New Techniques in Understanding Cancer Biology and Metabolism

Biswas, Dipsikha; Khan, M. Wajid

doi:10.1177/1533033820943248

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…A complexidade biológica do câncer, aliada à sua diversidade de tipos e subtipos, torna o diagnóstico e tratamento desafiadores. Embora as estratégias tradicionais, como cirurgia, quimioterapia e radioterapia, tenham mostrado eficácia em muitos casos, elas ainda enfrentam limitações substanciais, incluindo toxicidade sistêmica e resistência ao tratamento (Biswas & Khan;2020). Diante dessas limitações, a pesquisa tem se voltado para novas abordagens terapêuticas, como a imunoterapia, terapia-alvo e medicina de precisão.…”

Section: Introductionunclassified

Desafios E Avanços No Tratamento Do Câncer

Santos,

BENEVIDES,

FARAGE

et al. 2024

Anais Do III Congresso Brasileiro De Doenças Crônicas

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Section: Introductionunclassified

Desafios E Avanços No Tratamento Do Câncer

Santos,

BENEVIDES,

FARAGE

et al. 2024

Anais Do III Congresso Brasileiro De Doenças Crônicas

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“…In the previous years, oncology has observed a substantial advancement in understanding of the cancer biology 12,13 . With the advent of next generation sequencing (NGS) technology 14–18 such as single cell RNA 19–22 sequencing the ability to model explore the complex phenomenon such as cancer heterogeneity, viral cancers, drug resistance and etiologies have become easily accessible.…”

Section: Introductionmentioning

confidence: 99%

“…11 In the previous years, oncology has observed a substantial advancement in understanding of the cancer biology. 12,13 With the advent of next generation sequencing (NGS) technology [14][15][16][17][18] such as single cell RNA [19][20][21][22] sequencing the ability to model explore the complex phenomenon such as cancer heterogeneity, viral cancers, drug resistance and etiologies have become easily accessible. Additionally, the unprecedented progress in computational power 23 and computational strategies of machine learning (ML) 4,24,25 and deep learning (DL) [26][27][28][29][30] in combination with NGS single-cell RNA technologies have started to yield better results.…”

mentioning

confidence: 99%

Drug repurposing for viral cancers: A paradigm of machine learning, deep learning, and virtual screening‐based approaches

Ahmed

Kang

Kim

et al. 2023

Journal of Medical Virology

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Cancer management is major concern of health organizations and viral cancers account for approximately 15.4% of all known human cancers. Due to large number of patients, efficient treatments for viral cancers are needed. De novo drug discovery is time consuming and expensive process with high failure rate in clinical stages. To address this problem and provide treatments to patients suffering from viral cancers faster, drug repurposing emerges as an effective alternative which aims to find the other indications of the Food and Drug Administration approved drugs. Applied to viral cancers, drug repurposing studies following the niche have tried to find if already existing drugs could be used to treat viral cancers. Multiple drug repurposing approaches till date have been introduced with successful results in viral cancers and many drugs have been successfully repurposed various viral cancers.Here in this study, a critical review of viral cancer related databases, tools, and different machine learning, deep learning and virtual screening-based drug repurposing studies focusing on viral cancers is provided. Additionally, the mechanism of viral cancers is presented along with drug repurposing case study specific to each viral cancer. Finally, the limitations and challenges of various approaches along with possible solutions are provided.antihepatitis B virus antivirals, antiviral agents, artificial intelligence, drug repurposing, rational drug design | INTRODUCTIONDrug repurposing (also referred to as drug repositioning, drug reprofiling, drug redirecting, drug rescue and more 1 ) is a method for finding new indications beyond the scope of original indications of already approved drugs. 2 A conventional method of drug discovery is quite time taking and expensive task. Time required for a de novo drug is 12-17 years with an estimated expense of $2-$3 billion whereas the success rate is less than 10%. 3 This renders de novo drug discovery a risky process. Drug repurposing is an effective alternative to de novo drug discovery and offers many benefits such as reducing the time and money required to 5-7 years 4,5 and $200-$300 million, respectively, since much of the toxicity and efficacy information is already known. It also increases the success rate in clinical development and testing phases. 6 Success stories of drug repurposing have resulted in serendipity and by physicians' observation. 7 One such example is

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Cytogenetics to multiomics in biology of cancer

Gill,

Sobti

2024

Biomarkers in Cancer Detection and Monitoring of Therapeutics

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New Techniques in Understanding Cancer Biology and Metabolism

Cited by 4 publications

References 10 publications

Desafios E Avanços No Tratamento Do Câncer

Desafios E Avanços No Tratamento Do Câncer

Drug repurposing for viral cancers: A paradigm of machine learning, deep learning, and virtual screening‐based approaches

Cytogenetics to multiomics in biology of cancer

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