Machine Learning in Drug Discovery and Development Part 1: A Primer
- Autores
- Talevi, Alan; Morales, Juan Francisco; Hather, Gregory; Podichetty, Jagdeep T.; Kim, Sarah; Bloomingdale, Peter C.; Kim, Samuel; Burton, Jackson; Brown, Joshua D.; Winterstein, Almut G.; Schmidt, Stephan; White, Jensen Kael; Conrado, Daniela J.
- Año de publicación
- 2020
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and development. We also list possible data sources, describe good practices for ML model development and validation, and share a reproducible example. A companion article will summarize applications of ML in drug discovery, drug development, and postapproval phase.
Laboratorio de Investigación y Desarrollo de Bioactivos - Materia
-
Química
Machine learning
Algorithms
Drug development
Tutorial - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc/4.0/
- Repositorio
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/119195
Ver los metadatos del registro completo
| id |
SEDICI_4569ee1b77f10dee863e6f2c8edafbf5 |
|---|---|
| oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/119195 |
| network_acronym_str |
SEDICI |
| repository_id_str |
1329 |
| network_name_str |
SEDICI (UNLP) |
| spelling |
Machine Learning in Drug Discovery and Development Part 1: A PrimerTalevi, AlanMorales, Juan FranciscoHather, GregoryPodichetty, Jagdeep T.Kim, SarahBloomingdale, Peter C.Kim, SamuelBurton, JacksonBrown, Joshua D.Winterstein, Almut G.Schmidt, StephanWhite, Jensen KaelConrado, Daniela J.QuímicaMachine learningAlgorithmsDrug developmentTutorialArtificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and development. We also list possible data sources, describe good practices for ML model development and validation, and share a reproducible example. A companion article will summarize applications of ML in drug discovery, drug development, and postapproval phase.Laboratorio de Investigación y Desarrollo de Bioactivos2020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf129-142http://sedici.unlp.edu.ar/handle/10915/119195enginfo:eu-repo/semantics/altIdentifier/issn/2163-8306info:eu-repo/semantics/altIdentifier/doi/10.1002/psp4.12491info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/4.0/Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T17:09:00Zoai:sedici.unlp.edu.ar:10915/119195Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 17:09:01.084SEDICI (UNLP) - Universidad Nacional de La Platafalse |
| dc.title.none.fl_str_mv |
Machine Learning in Drug Discovery and Development Part 1: A Primer |
| title |
Machine Learning in Drug Discovery and Development Part 1: A Primer |
| spellingShingle |
Machine Learning in Drug Discovery and Development Part 1: A Primer Talevi, Alan Química Machine learning Algorithms Drug development Tutorial |
| title_short |
Machine Learning in Drug Discovery and Development Part 1: A Primer |
| title_full |
Machine Learning in Drug Discovery and Development Part 1: A Primer |
| title_fullStr |
Machine Learning in Drug Discovery and Development Part 1: A Primer |
| title_full_unstemmed |
Machine Learning in Drug Discovery and Development Part 1: A Primer |
| title_sort |
Machine Learning in Drug Discovery and Development Part 1: A Primer |
| dc.creator.none.fl_str_mv |
Talevi, Alan Morales, Juan Francisco Hather, Gregory Podichetty, Jagdeep T. Kim, Sarah Bloomingdale, Peter C. Kim, Samuel Burton, Jackson Brown, Joshua D. Winterstein, Almut G. Schmidt, Stephan White, Jensen Kael Conrado, Daniela J. |
| author |
Talevi, Alan |
| author_facet |
Talevi, Alan Morales, Juan Francisco Hather, Gregory Podichetty, Jagdeep T. Kim, Sarah Bloomingdale, Peter C. Kim, Samuel Burton, Jackson Brown, Joshua D. Winterstein, Almut G. Schmidt, Stephan White, Jensen Kael Conrado, Daniela J. |
| author_role |
author |
| author2 |
Morales, Juan Francisco Hather, Gregory Podichetty, Jagdeep T. Kim, Sarah Bloomingdale, Peter C. Kim, Samuel Burton, Jackson Brown, Joshua D. Winterstein, Almut G. Schmidt, Stephan White, Jensen Kael Conrado, Daniela J. |
| author2_role |
author author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
Química Machine learning Algorithms Drug development Tutorial |
| topic |
Química Machine learning Algorithms Drug development Tutorial |
| dc.description.none.fl_txt_mv |
Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and development. We also list possible data sources, describe good practices for ML model development and validation, and share a reproducible example. A companion article will summarize applications of ML in drug discovery, drug development, and postapproval phase. Laboratorio de Investigación y Desarrollo de Bioactivos |
| description |
Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and development. We also list possible data sources, describe good practices for ML model development and validation, and share a reproducible example. A companion article will summarize applications of ML in drug discovery, drug development, and postapproval phase. |
| publishDate |
2020 |
| dc.date.none.fl_str_mv |
2020 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Articulo http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/119195 |
| url |
http://sedici.unlp.edu.ar/handle/10915/119195 |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/issn/2163-8306 info:eu-repo/semantics/altIdentifier/doi/10.1002/psp4.12491 |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) |
| eu_rights_str_mv |
openAccess |
| rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) |
| dc.format.none.fl_str_mv |
application/pdf 129-142 |
| dc.source.none.fl_str_mv |
reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
| reponame_str |
SEDICI (UNLP) |
| collection |
SEDICI (UNLP) |
| instname_str |
Universidad Nacional de La Plata |
| instacron_str |
UNLP |
| institution |
UNLP |
| repository.name.fl_str_mv |
SEDICI (UNLP) - Universidad Nacional de La Plata |
| repository.mail.fl_str_mv |
alira@sedici.unlp.edu.ar |
| _version_ |
1846783412094894080 |
| score |
12.982451 |