Evolving Artificial Intelligence (AI) at the Crossroads: Potentiating Productive vs. Declining Disruptive Cancer Research DOI Open Access
Nilesh Kumar Sharma, Sachin C. Sarode

Cancers, Год журнала: 2024, Номер 16(21), С. 3646 - 3646

Опубликована: Окт. 29, 2024

Artificial intelligence (AI), encompassing several tools and platforms such as artificial “general” (AGI) generative (GenAI), has facilitated cancer research, enhancing productivity in terms of research publications translational value for patients. AGI tools, ChatGPT, assist preclinical clinical scientists identifying tumor heterogeneity, predicting therapy outcomes, streamlining publications. However, this perspective review also explores the potential AI’s influence on with regard to its impact disruptive sciences discoveries by scientists. The increasing reliance AI may compromise biological intelligence, disrupting abstraction, creativity, critical thinking. This could contribute declining trend sciences, hindering landmark innovations. narrates role different forms potentiation productive disruption due influence.

Язык: Английский

Bridging machine learning and peptide design for cancer treatment: a comprehensive review DOI Creative Commons
Khosro Rezaee, Hossein Eslami

Artificial Intelligence Review, Год журнала: 2025, Номер 58(5)

Опубликована: Март 5, 2025

Язык: Английский

Процитировано

1
DTLCDR: A target-based multimodal fusion deep learning framework for cancer drug response prediction DOI Creative Commons
Jie Yu, Cheng Shi, Yiran Zhou

и другие.

Journal of Pharmaceutical Analysis, Год журнала: 2025, Номер unknown, С. 101315 - 101315

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0
Artificial intelligence revolution in drug discovery: A paradigm shift in pharmaceutical innovation DOI Creative Commons
Somayah J. Jarallah, Fahad A. Almughem,

Nada K. Alhumaid

и другие.

International Journal of Pharmaceutics, Год журнала: 2025, Номер unknown, С. 125789 - 125789

Опубликована: Май 1, 2025

Integrating artificial intelligence (AI) into drug discovery has revolutionized pharmaceutical innovation, addressing the challenges of traditional methods that are costly, time-consuming, and suffer from high failure rates. By utilizing machine learning (ML), deep (DL), natural language processing (NLP), AI enhances various stages development, including target identification, lead optimization, de novo design, repurposing. tools, such as AlphaFold for protein structure prediction AtomNet structure-based have significantly accelerated process, improved efficiency reduced costs. Success stories like Insilico Medicine's AI-designed molecule idiopathic pulmonary fibrosis BenevolentAI's identification baricitinib COVID-19 highlight AI's transformative potential. Additionally, enables exploration vast chemical spaces, optimization clinical trials, novel therapeutic targets, paving way precision medicine. However, limited data accessibility, integration diverse datasets, interpretability models, ethical concerns remain critical hurdles. Overcoming these limitations through enhanced algorithms, standardized databases, interdisciplinary collaboration is essential. Overall, continues to reshape discovery, reducing timelines, increasing success rates, driving development innovative accessible therapies unmet medical needs.

Язык: Английский

Процитировано

0
Unlocking therapeutic frontiers: harnessing artificial intelligence in drug discovery for neurodegenerative diseases DOI
Bilal Nehmeh, Joseph Rebehmed,

Riham Nehmeh

и другие.

Drug Discovery Today, Год журнала: 2024, Номер 29(12), С. 104216 - 104216

Опубликована: Окт. 18, 2024

Язык: Английский

Процитировано

0
Evolving Artificial Intelligence (AI) at the Crossroads: Potentiating Productive vs. Declining Disruptive Cancer Research DOI Open Access
Nilesh Kumar Sharma, Sachin C. Sarode

Cancers, Год журнала: 2024, Номер 16(21), С. 3646 - 3646

Опубликована: Окт. 29, 2024

Artificial intelligence (AI), encompassing several tools and platforms such as artificial “general” (AGI) generative (GenAI), has facilitated cancer research, enhancing productivity in terms of research publications translational value for patients. AGI tools, ChatGPT, assist preclinical clinical scientists identifying tumor heterogeneity, predicting therapy outcomes, streamlining publications. However, this perspective review also explores the potential AI’s influence on with regard to its impact disruptive sciences discoveries by scientists. The increasing reliance AI may compromise biological intelligence, disrupting abstraction, creativity, critical thinking. This could contribute declining trend sciences, hindering landmark innovations. narrates role different forms potentiation productive disruption due influence.

Язык: Английский

Процитировано

0