PATENT CLAIM ANALYSIS

Application Number: 16197260
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2019-05
Patent Classification: ["703", "011000"]

Abstract:
A method for predicting drug concentration levels includes receiving at least one subject characteristic of the subject, and executing a full body circulation model by: determining a first concentration of the drug in a first blood flow entering a first organ determining a second concentration of the drug in the first organ, determining a third concentration of a drug in a third blood flow entering a second organ, the third blood flow downstream of the first organ, and determining, using the second organ model a fourth concentration of the drug in the second organ.

Claim (Index 10):
A method for predicting drug concentration levels as a function of time in one or more organs of a subject, comprising:\n receiving at least one subject characteristic of the subject; receiving at least one drug characteristic of a drug to be administered to the subject; executing a full body circulation engine using the at least one subject characteristic to determine a plurality of blood flow rates to the one or more organs of the subject; determining a first concentration of the drug in a first blood flow entering a first organ based on an initial drug dosage and the blood flow rate to the first organ; modifying a first drug concentration prediction model of the first organ using the at least one subject characteristic; determining a second concentration of the drug in the first organ using the modified first drug concentration prediction model; determining a third concentration of the drug in a second blood flow entering a second organ downstream of the first organ based on the second concentration and the blood flow rate to the second organ; modifying a second drug concentration prediction model of the second organ using the at least one subject characteristic; and determining a fourth concentration of the drug in the second organ using the modified second drug concentration prediction model.

Metadata:
- Claim Count in Document: 38.0
- Percentile: 98.0
- Lexical Diversity: 2.58974
- Patent Class: 703.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15933854', '14112311', '09937146', '16104391', '15977347']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2340329419435572
- 35 USC 102 Novelty (BERT): 0.4958338328048166
- Combined Prediction Score: 0.2602130310296832
- Mean Citation Score: 171.755744
- Max Citation Score: 184.44684
- Similarity Product: 116.00447585297584

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

Dataset: test