scholarly journals Earlier Intervention to Reduce Time to Receipt for Oral Anti-Cancer Drugs

2021 ◽  
Vol 43 (23) ◽  
pp. 31-31
Author(s):  
Catlin Nalley
Keyword(s):  
1993 ◽  
Vol 55 (1) ◽  
pp. 43-46
Author(s):  
Jun YOSHIDA ◽  
Juichiro NAKAYAMA ◽  
Nobuyuki SHIMIZU ◽  
Shonosuke NAGAE ◽  
Yoshiaki HORI

2019 ◽  
Vol 24 (32) ◽  
pp. 3829-3841 ◽  
Author(s):  
Lakshmanan Loganathan ◽  
Karthikeyan Muthusamy

Worldwide, colorectal cancer takes up the third position in commonly detected cancer and fourth in cancer mortality. Recent progress in molecular modeling studies has led to significant success in drug discovery using structure and ligand-based methods. This study highlights aspects of the anticancer drug design. The structure and ligand-based drug design are discussed to investigate the molecular and quantum mechanics in anti-cancer drugs. Recent advances in anticancer agent identification driven by structural and molecular insights are presented. As a result, the recent advances in the field and the current scenario in drug designing of cancer drugs are discussed. This review provides information on how cancer drugs were formulated and identified using computational power by the drug discovery society.


2020 ◽  
Vol 20 (9) ◽  
pp. 779-787
Author(s):  
Kajal Ghosal ◽  
Christian Agatemor ◽  
Richard I. Han ◽  
Amy T. Ku ◽  
Sabu Thomas ◽  
...  

Chemotherapy employs anti-cancer drugs to stop the growth of cancerous cells, but one common obstacle to the success is the development of chemoresistance, which leads to failure of the previously effective anti-cancer drugs. Resistance arises from different mechanistic pathways, and in this critical review, we focus on the Fanconi Anemia (FA) pathway in chemoresistance. This pathway has yet to be intensively researched by mainstream cancer researchers. This review aims to inspire a new thrust toward the contribution of the FA pathway to drug resistance in cancer. We believe an indepth understanding of this pathway will open new frontiers to effectively treat drug-resistant cancer.


2006 ◽  
Vol 1 (3) ◽  
pp. 327-346 ◽  
Author(s):  
Stephen Ralph ◽  
Pauline Low ◽  
Langfeng Dong ◽  
Alfons Lawen ◽  
Jiri Neuzil

2020 ◽  
Vol 20 (8) ◽  
pp. 1017-1027
Author(s):  
Abdul M. Baig ◽  
Zohaib Rana ◽  
Mohammad M. Mannan ◽  
Areeba Khaleeq ◽  
Fizza Nazim ◽  
...  

Background: Targeting evolutionarily conserved proteins in malignant cells and the adapter proteins involved in signalling that generates from such proteins may play a cardinal role in the selection of anti-cancer drugs. Drugs targeting these proteins could be of importance in developing anti-cancer drugs. Objectives: We inferred that drugs like loperamide and promethazine that act as antagonists of proteins conserved in cancer cells like voltage-gated Calcium channels (Cav), Calmodulin (CaM) and drug efflux (ABCB1) pump may have the potential to be re-purposed as an anti-cancer agent in Prostate Cancer (PCa). Methods: Growth and cytotoxic assays were performed by selecting loperamide and promethazine to target Cav, CaM and drug efflux (ABCB1) pumps to elucidate their effects on androgen-independent PC3 and DU145 PCa cell lines. Results: We show that loperamide and promethazine in doses of 80-100μg/ml exert oncocidal effects when tested in DU145 and PC3 cell lines. Diphenhydramine, which shares its targets with promethazine, except the CaM, failed to exhibit oncocidal effects. Conclusion: Anti-cancer effects can be of significance if structural analogues of loperamide and promethazine that specifically target Cav, CaM and ABCB1 drug efflux pumps can be synthesized, or these two drugs could be re-purposed after human trials in PCa.


2013 ◽  
Vol 14 (7) ◽  
pp. 963-974 ◽  
Author(s):  
Vincent Jamier ◽  
Wioleta Marut ◽  
Sergio Valente ◽  
Christiane Chereau ◽  
Sandrine Chouzenoux ◽  
...  

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Chris Bauer ◽  
Ralf Herwig ◽  
Matthias Lienhard ◽  
Paul Prasse ◽  
Tobias Scheffer ◽  
...  

Abstract Background There is a huge body of scientific literature describing the relation between tumor types and anti-cancer drugs. The vast amount of scientific literature makes it impossible for researchers and physicians to extract all relevant information manually. Methods In order to cope with the large amount of literature we applied an automated text mining approach to assess the relations between 30 most frequent cancer types and 270 anti-cancer drugs. We applied two different approaches, a classical text mining based on named entity recognition and an AI-based approach employing word embeddings. The consistency of literature mining results was validated with 3 independent methods: first, using data from FDA approvals, second, using experimentally measured IC-50 cell line data and third, using clinical patient survival data. Results We demonstrated that the automated text mining was able to successfully assess the relation between cancer types and anti-cancer drugs. All validation methods showed a good correspondence between the results from literature mining and independent confirmatory approaches. The relation between most frequent cancer types and drugs employed for their treatment were visualized in a large heatmap. All results are accessible in an interactive web-based knowledge base using the following link: https://knowledgebase.microdiscovery.de/heatmap. Conclusions Our approach is able to assess the relations between compounds and cancer types in an automated manner. Both, cancer types and compounds could be grouped into different clusters. Researchers can use the interactive knowledge base to inspect the presented results and follow their own research questions, for example the identification of novel indication areas for known drugs.


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