Population Modeling of Anti-infective Drugs Clinical Trial
Official title:
Translational PKPD Modeling of Anti-infective Drugs in Children Treated in Pediatric Units on the Example of Selected Antibiotics and Antifungals.
Pharmacokinetic and pharmacodynamic modeling (PKPD) is becoming an essential tool for optimizing pharmacotherapy. Building mechanistic models allows determining the relationship between the dose, concentration, pharmacological effect, and side effects in various populations. The growing resistance to drugs among bacteria is a challenge for medicine, and the progress in pharmacometrics enables us to make rational clinical decisions. A particular group of patients is children with differences in PK and PD of drugs. The lack of clinical studies often forces to extrapolate dosing based on the results obtained in adults. In intensive care units, up to 70-90% of drugs in children are used off-label. Drug agencies point to the importance of the population-based approach to data analysis, especially in infants and children. Under the project, work will focus on the PK and PD of antifungal drugs (fluconazole, isavuconazole, and anidulafungin) and antibiotics (cefotaxime and meropenem) in the pediatric and adult populations. The choice of topic is dictated by the growing need to create PKPD models of the drugs mentioned above in children. The hypothesis is the assumption that using a mathematical model will enable to describe the time course of the drug in the organism, the relationship between the effect and the dose of the medicine and its concentration in the plasma, and the influence of individual factors on the PKPD profile of a drug.
Cefotaxime and meropenem are broad-spectrum antibiotics, most commonly prescribed in pediatric and adult intensive care units. Unfortunately, the applied dosing regimens based on the results obtained in adults or only on drug pharmacokinetics (without taking into account the pharmacodynamic profile) often fail. The situation is additionally complicated by the observed clinically significant drug interactions. The results of published studies indicate the need to develop PKPD models for these drugs in the pediatric and adult populations. Fluconazole, isavuconazole and anidulafungin are the azole anti-fungal drugs and echinocandin. Despite the optimistic results of studies in adults, showing high efficacy, a favorable PK profile, and the safety profile of these therapeutics, there are no studies in children. The research will be conducted at the Pediatric Clinical Hospital of K. Jonscher, The Greater Poland Cancer Center, and Heliodor Święcicki Clinical Hospital of the Medical University in Poznań. With the approval of the Bioethics Committee, about 150 children and adults will be included in the study. Blood samples will be collected at appropriate time points to investigate the PK profile. The measured pharmacological effect will be the minimum inhibitory concentration (MIC). PKPD indices will be included in the model, depending on the tested drug: T> MIC, Cmax / MIC, and AUC / MIC. The values of covariates that may affect drug PK and PD will be reported. The analysis will consider the polymorphisms of the OAT3 organic anion transporter genes and the MRP4 transport protein. HPLC will examine plasma drug concentration levels in conjunction with UV detection. The Xevo TQ-S micro triple quadrupole mass spectrometer, coupled with ultra-efficient liquid chromatography with the PDA acquity UPLC detector I-class PDA Waters. The genetic polymorphism of selected genes will be tested by real-time PCR using the LightCycler® 480 II Instrument. The PKPD population analysis will be performed by nonlinear modeling of mixed-effects using NONMEM version 7.2.0, the GNU Fortran 9.0 compiler, and Wings for NONMEM and RStudio. The collected data will be used to build hypothetical models using neural networks. The expected result of the project's primary goal is to build PKPD models of fluconazole, isavuconazole, anidulafungin, cefotaxime, and meropenem in the pediatric and adult populations. According to the final model's principles, they will be evaluated and can serve as a specialized tool for personalizing pharmacotherapy. ;