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 16):
A computing device for identifying pharmacological phenotypes using statistical modeling and machine learning techniques, the computing device comprising:\n a communication network, one or more processors; and a non-transitory computer-readable memory coupled to the one or more processors and storing thereon instructions that, when executed by the one or more processors, cause the computing device to:\n obtain a set of training data including for each of a plurality of first patients:\n panomic data indicative of biological characteristics of the first patient, \n sociomic and environmental data indicative of experiences of the first patient collected over time, and \n phenomic data indicative of at least one of: a response to one or more drugs, whether the first patient experiences substance abuse, or one or more chronic diseases of the first patient; \n \n generate a statistical model for determining pharmacological phenotypes s based on the set of training data; \n receive a set of panomic data, and sociomic and environmental data for a second patient collected over a period of time; \n apply the panomic data and the sociomic and environmental data for the second patient to the statistical model to determine one or more pharmacological phenotypes for the second patient; and \n provide, via the communication network, the one or more pharmacological phenotypes for the second patient for display to a health care provider, wherein the health care provider recommends a course of treatment to the second patient according to the pharmacological phenotypes.

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): 0.6440982487549544
- 35 USC 102 Novelty (BERT): 0.5094343574599559
- Combined Prediction Score: 0.6306318596254545
- Mean Citation Score: 200.690944
- Max Citation Score: 222.30406
- Similarity Product: 136.68689421456813

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