Related Experiment Videos
Extending principles learned in model systems to clinical trials design
P J Houghton1, C F Stewart, J Thompson
1Department of Molecular Pharmacology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA.
Oncology (Williston Park, N.Y.)
|September 3, 1998
Summary
Preclinical cancer models accurately predict clinical response to irinotecan (CPT-11) and camptothecin analogs when host tolerance is considered in clinical trial design. Optimizing trial design enhances drug efficacy.
Area of Science:
- Oncology
- Pharmacology
- Translational Medicine
Background:
- Clinical outcomes with irinotecan (CPT-11) and other camptothecin derivatives in cancer treatment have not met preclinical predictions.
- A common hypothesis suggests preclinical xenograft models fail to predict human cancer sensitivity.
Purpose of the Study:
- To investigate the discrepancy between preclinical findings and clinical outcomes for camptothecin derivatives.
- To re-evaluate the predictive accuracy of preclinical xenograft models in cancer drug development.
Main Methods:
- Analysis of existing preclinical and clinical data for irinotecan and related compounds.
- Comparative assessment of xenograft model predictions versus actual clinical response rates.
- Evaluation of the impact of host tolerance factors on drug efficacy.
Main Results:
- Preclinical xenograft models are accurate predictors of clinical response when host tolerance differences are incorporated into clinical trial design.
- The discrepancy between preclinical and clinical results is attributed to suboptimal clinical trial design, not model inaccuracy.
- Adjusting clinical trial parameters based on preclinical data can significantly improve response rates.
Conclusions:
- Camptothecin analogs demonstrate the potential for integrated, pharmacokinetically driven preclinical and clinical drug development.
- Optimizing clinical trial design based on preclinical principles is crucial for enhancing cancer therapeutic efficacy.
- Future drug development should prioritize the translation of preclinical insights into robust clinical trial strategies.