Literature DB >> 23373702

How can attrition rates be reduced in cancer drug discovery?

Lucas Moreno, Andrew D J Pearson.   

Abstract

Attrition is a major issue in anticancer drug development with up to 95% of drugs tested in Phase I trials not reaching a marketing authorisation making the drug development process enormously costly and inefficient. It is essential that this problem is addressed throughout the whole drug development process to improve efficiency which will ultimately result in increased patient benefit with more profitable drugs. The approach to reduce cancer drug attrition rates must be based on three pillars. The first of these is that there is a need for new pre-clinical models which can act as better predictors of success in clinical trials. Furthermore, clinical trials driven by tumour biology with the incorporation of predictive and pharmacodynamic biomarkers would be beneficial in drug development. Finally, there is a need for increased collaboration to combine the unique strengths between industry, academia and regulators to ensure that the needs of all stakeholders are met.

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Year:  2013        PMID: 23373702     DOI: 10.1517/17460441.2013.768984

Source DB:  PubMed          Journal:  Expert Opin Drug Discov        ISSN: 1746-0441            Impact factor:   6.098


  37 in total

Review 1.  Cancer drug development: The missing links.

Authors:  Ajaikumar B Kunnumakkara; Devivasha Bordoloi; Bethsebie Lalduhsaki Sailo; Nand Kishor Roy; Krishan Kumar Thakur; Kishore Banik; Mehdi Shakibaei; Subash C Gupta; Bharat B Aggarwal
Journal:  Exp Biol Med (Maywood)       Date:  2019-04-08

Review 2.  A Pathway to Personalizing Therapy for Metastases Using Liver-on-a-Chip Platforms.

Authors:  A S Khazali; A M Clark; A Wells
Journal:  Stem Cell Rev Rep       Date:  2017-06       Impact factor: 5.739

3.  Physiologically-Based Pharmacokinetic/Pharmacodynamic Model of MBQ-167 to Predict Tumor Growth Inhibition in Mice.

Authors:  Javier Reig-López; María Del Mar Maldonado; Matilde Merino-Sanjuan; Ailed M Cruz-Collazo; Jean F Ruiz-Calderón; Victor Mangas-Sanjuán; Suranganie Dharmawardhane; Jorge Duconge
Journal:  Pharmaceutics       Date:  2020-10-15       Impact factor: 6.321

4.  Real-time cytotoxicity assays in human whole blood.

Authors:  Ching-Wen Hsiao; Yen-Ting Lo; Hong Liu; Sonny C Hsiao
Journal:  J Vis Exp       Date:  2014-11-07       Impact factor: 1.355

5.  Inventing new therapies without reinventing the wheel: the power of drug repurposing.

Authors:  Andreas Papapetropoulos; Csaba Szabo
Journal:  Br J Pharmacol       Date:  2018-01       Impact factor: 8.739

6.  Metastasis-Specific Gene Expression in Autochthonous and Allograft Mouse Mammary Tumor Models: Stratification and Identification of Targetable Signatures.

Authors:  Christina Ross; Karol Szczepanek; Maxwell Lee; Howard Yang; Cody J Peer; Jessica Kindrick; Priya Shankarappa; Zhi-Wei Lin; Jack D Sanford; William D Figg; Kent W Hunter
Journal:  Mol Cancer Res       Date:  2020-06-08       Impact factor: 5.852

Review 7.  Tackling Crizotinib Resistance: The Pathway from Drug Discovery to the Pediatric Clinic.

Authors:  Elizabeth R Tucker; Laura S Danielson; Paolo Innocenti; Louis Chesler
Journal:  Cancer Res       Date:  2015-06-29       Impact factor: 12.701

8.  Characterization of a murine model of metastatic human non-small cell lung cancer and effect of CXCR4 inhibition on the growth of metastases.

Authors:  Arvind K Singla; Charlene M Downey; Gwyn D Bebb; Frank R Jirik
Journal:  Oncoscience       Date:  2015-02-09

9.  Two preclinical tests to evaluate anticancer activity and to help validate drug candidates for clinical trials.

Authors:  Miguel López-Lázaro
Journal:  Oncoscience       Date:  2015-02-20

Review 10.  Predictive biomarkers in precision medicine and drug development against lung cancer.

Authors:  Bingliang Fang; Reza J Mehran; John V Heymach; Stephen G Swisher
Journal:  Chin J Cancer       Date:  2015-07-02
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