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Predicting the active doses in humans from animal studies: a novel approach in oncology
M Rocchetti1, M Simeoni, E Pesenti
1Preclinical Development, Nerviano Medical Sciences, Viale Pasteur 10, 20014 Nerviano (MI), Italy. maurizio.rocchetti@nervianoms.com
Abstract:
The success rate of clinical drug development is significantly lower in oncology than in other therapeutic areas. Predicting the activity of new compounds in humans from preclinical data could substantially reduce the number of failures. A novel approach for predicting the expected active doses in humans from the first animal studies is presented here. The method relies upon a PK/PD model of tumour growth inhibition in xenografts, which provides parameters describing the potency of the tested compounds. Anticancer drugs, currently used in the clinic, were evaluated in xenograft models and their potency parameters were estimated. A good correlation was obtained between these parameters and the exposures sustained at the therapeutically relevant dosing regimens. Based on the corresponding regression equation and the potency parameters estimated in the first preclinical studies, the therapeutically active concentrations of new compounds can be estimated. An early knowledge of level of exposure or doses to be reached in humans will improve the risk evaluation and decision making processes in anticancer drug development.
Insights
Predicting anticancer drug efficacy in humans early can reduce costly failures. This study presents a novel preclinical method using PK/PD modeling in xenografts to estimate effective human doses for new cancer drugs.
Area of Science:
- Pharmacology
- Oncology
- Drug Development
Background:
- Clinical drug development in oncology has a notably low success rate compared to other therapeutic areas.
- Reducing late-stage failures in oncology drug development is crucial for efficiency and patient benefit.
Purpose of the Study:
- To introduce a novel predictive method for estimating the active doses of anticancer compounds in humans based on early preclinical data.
- To improve risk assessment and decision-making processes in preclinical oncology drug development.
Main Methods:
- Utilized a pharmacokinetic/pharmacodynamic (PK/PD) model to analyze tumor growth inhibition in xenograft models.
- Estimated compound potency parameters from preclinical xenograft studies.
- Correlated preclinical potency parameters with drug exposures at therapeutically relevant human dosing regimens.
Main Results:
- A significant correlation was observed between estimated compound potency parameters from xenografts and drug exposures in humans.
- The developed regression equation allows for the estimation of therapeutically active concentrations of new compounds.
- Preclinical studies successfully predicted the potency of existing anticancer drugs.
Conclusions:
- The novel PK/PD modeling approach enables early prediction of human therapeutic doses for anticancer drugs.
- This method can substantially reduce the failure rate in oncology drug development by improving early risk evaluation.
- Informed decision-making in preclinical stages can be achieved through early estimation of drug exposure levels.
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