PATENT CLAIM ANALYSIS

Application Number: 15977347
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-11
Patent Classification: ["340", "539120"]

Abstract:
For patients who exhibit or may exhibit primary or comorbid disease, pharmacological phenotypes may be predicted through the collection of panomic, physiomic, environmental, sociomic, demographic, and outcome phenotype 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 4):
The method of  claim 1 , wherein the one or more pharmacological phenotypes includes a predicted response by the second patient to one or more drugs and further comprising:\n receiving, at the one or more processors, an indication of a type of disease diagnosed for the second patient; applying, by the one or more processors, the panomic data and the sociomic and environmental data for the second patient to the statistical model to determine the predicted response by the second patient to a plurality of drugs for treating the type of disease diagnosed for the second patient; identifying, the one or more processors, one of the plurality of drugs to treat the second patient with based on the predicted response for each of the plurality of prescriptions drugs; and providing, by the one or more processors, an indication of the identified drug to the health care provider for prescribing an optimal course of treatment for the type of disease diagnosed for the second patient.

Metadata:
- Claim Count in Document: 5.0
- Percentile: 93.0
- Lexical Diversity: 1.77
- Patent Class: 340.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['10229119', '11371511', '12031327', '13316144', '12484163']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6470144262965842
- 35 USC 102 Novelty (BERT): 0.4961605712147158
- Combined Prediction Score: 0.6319290407883974
- Mean Citation Score: 200.690944
- Max Citation Score: 222.30406
- Similarity Product: 162.07690555343154

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