System and method for algorithmic extracellular vesicle population discovery and characterization

Abstract

Methods and systems for extracellular vesicle characterization are provided herein. Embodiments of the methods include inputting measured physical, biological, or chemical aspects of extracted extracellular vesicles. Next, an information architecture that characterizes relationships between biological entities and diseases in humans or other vertebrates is generated. Then, relationships between the measured physical, biological, or chemical aspects of the isolated extracellular vesicles with the information architecture are automatically inferred, thereby characterizing extracellular vesicles.

What is claimed is: 
     
         1 . A method of recommending treatment for diseases, the method comprising:
 inputting measured physical, biological, or chemical aspects of extracted extracellular vesicles;   generating an information architecture that characterizes relationships between biological entities and diseases in humans or other vertebrates;   automatically inferring relationships between the measured physical, biological, or chemical aspects of the extracted extracellular vesicles with the information architecture and thereby characterizing the extracellular vesicles; and   providing recommendations for treatment of diseases based on the automatically inferred relationships.   
     
     
         2 . The method of  claim 1 , wherein the measured aspects of the extracellular vesicles comprise: vesicle size, vesicle density, vesicle lipid bilayer composition, extravesicular proteins or genetic material attached to the vesicles, extravesicular proteins or genetic material floating in surrounding biological sample, vesicle membrane proteins, intravesicular proteins, intravesicular genetic material, biochemical alterations of extravesicular or intravesicular genetic material, or any combinations thereof. 
     
     
         3 . The method of  claim 1 , wherein the information architecture stores relationships and attributes of biological entities or diseases as a relational database, a non-relational database, a graph database, lists of attributes in flat files, or any combination of such databases. 
     
     
         4 . The method of  claim 1 , wherein the relationships between biological entities, diseases, or attributes of the entities or diseases stored in the information architecture contain different values for different states. 
     
     
         5 . The method of  claim 1 , wherein the measured aspects of the extracellular vesicles are interpreted to have potential relationships amongst themselves. 
     
     
         6 . The method of  claim 1 , wherein relationships between measurement aspects of the extracellular vesicles are represented via a binary decision, thresholding, covariance, variance, distance metrics, or any combination thereof. 
     
     
         7 . The method of  claim 1 , further comprising comparing the relationships between measurement aspects of the extracellular vesicles, values of the measured aspects between extracellular vesicles, one or more lists of key measured aspects in extracellular vesicles, or any combinations thereof, with the relationships or attributes of biological entities or diseases stored in the information architecture. 
     
     
         8 . The method of  claim 1 , further comprising providing recommendations for diagnosis of diseases, potential biochemical compounds that may act as pharmaceutical agents, potential EV subpopulations to be used as targeted EV delivery vehicles, or any other clinical conditions for human or vertebrate healthcare. 
     
     
         9 . The method of  claim 1 , wherein providing recommendations includes quantifying a similarity measurement and determining whether the similarity measurement exceeds a predetermined threshold. 
     
     
         10 . The method of  claim 1 , wherein additional information linked to the origin of the biological sample, such as medical history, additional measurements from the biological sample, disease status or therapies administered, is incorporated to improve the accuracy of the recommendations. 
     
     
         11 . A system for recommending treatment for diseases, the system comprising:
 a processor device that:
 receives an input comprising measured physical, biological, or chemical aspects of extracellular vesicles extracted from a biological sample; 
 generates an information architecture that characterizes relationships between biological entities and diseases in humans or other vertebrates; 
 automatically infers relationships between the measured physical, biological, or chemical aspects of the extracted extracellular vesicles with the information architecture; and 
 provides recommendations for treatment of diseases based on the automatically inferred relationships. 
   
     
     
         12 . The system of  claim 11 , wherein the measured aspects of the extracellular vesicles comprise: vesicle size, vesicle density, vesicle lipid bilayer composition, extravesicular proteins or genetic material attached to the vesicles, extravesicular proteins or genetic material floating in surrounding biological sample, vesicle membrane proteins, intravesicular proteins, intravesicular genetic material, and biochemical alterations of any extravesicular or intravesicular genetic material, or any combinations thereof. 
     
     
         13 . The system of  claim 11 , wherein the information architecture stores relationships and attributes of biological entities or diseases as a relational database, a non-relational database, a graph database, lists of attributes in flat files, or any combination of such databases. 
     
     
         14 . The system of  claim 11 , wherein the relationships between biological entities, diseases, or attributes of the entities or diseases stored in the information architecture contain different values for different states. 
     
     
         15 . The system of  claim 11 , wherein the measured aspects of the extracellular vesicles are interpreted to have potential relationships amongst themselves. 
     
     
         16 . The system of  claim 11 , wherein relationships between measurement aspects of the extracellular vesicles are represented via a binary decision, thresholding, covariance, variance, distance metrics, or any combination thereof. 
     
     
         17 . The system of  claim 11 , further comprising comparing the relationships between measurement aspects of the extracellular vesicles, values of the measured aspects between extracellular vesicles, one or more lists of key measured aspects in extracellular vesicles, or any combinations thereof, with the relationships or attributes of biological entities or diseases stored in the information architecture. 
     
     
         18 . The system of  claim 11 , further comprising providing recommendations for diagnosis of diseases, potential biochemical compounds that may act as pharmaceutical agents, potential EV subpopulations to be used as targeted EV delivery vehicles, or any other clinical conditions for human or vertebrate healthcare. 
     
     
         19 . The system of  claim 11 , wherein providing recommendations includes quantifying a similarity measurement and determining whether the similarity measurement exceeds a predetermined threshold. 
     
     
         20 . The system of  claim 11 , wherein additional information linked to the origin of the biological sample, such as medical history, additional measurements from the biological sample, disease status or therapies administered, is incorporated to improve the accuracy of the recommendations.