ACS Medicinal Chemistry Letters, Год журнала: 2025, Номер unknown
Опубликована: Май 9, 2025
Язык: Английский
Heliyon, Год журнала: 2023, Номер 9(7), С. e17575 - e17575
Опубликована: Июнь 26, 2023
The COVID-19 pandemic has emphasized the need for novel drug discovery process. However, journey from conceptualizing a to its eventual implementation in clinical settings is long, complex, and expensive process, with many potential points of failure. Over past decade, vast growth medical information coincided advances computational hardware (cloud computing, GPUs, TPUs) rise deep learning. Medical data generated large molecular screening profiles, personal health or pathology records, public organizations could benefit analysis by Artificial Intelligence (AI) approaches speed up prevent failures pipeline. We present applications AI at various stages pipelines, including inherently de novo design prediction drug's likely properties. Open-source databases AI-based software tools that facilitate are discussed along their associated problems molecule representation, collection, complexity, labeling, disparities among labels. How contemporary methods, such as graph neural networks, reinforcement learning, models, structure-based (i.e., dynamics simulations docking) can contribute responses also explored. Finally, recent developments investments start-up companies biotechnology, current progress, hopes promotions this article.
Язык: Английский
Процитировано
162
Progress in molecular biology and translational science, Год журнала: 2022, Номер unknown, С. 57 - 100
Опубликована: Янв. 1, 2022
Язык: Английский
Процитировано
95
Frontiers in Drug Discovery, Год журнала: 2023, Номер 3
Опубликована: Май 24, 2023
Finding new drugs usually consists of five main stages: 1) a pre-discovery stage in which basic research is performed to try understand the mechanisms leading diseases and propose possible targets (e.g., proteins); 2) drug discovery stage, during scientists search for molecules (two large families, small biologics) or other therapeutic strategies that interfere cure investigated disease at least alleviate symptoms; 3) preclinical development focuses on clarifying mode action candidates, investigates potential toxicity, validates efficacy various vitro vivo models, starts evaluate formulation; 4) clinical candidate humans; 5) reviewing, approval post-market monitoring approved not. In practice, finding treatments very challenging. Despite advances understanding biological systems cutting-edge technologies, process still long, costly with high attrition rate. New approaches, such as artificial intelligence novel are being used an attempt rationalize R&D bring patients faster, but several obstacles remain. Our hope one day, it becomes rapidly design inexpensive, more specific, effective, non-toxic, personalized drugs. This goal towards all authors this article have devoted most their careers.
Язык: Английский
Процитировано
86
Drug Discovery Today, Год журнала: 2023, Номер 28(7), С. 103605 - 103605
Опубликована: Май 3, 2023
Язык: Английский
Процитировано
45
Diagnostics, Год журнала: 2024, Номер 14(14), С. 1472 - 1472
Опубликована: Июль 9, 2024
With the improvement of economic conditions and increase in living standards, people's attention regard to health is also continuously increasing. They are beginning place their hopes on machines, expecting artificial intelligence (AI) provide a more humanized medical environment personalized services, thus greatly expanding supply bridging gap between resource demand. development IoT technology, arrival 5G 6G communication era, enhancement computing capabilities particular, application AI-assisted healthcare have been further promoted. Currently, research field assistance deepening expanding. AI holds immense value has many potential applications institutions, patients, professionals. It ability enhance efficiency, reduce costs, improve quality intelligent service experience for professionals patients. This study elaborates history timelines field, types technologies informatics, opportunities challenges medicine. The combination profound impact human life, improving levels life changing lifestyles.
Язык: Английский
Процитировано
28
Frontiers in Pharmacology, Год журнала: 2024, Номер 15
Опубликована: Фев. 23, 2024
Traditional Chinese medicine (TCM) is the practical experience and summary of nation for thousands years. It shows great potential in treating various chronic diseases, complex diseases major infectious has gradually attracted attention people all over world. However, due to complexity prescription action mechanism TCM, development TCM industry still a relatively conservative stage. With rise artificial intelligence technology fields, many scholars began apply traditional made remarkable progress. This paper comprehensively summarizes important role from aspects, including new drug discovery, data mining, quality standardization medicine. The limitations these applications are also emphasized, lack pharmacological research, database problems challenges brought by human-computer interaction. Nevertheless, opportunities innovations modernization Integrating into comprehensive application expected overcome faced further promote whole industry.
Язык: Английский
Процитировано
21
The Journal of Nutritional Biochemistry, Год журнала: 2022, Номер 114, С. 109250 - 109250
Опубликована: Дек. 9, 2022
Flavonoids are a major group of phytoestrogens associated with physiological effects, and ecological social impacts. Although the estrogenic activity flavonoids was reported by researchers in fields medical, environmental food studies, their molecular mechanisms action have not been comprehensively reviewed. The respective classes flavonoids, anthocyanidins/anthocyanins, 2-arylbenzofurans/3-arylcoumarins/α-methyldeoxybenzoins, aurones/chalcones/dihydrochalcones, coumaronochromones, coumestans, flavans/flavan-3-ols/flavan-4-ols, flavanones/dihydroflavonols, flavones/flavonols, homoisoflavonoids, isoflavans, isoflavanones, isoflavenes, isoflavones, neoflavonoids, oligoflavonoids, pterocarpans/pterocarpenes, rotenone/rotenoids, summarized through comprehensive literature search, structure-activity relationship, biological activities, signaling pathways, applications were discussed. contained at least one chemical mimicking estrogen, varied, such as those estrogenic, anti-estrogenic, non-estrogenic, biphasic additional activities crosstalk/bypassing, which exert cell pathways. Such mechanistic variations estrogen limited to observed among other broad categories chemicals, thus this chemicals can be termed "estrogenome". This review article focuses on connection mainly between outer inner environments, represent activities/signaling respectively, form basis understand applications. will markedly progress due emerging technologies, artificial intelligence for precision medicine, is also true study estrogenome including flavonoids.
Язык: Английский
Процитировано
50
Trends in Pharmacological Sciences, Год журнала: 2023, Номер 44(7), С. 411 - 424
Опубликована: Май 31, 2023
Artificial intelligence (AI)-based predictive models are being used to foster a precision medicine approach treat complex chronic diseases such as autoimmune and autoinflammatory disorders (AIIDs). In the past few years first of systemic lupus erythematosus (SLE), primary Sjögren syndrome (pSS), rheumatoid arthritis (RA) have been produced by molecular profiling patients using omic technologies integrating data with AI. These advances confirmed pathophysiology involving multiple proinflammatory pathways also provide evidence for shared dysregulation across different AIIDs. I discuss how stratify patients, assess causality in pathophysiology, design drug candidates silico, predict efficacy virtual patients. By relating individual patient characteristics predicted properties millions candidates, these can improve management AIIDs through more personalized treatments.
Язык: Английский
Процитировано
30
Signal Transduction and Targeted Therapy, Год журнала: 2025, Номер 10(1)
Опубликована: Март 10, 2025
Abstract The ability of small nucleic acids to modulate gene expression via a range processes has been widely explored. Compared with conventional treatments, acid therapeutics have the potential achieve long-lasting or even curative effects editing. As result recent technological advances, efficient delivery for therapeutic and biomedical applications achieved, accelerating their clinical translation. Here, we review increasing number classes most common chemical modifications platforms. We also discuss key advances in design, development application each platform. Furthermore, this presents comprehensive profiles currently approved drugs, including 11 antisense oligonucleotides (ASOs), 2 aptamers 6 siRNA summarizing modifications, disease-specific mechanisms action strategies. Other candidates whose trial status recorded updated are discussed. consider strategic issues such as important safety considerations, novel vectors hurdles translating academic breakthroughs clinic. Small produced favorable results trials address previously “undruggable” targets, suggesting that they could be useful guiding additional candidates.
Язык: Английский
Процитировано
1
Elsevier eBooks, Год журнала: 2024, Номер unknown, С. 417 - 454
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
7