Virtual patients, digital twins and causal disease models: Paving the ground for in silico clinical trials.
Drug Discov Today
; 28(7): 103605, 2023 07.
Article
em En
| MEDLINE
| ID: mdl-37146963
ABSTRACT
Computational models are being explored to simulate in silico the efficacy and safety of drug candidates and medical devices. Disease models that are based on patients' profiling data are being produced to represent interactomes of genes or proteins and to infer causality in the pathophysiology, which makes it possible to mimic the impact of drugs on relevant targets. Virtual patients designed from medical records as well as digital twins are generated to simulate specific organs and to predict treatment efficacy at the individual patient level. As the acceptance of digital evidence by regulators grows, predictive artificial intelligence (AI)-based models will support the design of confirmatory trials in humans and will accelerate the development of efficient drugs and medical devices.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Simulação por Computador
/
Inteligência Artificial
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Drug Discov Today
Assunto da revista:
FARMACOLOGIA
/
TERAPIA POR MEDICAMENTOS
Ano de publicação:
2023
Tipo de documento:
Article