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Developments in preclinical cancer imaging: innovating the discovery of therapeutics
James R W Conway1, Neil O Carragher2, Paul Timpson1
1Garvan Institute of Medical Research and The Kinghorn Cancer Centre Sydney, St Vincent's Clinical School, Faculty of Medicine, University of New South Wales, New South Wales 2010, Sydney, Australia.
Abstract:
Integrating biological imaging into early stages of the drug discovery process can provide invaluable readouts of drug activity within complex disease settings, such as cancer. Iterating this approach from initial lead compound identification in vitro to proof-of-principle in vivo analysis represents a key challenge in the drug discovery field. By embracing more complex and informative models in drug discovery, imaging can improve the fidelity and statistical robustness of preclinical cancer studies. In this Review, we highlight how combining advanced imaging with three-dimensional systems and intravital mouse models can provide more informative and disease-relevant platforms for cancer drug discovery.
Insights
Integrating advanced biological imaging into early drug discovery improves cancer research. Combining imaging with 3D systems and intravital mouse models offers more informative, disease-relevant preclinical studies.
Area of Science:
- Oncology
- Pharmacology
- Biomedical Imaging
Background:
- Biological imaging offers valuable insights into drug activity in complex diseases like cancer.
- Integrating imaging early in drug discovery, from in vitro to in vivo, presents a significant challenge.
- More informative and disease-relevant preclinical cancer studies can be achieved by using advanced imaging.
Purpose of the Study:
- To review how advanced imaging can enhance cancer drug discovery.
- To highlight the benefits of combining imaging with complex biological models.
- To demonstrate improved fidelity and statistical robustness in preclinical cancer research.
Main Methods:
- Review of current literature on biological imaging in drug discovery.
- Focus on advanced imaging techniques.
- Integration of three-dimensional (3D) systems and intravital mouse models.
Main Results:
- Advanced imaging provides crucial data on drug efficacy in complex disease models.
- Combining imaging with 3D systems and intravital models enhances the relevance of preclinical studies.
- Improved accuracy and reliability of drug discovery readouts.
Conclusions:
- Advanced imaging, coupled with sophisticated models, is key to overcoming challenges in preclinical cancer drug discovery.
- This integrated approach leads to more informative and disease-relevant platforms.
- Enhancing the drug discovery process for better cancer therapeutics.
