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Updated: May 20, 2026
A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Published on: April 6, 2016
Modeling and predicting clinical efficacy for drugs targeting the tumor milieu
Mallika Singh1, Napoleone Ferrara
1Novartis Institutes for Biomedical Research, Emeryville, California, USA. mallika.singh@novartis.com
Abstract:
Disappointing results from most late-stage clinical trials of cancer therapeutics indicate a need for improved and more-predictive animal tumor models. This insufficiency of models, combined with the advent of a class of drugs that target the tumor microenvironment rather than the tumor cell, presents new challenges for designing and interpreting preclinical efficacy studies. A comparison of the clinical efficacy of anti-angiogenic drugs with their corresponding preclinical studies over the past two decades offers many lessons that can inform and improve the design of experiments in existing mouse models. In addition, technological and logistical advances in mouse models of human cancer over the past five years have the potential to increase the clinical translatability of animal studies.
Insights
Improving cancer models is crucial as many late-stage trials fail. Lessons from anti-angiogenic drug studies in mice can enhance preclinical cancer research and drug development.
Area of Science:
- Oncology
- Translational Medicine
- Pharmacology
Background:
- Late-stage clinical trials for cancer therapeutics frequently yield disappointing results, highlighting a critical need for more predictive animal tumor models.
- The development of drugs targeting the tumor microenvironment, rather than tumor cells directly, introduces complexities in preclinical study design and interpretation.
- A significant gap exists between the efficacy observed in preclinical cancer models and clinical outcomes, impacting drug development.
Purpose of the Study:
- To analyze the lessons learned from two decades of comparing clinical efficacy of anti-angiogenic drugs with their preclinical studies.
- To propose improvements for the design and interpretation of preclinical efficacy studies in existing mouse models.
- To explore how recent technological and logistical advances in mouse models of human cancer can enhance clinical translatability.
Main Methods:
- Comparative analysis of preclinical data and clinical trial outcomes for anti-angiogenic drugs over the past 20 years.
- Review of technological and logistical advancements in mouse models of human cancer within the last five years.
- Literature review and synthesis of findings related to cancer therapeutics targeting the tumor microenvironment.
Main Results:
- Historical comparisons reveal valuable insights into the limitations of current preclinical models for predicting clinical success of anti-angiogenic therapies.
- Specific experimental design elements and interpretation strategies can be refined based on past discrepancies between preclinical and clinical results.
- Recent innovations in mouse cancer models offer enhanced potential for increased clinical translatability.
Conclusions:
- Refining preclinical cancer models and study designs, informed by past clinical trial data, is essential for improving the success rate of cancer therapeutics.
- Leveraging advancements in mouse models and focusing on tumor microenvironment interactions can lead to more predictive preclinical studies.
- Enhanced translatability of animal studies is achievable through strategic improvements in model selection and experimental methodology.
