Biomedical subjects

D Barbolosi

Publications and source records attributed to D Barbolosi.

4 recordsLinked to original sources

PubMed2001

Optimizing drug regimens in cancer chemotherapy: a simulation study using a PK-PD model.

In cancer chemotherapy, it is important to design treatment strategies for drug protocols that ensure a desired rate of tumor cell kill without overdosing the host. Mathematical modeling was used for optimization in which we minimize the end value of the tumor cells while limiting toxicity by always maintaining the white blood cell count beyond a limit. The optimal solution for this is a mixture of an initial bolus application of drug followed by no drug and then continuous infusion that keeps the normal cell population at its lower limit while decreasing the tumor cell population.

Antineoplastic Agents↗

PubMed2001

Information tools for exploratory data analysis in population pharmacokinetics.

For a group of individuals, population pharmacokinetic studies describe the interindividual variability through a statistical distribution. These studies conducted during the drug development serve as a useful marker of the safety of the drug, provide information that might be decisive for future experiments and, in a clinical context, help establish guidelines for optimal use in each patient. As complementary tools to the existing statistical and graphical techniques for population pharmacokinetic data analysis, indexes derived from information theory were used to select the most appropriate modelfor the statistical distribution, to detect atypical individuals, and to screen influential covariates. The rationale for using these indexes is shown using simulated and real data.

Humans↗

PubMed2000

Optimizing drug regimens in cancer chemotherapy by an efficacy-toxicity mathematical model.

In cancer chemotherapy, it is important to design treatment strategies that ensure a desired rate of tumor cell kill without unacceptable toxicity. To optimize treatment, we used a mathematical model describing the pharmacokinetics of anticancer drugs, antitumor efficacy, and drug toxicity. This model was associated with constraints on the allowed plasma concentrations, drug exposure, and leukopenia. Given a schedule of drug administrations, the mathematical model optimized the drug doses that can minimize the tumor burden while limiting toxicity at the level of the white blood cells. The main result is that the optimal drug administration is an initial high-dose chemotherapy up to saturation of constraints associated with normal cell toxicity and a maintenance continuous infusion at a moderate rate. Data related to etoposide investigations were used in a feasibility study. Simulations with the optimized protocol showed better performances than usual clinical protocols. Model-based optimal drug doses provide for greater cytoreduction, while limiting the risk of unacceptable toxicity.

Antineoplastic Agents↗

PubMed1994

Dosage regimen calculations with optimal control theory.

In clinical pharmacokinetics, dosage regimen calculation involves determination of either: (1) the drug amount to be administered according to a set time schedule, or (2) the time schedule to be used for appropriate drug amounts. The goal is to guarantee that the time profile of circulating drug levels is between the thresholds of toxicity and efficacy. For the first case, solutions are obtained by using the property of linearity when it holds. Herein, we present several results concerning the second case. The optimal control theory allows determination of switching times between the minimal and maximal input rates in order to ensure the fastest transition from an initial state to the therapeutic levels. Fundamental results are reported and the approach is developed for drugs administered by intravenous infusion. By means of the phase trajectories, general graphical rules are presented to design the optimal control and to determine the reachable areas. A numerical example is given, comparisons of the method with others are attempted and potential developments are pointed out.

Drug Administration Schedule↗