A pharmacokinetic-pharmacodynamic model for predicting tumour growth inhibition in mice: a useful tool in oncology drug development.
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Animals↗
Biomedical subjects
Monica Simeoni
Publications and source records attributed to Monica Simeoni.
Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth kinetics in xenograft models after administration of anticancer agents.
The available mathematical models describing tumor growth and the effect of anticancer treatments on tumors in animals are of limited use within the drug industry. A simple and effective model would allow applying quantitative thinking to the preclinical development of oncology drugs. In this article, a minimal pharmacokinetic-pharmacodynamic model is presented, based on a system of ordinary differential equations that link the dosing regimen of a compound to the tumor growth in animal models. The growth of tumors in nontreated animals is described by an exponential growth followed by a linear growth. In treated animals, the tumor growth rate is decreased by a factor proportional to both drug concentration and number of proliferating tumor cells. A transit compartmental system is used to model the process of cell death, which occurs at later times. The parameters of the pharmacodynamic model are related to the growth characteristics of the tumor, to the drug potency, and to the kinetics of the tumor cell death. Therefore, such parameters can be used for ranking compounds based on their potency and for evaluating potential differences in the tumor cell death process. The model was extensively tested on discovery candidates and known anticancer drugs. It fitted well the experimental data, providing reliable parameter estimates. On the basis of the parameters estimated in a first experiment, the model successfully predicted the response of tumors exposed to drugs given at different dose levels and/or schedules. It is, thus, possible to use the model prospectively, optimizing the design of new experiments.
Antineoplastic Agents↗
Validation of two algorithms to evaluate the interface between bone and orthopaedic implants.
The level of fit and fill of the prosthetic stem in the femoral canal is an important parameter when planning a cementless total hip arthroplasty. However, the standard templates used in combination with radiographs are not always effective in the pre-operative evaluation of the level of fitting. For this reason, two algorithms were developed able to provide clinically relevant three-dimensional indicators of the implant fit and fill in the host femur, based on the CT data of each specific patient as collected in vivo. In this study the computational methods were described and validated using digital phantom datasets. Then the algorithms were applied for in vivo datasets and the sensitivity of each indicator was evaluated. The validation showed that the two algorithms are accurate from a computational point of view. Moreover, the in vivo testing demonstrated that the developed methods provide reasonable quantitative indicators of the stem positioning in the femoral CT dataset.
Algorithms↗
An automated method to position prosthetic components within multiple anatomical spaces.
The level of fit and fill of a stem in the host femur is the most critical factor for the mechanical stability and success of the prosthesis. It would be useful to have a simulation tool able to investigate the anatomical compatibility of a new implant in a large library of femoral anatomies in the early phases of the design process. In order to realise this tool, it is necessary to develop an automatic method for the positioning of the stem in a database of anatomies. The aim of this study was to develop and evaluate a method for the automatic positioning of the stem geometry in the anatomical CT dataset. Two different strategies were considered: a completely automatic registration technique and a semi-automatic method based on an anatomical referencing. The two procedures were compared to the manual positioning obtained by an expert surgeon in a set of nine CT datasets. For both methods in each femur the positioning and the orientation of the stem were good. The results showed a better level of fitting for the automatic method, while the shift of the hip joint centre was lower for the anatomical referencing technique. However, the anatomical referencing method requires a higher computational effort without being significantly better than the automatic method. For this reason, the automatic method should be chosen to develop the automatic positioning of a stem in a database of anatomies.
Arthroplasty, Replacement, Hip↗