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Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo

Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo

Published on: February 6, 2015

Drug Sensitivity Testing for Cancer Therapy, Key Areas

Da-Yong Lu¹, Ting-Ren Lu², Nagendra Sastry Yarla³

¹School of Life Sciences, Shanghai University, Shanghai 200444, PRC, China.

Reviews on Recent Clinical Trials

|August 20, 2022

Abstract

Aims:

Cancer is a high-mortality disease (9.6 million deaths in 2018 worldwide). Given various anticancer drugs, drug selection plays a key role in patient survival in clinical trials.

Methods:

Drug Sensitivity Testing (DST), one of the leading drug selective systems, was widely practiced for therapeutic promotion in the clinic. Notably, DSTs assist in drug selection that benefits drug responses against cancer from 20-22% to 30-35% over the past two decades. The relationship between drug resistance in vitro and drug treatment benefits was associated with different tumor origins and subtypes. Medical theory and underlying DST mechanisms remain poorly understood until now. The study of the clinical scenario, sustainability and financial support for mechanism and technical promotions is indispensable.

Results:

Despite the great technical advance, therapeutic prediction and drug selection by DST needs to be miniature, versatility and cost-effective in the clinic. Multi-parameters and automation of DST should be a future trend. Advanced biomedical knowledge and clinical approaches to translating oncologic profiles into drug selection were the main focuses of DST developments. With a great technical stride, the clinical architecture of the DST platform was entering higher levels (drug response testing at any stage of cancer patients and miniaturization of tumor samples).

Discussion:

The cancer biology and pharmacology for drug selection mutually benefit the clinic. New proposals to reveal more therapeutic information and drug response prediction at genetic, molecular and omics levels should be estimated overall.

Conclusion:

By upholding this goal of non-invasive, versatility and automation, DST could save the life of several thousand annually worldwide. In this article, new insights into DST novelty and development are highlighted.

Insights

Drug Sensitivity Testing (DST) improves cancer drug selection, enhancing patient survival. Further research into DST mechanisms and clinical integration is crucial for advancing cancer treatment and saving lives globally.

Area of Science:

Oncology
Pharmacology
Biomedical Science

Background:

Cancer remains a leading cause of mortality worldwide, with effective drug selection being critical for patient survival in clinical trials.
Drug Sensitivity Testing (DST) has been employed to guide anticancer drug selection, showing modest improvements in drug response rates over two decades.
The underlying mechanisms and clinical applicability of DST require further investigation, particularly concerning the correlation between in vitro drug resistance and clinical outcomes across diverse tumor types.

Purpose of the Study:

To review the advancements and future directions of Drug Sensitivity Testing (DST) in clinical oncology.
To highlight the importance of understanding DST mechanisms for improved therapeutic prediction and drug selection.
To emphasize the need for cost-effective, versatile, and automated DST platforms in clinical practice.

Main Methods:

Review of current literature and clinical practices related to Drug Sensitivity Testing (DST).
Analysis of the technical progress and limitations of existing DST platforms.
Exploration of the relationship between in vitro drug resistance, tumor characteristics, and clinical treatment benefits.

Main Results:

Drug Sensitivity Testing (DST) has shown incremental benefits in cancer drug selection, but its full potential is limited by a lack of understanding of underlying mechanisms.
Current DST approaches require advancements towards miniaturization, versatility, and cost-effectiveness to be widely adopted.
Future trends in DST involve multi-parameter analysis, automation, and integration of advanced biomedical knowledge for precise oncologic profiling.

Conclusions:

Drug Sensitivity Testing (DST) holds significant promise for improving cancer patient outcomes through personalized drug selection.
Further research into cancer biology, pharmacology, and omics-level analysis is essential for enhancing DST's predictive power.
The development of non-invasive, versatile, and automated DST platforms could significantly impact global cancer survival rates.

Read full analysis

Keywords:

Drug sensitivity testing anti-cancer drug cancer pathology clinical pharmacology diagnostic platform drug selection microfluidics

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