WO2013141842A2 - Systèmes de gestion de médicaments fondés sur le génome - Google Patents

Systèmes de gestion de médicaments fondés sur le génome Download PDF

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Publication number
WO2013141842A2
WO2013141842A2 PCT/US2012/029704 US2012029704W WO2013141842A2 WO 2013141842 A2 WO2013141842 A2 WO 2013141842A2 US 2012029704 W US2012029704 W US 2012029704W WO 2013141842 A2 WO2013141842 A2 WO 2013141842A2
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WO
WIPO (PCT)
Prior art keywords
genome
drug
genetic
database
scanner
Prior art date
Application number
PCT/US2012/029704
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English (en)
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WO2013141842A3 (fr
Inventor
James Plante
David Becker
Original Assignee
Pathway Genomics
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Pathway Genomics filed Critical Pathway Genomics
Priority to PCT/US2012/029704 priority Critical patent/WO2013141842A2/fr
Priority to RU2012124154/10A priority patent/RU2012124154A/ru
Publication of WO2013141842A2 publication Critical patent/WO2013141842A2/fr
Publication of WO2013141842A3 publication Critical patent/WO2013141842A3/fr

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Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients

Definitions

  • the following invention disclosure is generally concerned with automated genome-based systems for management of drug use and specifically concerned with execution of computer implemented rules against stored genomic information for control h ng drug development, appi icati n and use .
  • the colon cancer drugs Erbitux and Vectibix do not work for the 40 percent of patients whose tumors have a particular genetic mutation.
  • the U.S. Food and Drug Administration FDA recently held a meeting to discuss whether patients should be tested to narrow use of the drugs, which cost $8,000 to $10,000 a month. This step, even if adopted and recommended as policy by the FDA would sti ll be executed manually by physicians - all but assuring a low adoption rate.
  • the required time for patient-doctor interaction to bring about such practice in a treatment plan is significant and the doctor case load is not amenable to such interaction. A doctor must give the best plan which can be dispensed in 15 minutes or less and move on to the next patient.
  • Warfarin® a blood thinner used by millions of Americans. Tens of thousands of them are hospitalized each year because of internal bleeding from an overdose or a blood clot from an inadequate dose. Presently, a doctor does not allocate enough time to check for a readily identifiable genetic marker which suggests that use of Warfarin® is too dangerous. As a result, patients are dying due to lack of an automated system which can take this step without further taxing a doctors time
  • Tamoxifen illustrates promise and current limitations of manual genetic testing. In 2003, more than 25 years after tamoxifen was introduced, researchers at Indiana
  • Tamoxifen now a generic drug, costs as little as $500 for the typical five-year treatment. But most patients in the United States are currently treated with a newer, much more expensive class of drugs, called aromatase inhibitors, that cost about $18,000 over five years. Those drugs performed better than tamoxifen in clinical trials before the role of 2D6 was generally understood. If only women with acti ve 2D6 had been assessed, tamoxifen might have worked as well or better than the newer drugs. But as it was overly cumbersome for doctors to manage such appli cati on of the drug i n view of each patient's genomic data, we only have information as to the effectiveness of Tamoxifen with regard to the general public without consideration of genetic variation.
  • Jt is a further object to provide an automated system which couples with physician's office, pharmacy and drug manufacturers systems to improve management of drugs in their use and development.
  • a 'personal genome' is m expression, either complete or a portion thereof of a any particular person's DNA.
  • Fig. 1 is a general. block di agram of one exam ple version of these genome based drug use management systems 1.
  • the general public may participate as system members by voluntarily submitting a DNA sample 2 for processing at a genome scanner 3.
  • DNA is received at a receiving port, 4 where it is subject to chemical and electro-optical processes to read genetic sequence features of the DNA including genes, alleles, polymorphisms, "copy number" instances, et cetera.
  • the output of the genome scanner is a digital representation of a person's genome. While in some cases this may not be a complete genome sequence, modern systems are configured to readily read 10 million features in a single inexpensive process and therefore a system member may have her genome expressed by millions of genome subset sequences.
  • the output of the genome scanner is carefully coupled to a membership database
  • a database is prepared with a structure and architecture which supports storing a great plurality of unique member genomes and means for identifying those with respect to a member to whom they belong. Accordingly, database schema are prepared to enforce a. one-to-one relationship between a member and a digital representation of a genome received from the genome scanner by way of a unique identifier index.
  • the database may further store data related to a member such as contact and address information, medical history * ; lifestyle classifications, family history, et cetera, in some versions, most important address information includes an e-mail address which enables special functionality disclosed hereafter, it should be appreciated however that in all cases the membership database structure Is arranged to firmly couple a single genome to a single member and maintain an association therebetween. In this manner, drug use functionality described herein is directed to the appropriate persons.
  • an analysis module 6 of these genome based drug use management systems also coupled to the membership database.
  • An analysis module comprising primarily of a rules library 7 and a query engine 8, and a result processor 9, forms the essential backbone of the system.
  • the rules library' accommodates stored logic which forms rules and analysis algorithms related to drug therapies and other drug use programs and issues. These rules and analysis algorithms may be prepared in advance view of system objectives and further may be subject to updates and frequent tuning. They ma be updated and adjusted from time-to-time and the library' is suitable for accommodating additional mles as they might be developed in vi ew of new research. Rul es may be formed such tha t they are dependent upon genetic features which may be found in a human genome. In a most simple example a rule might be formed to consider the presence of a particular single nucleotide polymorphism (SN ' P) in a genome.
  • SN ' P single nucleotide polymorphism
  • a drug use program may depend upon indicators found in a person's genome, the presence or absence of a certain known SNP may be used to modify a drug use therapy.
  • More advanced compound rules may depend upon several distinct features of a genome. For example, a particular rule may be configured to perform a Boolean logic operation on two or more features of a digital genome representation to find the presence of a particular SNP and its copy number (number of instances).
  • Various rules can be written and embodied as stored code in a rules library to accommodate infinite possibilities of features which may be found in a genome.
  • a compound rule may be additionally devi sed to depend upon those data as well .
  • a database schema includes structure to accommodate discrete family history data and discrete lifestyle dat for example, in a fashion whereby it may be sorted, indexed, and searched electronically. Rule written against this data are to further view of genetic data drive additional dru use plans.
  • Rules stored in the rules library form the basis upon which a query engine may interrogate the member's database.
  • the query engine manages formation of computer executable queries 10 in agreement with a database procedure and function such that, these queries may be run periodically against data stored in the database to produce results output 11 , Results output may include subsets of data stored in the membership database. For example, a rule devised to select all members having genetic
  • predisposition to Celiac disease may form basis tor a SQL 'select' query such as.
  • the query engine may run the query against the membership database to identify members having a predisposition to the disease.
  • a query may be run once, run periodically on a recurring schedule or be programmed to run on demand.
  • the query engine supports special events such as a 'new member' event.
  • a 'new member' event When a new member joins, it is useful to run an entire collection of queries on that new member genome. Accordingly, the query engine is arranged to run specialized query sets in response to a. new member being added to the database.
  • a result set is produced and conveyed to a result process module.
  • the results set is comprised of all the "hits" or members having data in agreement with the particular rule being tested.
  • the result process module produces a response appropnaie for circumstances defined in the rule - and it may do this specifically for each member found to have the genetic characteristic defined in the rule; and the response may be different for each in view of particulars stored as a user profile.
  • the result process module may produce a therapy plan e.g. for persons having a genome which suggests predisposition to a particular disease.
  • a drug use prescription or therap plan may be provided. This may include combinations of drugs which might better serve the particular features of the genetic profile in question.
  • a drug therapy plan output of these systems may be transmitted to a physician's office for further review and consideration in view of the normal course of a physician's practice.
  • a result process module may receive a result set response from execution of a query to receive a group of members who would benefit from a specific drug
  • Alzheimer's disease mitigation including use of Cholinesterase inhibitor drugs: donepezil (Aricept), gaiantamine (Ra adyrte) or rivastigmine (Exeione).
  • a report may be provided with names and addresses of persons having an increased predisposition to some disease without yet showing any symptoms.
  • the report can be passed to a marketing services company who might provide
  • a report output in response to identifying members of a group who might benefit, from a drug may be sent to a drug manufacturer so that they may better configure the drag packagi ng, marketing, and advertising campaigns they might use to promote use of the drug.
  • a result process module may receive a result set and prepare a reference report of studies collections of studies and drug use statistical date for example for a member's review. Members interested in further education about drugs they currently use may receive reports which might be newly updated from time- to- time in accordance with this version of the invention. Accordingly, after execution of a query on the member's database, an object server may provide a package of research studies to those to whom the information is most relevant.
  • An object server is arranged to prepare and del iver various types of electronic communications 'objects' which carry a payload of genetic information while additionally including the overhead of a cooperating target machine or computing system.
  • an object server may prepare a response as a 'COM object' which might be consumed on a desktop application for exam le a Windows operating system based application.
  • a 'WebObject' might be arranged as an XML package consumable on a general-purpose Web browser system.
  • some versions of these systems may embody drug use reports and information as POJO or "plain old Java objects" which interface with and are readily consumed by Java-enabled computer systems.
  • a report may be wrapped in an 'e-mail' overhead and transmitted to an e-mail client e.g. 'Outlook' of an interested party
  • drag use output reports may be configured by the object server as an SMS message and routed by telephone number to an intended recipient.
  • An object server may be arranged to deli ver drug use information via 140 character 'tweet' messages compatible with the Twitter platform and paradigm.
  • an object server may prepare drug use information as a Flash type computer file including high functionality ActionScript to be run on a FlashPlayer enabled computing platform. In this way, an object server is well coupled via various farms of electronics medications to many recipient targets.
  • An object, server 12 is provided as part of the original computing system, to receive information, for example a therapy plan; a drug prescription; or drag conflict definition; etc., from the result processor and configure the information using an OOP model as an. "object" and presenting the State thereof in accordance with the output of the result processor.
  • the object server then transmits the object to a cooperating computin system for example those which may be deployed in a pharmacy 13, physician's office 14, drug manufacturers research laboratories 15, where the object may be consumed in a manner to advance a drug use strategy, in this way, these automated drug use systems are suitable for communication and interface with various computing platforms and purposes.
  • a pharmacy equipped with a highly advanced drug conflict system further benefits from receipt of information as it relates to particular patient's genome. That is, today pharmacies deploy automated computer systems to check a particular patient's drug use and determine if simultaneous use of two separate drugs present any conflicts. However these systems and do nothing to consider a patient's genetic composition when performing a drug conflict check.
  • an enabled pharmacy would request informati n on a certain patient and received a drug use conflict report based upon genetic information wi hout receiving the patient's highly confidential genome data.
  • the result processor developed a drug conflict definition and that i passed by the object server to proprietary software running on pharmacy computers.
  • these systems may he coupled to software used by physicians in the positions office 14.
  • a computing system 15 prepared with a priori knowledge of a certain interface 16 is well coupled to receive from the object server a therapy pla object.
  • Independent software at a doctor's private office then uses the object which is based upon, but may not include a complete genetic disclosure.
  • Physicians running appropriate computi ng software can be advised of drug therapy plans devised in view of the patient's genome - freeing the doctor from becoming a drug geneticist while having continuous access to updates by way of the ever-changing rules library.
  • drug manufacturers can receive dr g performance data compiled in view of common features present in drug users genome. Datg performance studies can more precisely target problems, issues, unexpected benefits, etc. when they include computing systems prepared with an interface to receive information by an object server specifically designed to provide genetics related drug performance data to drug manufacturers. Further, drug manufacturers are in a. position, to provide feedback 22 which might be used to further adjust and tune the rules library. Esther new rules or modifications to existing rules improve the overall system as future queries will produce a more accurate result sets when based upon improved definitions in the rules library.
  • a society of persons in the same genetic class might be ideal for directing marketing campaigns to more accurately inform people of the existence of drugs which could benefit them.
  • a society object may be comprised of a list, of potential drug beneficiaries and their appropriate contact information so that drug marketing campaigns can be devised to most effectively address these persons with the prescribed genetic feature.

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  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Medicinal Chemistry (AREA)
  • Epidemiology (AREA)
  • Chemical & Material Sciences (AREA)
  • Medical Informatics (AREA)
  • Primary Health Care (AREA)
  • Public Health (AREA)
  • Medical Treatment And Welfare Office Work (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Apparatus Associated With Microorganisms And Enzymes (AREA)

Abstract

Selon l'invention, un système de gestion de médicaments fondé sur des données génomiques de membres est couplé à des systèmes informatiques externes associés, par l'intermédiaire d'un serveur d'objets qui prépare des rapports sur l'utilisation de médicaments en vue d'une distribution automatique, en réponse aux résultats produits par ces données à partir de la base de données des membres. Sur la base de règles stockées dans une bibliothèque de règles, un moteur d'interrogation exécute des tests sur les informations génétiques des membres stockées, en vue d'identifier et de satisfaire des critères spécifiques.
PCT/US2012/029704 2012-03-19 2012-03-19 Systèmes de gestion de médicaments fondés sur le génome WO2013141842A2 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
PCT/US2012/029704 WO2013141842A2 (fr) 2012-03-19 2012-03-19 Systèmes de gestion de médicaments fondés sur le génome
RU2012124154/10A RU2012124154A (ru) 2012-03-19 2012-03-19 Системы на основе генома для управления медикаментозными средствами

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PCT/US2012/029704 WO2013141842A2 (fr) 2012-03-19 2012-03-19 Systèmes de gestion de médicaments fondés sur le génome

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2015130954A1 (fr) * 2014-02-26 2015-09-03 Nantomics, Llc Dispositif mobile sécurisé de navigation du génome et procédés associés

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7062076B1 (en) * 1999-08-27 2006-06-13 Iris Biotechnologies, Inc. Artificial intelligence system for genetic analysis
US20100286994A1 (en) * 2008-11-10 2010-11-11 Signature Genomic Labs Interactive Genome Browser
US20110153356A1 (en) * 2008-09-10 2011-06-23 Expanse Networks, Inc. System, Method and Software for Healthcare Selection Based on Pangenetic Data
US20110251243A1 (en) * 2005-09-09 2011-10-13 Mark Rupert Tucker Method and Kit for Assessing a Patient's Genetic Information, Lifestyle and Environment Conditions, and Providing a Tailored Therapeutic Regime
US20120066001A1 (en) * 2010-05-25 2012-03-15 John Zachary Sanborn Bambam: Parallel comparative analysis of high-throughput sequencing data

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7062076B1 (en) * 1999-08-27 2006-06-13 Iris Biotechnologies, Inc. Artificial intelligence system for genetic analysis
US20110251243A1 (en) * 2005-09-09 2011-10-13 Mark Rupert Tucker Method and Kit for Assessing a Patient's Genetic Information, Lifestyle and Environment Conditions, and Providing a Tailored Therapeutic Regime
US20110153356A1 (en) * 2008-09-10 2011-06-23 Expanse Networks, Inc. System, Method and Software for Healthcare Selection Based on Pangenetic Data
US20100286994A1 (en) * 2008-11-10 2010-11-11 Signature Genomic Labs Interactive Genome Browser
US20120066001A1 (en) * 2010-05-25 2012-03-15 John Zachary Sanborn Bambam: Parallel comparative analysis of high-throughput sequencing data

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2015130954A1 (fr) * 2014-02-26 2015-09-03 Nantomics, Llc Dispositif mobile sécurisé de navigation du génome et procédés associés

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WO2013141842A3 (fr) 2014-05-01
RU2012124154A (ru) 2015-04-10

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