPs in the biological sample that match with the set of SNPs within the warfarin response pathway; and combining the assigned scores to determine the dosage for administering to the patient.

Metadata:
- Claim Count in Document: 28.0
- Percentile: 99.0
- Lexical Diversity: 1.75532
- Patent Class: 340.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15977347', '12054072', '10229119', '11371511', '12484163']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6609125434411838
- 35 USC 102 Novelty (BERT): 0.5979949848267692
- Combined Prediction Score: 0.6546207875797424
- Mean Citation Score: 272.30126400000006
- Max Citation Score: 570.68585
- Similarity Product: 417.7630599861741

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