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1. WO2020138590 - DATA PROCESSING APPARATUS AND METHOD FOR PREDICTING EFFECTIVENESS AND SAFETY OF NEW DRUG CANDIDATE SUBSTANCES

Publication Number WO/2020/138590
Publication Date 02.07.2020
International Application No. PCT/KR2019/002920
International Filing Date 13.03.2019
IPC
G16C 20/50 2019.01
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
50Molecular design, e.g. of drugs
G16C 20/30 2019.01
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
30Prediction of properties of chemical compounds, compositions or mixtures
G16C 20/70 2019.01
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
70Machine learning, data mining or chemometrics
G16C 20/10 2019.01
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
10Analysis or design of chemical reactions, syntheses or processes
CPC
G16C 20/10
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
10Analysis or design of chemical reactions, syntheses or processes
G16C 20/30
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
30Prediction of properties of chemical compounds, compositions or mixtures
G16C 20/50
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
50Molecular design, e.g. of drugs
G16C 20/70
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
70Machine learning, data mining or chemometrics
Applicants
  • 주식회사 메디리타 MEDIRITA [KR]/[KR]
Inventors
  • 배영우 PAE, Young Woo
  • 진승현 JIN, Seung-Hyun
Agents
  • 강범주 KANG, Beom Ju
Priority Data
10-2018-016865824.12.2018KR
10-2019-002879013.03.2019KR
Publication Language Korean (KO)
Filing Language Korean (KO)
Designated States
Title
(EN) DATA PROCESSING APPARATUS AND METHOD FOR PREDICTING EFFECTIVENESS AND SAFETY OF NEW DRUG CANDIDATE SUBSTANCES
(FR) APPAREIL DE TRAITEMENT DE DONNÉES ET PROCÉDÉ DE PRÉVISION DE L'EFFICACITÉ ET DE LA SÉCURITÉ DE NOUVELLES SUBSTANCES MÉDICAMENTEUSES CANDIDATES
(KO) 신약 후보 물질의 효과 및 안전성 예측을 위한 데이터 처리 장치 및 방법
Abstract
(EN)
A data processing method for discovering new drug candidate substances in a data processing apparatus according to one embodiment of the present invention comprises the steps of: receiving a predetermined search word input through a user interface unit; extracting a plurality of druggable paths related to the predetermined search word and a druggable path (DP) index for each of the druggable paths by using an artificial neural network (ANN) model; selecting some druggable paths having high DP indexes, among the plurality of druggable paths; extracting absorption, distribution, metabolism, excretion, and toxicity (ADMET) information of the druggable paths by using an ADMET model; and outputting ADMET information and a DP index for each of the some druggable paths.
(FR)
Un mode de réalisation de La présente invention concerne un procédé de traitement de données pour découvrir de nouvelles substances médicamenteuses candidates dans un appareil de traitement de données qui comprend les étapes consistant à : recevoir une entrée de mot de recherche prédéterminée par l'intermédiaire d'une unité d'interface d'utilisateur ; extraire une pluralité de chemins potentiellement médicamenteux associés au mot de recherche prédéterminé et à un indice de chemin potentiellement médicamenteux (DP) pour chacun des chemins potentiellement médicamenteux à l'aide d'un réseau neuronal artificiel (RNA) ; sélectionner certains chemins potentiellement médicamenteux ayant des indices DP élevés, parmi la pluralité de chemins potentiellement médicamenteux ; extraire des informations d'absorption, de distribution, de métabolisme, d'excrétion et de toxicité (ADMET) des chemins potentiellement médicamenteux à l'aide d'un modèle ADMET ; et délivrer en sortie des informations ADMET et un indice DP pour chacun de certains chemins potentiellement médicamenteux.
(KO)
본 발명의 한 실시예에 따른 데이터 처리 장치의 신약 후보 물질 발굴을 위한 데이터 처리 방법은 사용자 인터페이스부를 통하여 소정의 검색어를 입력 받는 단계; 인공신경망(artificial neural network, ANN) 모델을 이용하여 상기 소정의 검색어와 관련된 복수의 약물 가능 경로 및 약물 가능 경로 별 DP(druggable path) 지수를 추출하는 단계; 상기 복수의 약물 가능 경로 중 상기 DP 지수가 높은 일부의 약물 가능 경로를 선택하는 단계; 상기 일부의 약물 가능 경로에 대하여 ADMET(absorption, distribution, metabolism, excretion, toxicity) 모델을 이용하여 ADMET 정보를 추출하는 단계; 그리고 상기 일부의 약물 가능 경로에 대하여 각 약물 가능 경로 별 DP 지수 및 ADMET 정보를 출력하는 단계를 포함한다.
Also published as
Latest bibliographic data on file with the International Bureau