The role of population PK-PD modelling in paediatric clinical research

Children differ from adults in their response to drugs. While this may be the result of changes in dose exposure (pharmacokinetics [PK]) and/or exposure response (pharmacodynamics [PD]) relationships, the magnitude of these changes may not be solely reflected by differences in body weight. As a consequence, dosing recommendations empirically derived from adults dosing regimens using linear extrapolations based on body weight, can result in therapeutic failure, occurrence of adverse effect or even fatalities. In order to define rational, patient-tailored dosing schemes, population PK-PD studies in children are needed. For the analysis of the data, population modelling using non-linear mixed effect modelling is the preferred tool since this approach allows for the analysis of sparse and unbalanced datasets. Additionally, it permits the exploration of the influence of different covariates such as body weight and age to explain the variability in drug response. Finally, using this approach, these PK-PD studies can be designed in the most efficient manner in order to obtain the maximum information on the PK-PD parameters with the highest precision. Once a population PK-PD model is developed, internal and external validations should be performed. If the model performs well in these validation procedures, model simulations can be used to define a dosing regimen, which in turn needs to be tested and challenged in a prospective clinical trial. This methodology will improve the efficacy/safety balance of dosing guidelines, which will be of benefit to the individual child

SIMS: A Hybrid Method for Rapid Conformational Analysis

Proteins are at the root of many biological functions, often performing complex tasks as the result of large changes in their structure. Describing the exact details of these conformational changes, however, remains a central challenge for computational biology due the enormous computational requirements of the problem. This has engendered the development of a rich variety of useful methods designed to answer specific questions at different levels of spatial, temporal, and energetic resolution. These methods fall largely into two classes: physically accurate, but computationally demanding methods and fast, approximate methods. We introduce here a new hybrid modeling tool, the Structured Intuitive Move Selector (SIMS), designed to bridge the divide between these two classes, while allowing the benefits of both to be seamlessly integrated into a single framework. This is achieved by applying a modern motion planning algorithm, borrowed from the field of robotics, in tandem with a well-established protein modeling library. SIMS can combine precise energy calculations with approximate or specialized conformational sampling routines to produce rapid, yet accurate, analysis of the large-scale conformational variability of protein systems. Several key advancements are shown, including the abstract use of generically defined moves (conformational sampling methods) and an expansive probabilistic conformational exploration. We present three example problems that SIMS is applied to and demonstrate a rapid solution for each. These include the automatic determination of ﾑﾑactiveﾒﾒ residues for the hinge-based system Cyanovirin-N, exploring conformational changes involving long-range coordinated motion between non-sequential residues in Ribose- Binding Protein, and the rapid discovery of a transient conformational state of Maltose-Binding Protein, previously only determined by Molecular Dynamics. For all cases we provide energetic validations using well-established energy fields, demonstrating this framework as a fast and accurate tool for the analysis of a wide range of protein flexibility problems

Intracoronary Eptifibatide During Primary Percutaneous Coronary Intervention in Early Versus Late Presenters with ST Segment Elevation Myocardial Infarction: A Randomized Trial

INTRODUCTION: The role of intracoronary (IC) eptifibatide in primary percutaneous coronary intervention (PPCI) for ST segment elevation myocardial infarction (STEMI) and whether time of patient presentation affects this role are unclear. We sought to evaluate the benefit of IC eptifibatide use during primary PCI in early STEMI presenters compared to late STEMI presenters. METHODS: We included 70 patients who presented with STEMI and were eligible for PPCI. On the basis of symptom-to-door time, patients were classified into two arms: early (\u3c 3 h, n = 34) vs late (≥ 3 h, n = 36) presenters. They were then randomized to local IC eptifibatide infusion vs standard care (control group). The primary end point was post-PCI myocardial blush grade (MBG) in the culprit vessel. Other end points included corrected TIMI frame count (cTFC), ST segment resolution (STR) ≥70%, and peak CKMB. RESULTS: In the early presenters arm, no difference was observed in MBG results ≥2 in the IC eptifibatide and control groups (100% vs 82%; p = 0.23). In the late presenters arm, the eptifibatide subgroup was associated with improved MBG ≥2 (100% vs 50%; p = 0.001). IC eptifibatide in both early and late presenters was associated with less cTFC (early presenters 19 vs. 25.6, p = 0.001; late presenters 20 vs. 31.5, p \u3c 0.001) and less peak CKMB (early presenters 210 vs 260 IU/L, p = 0.006; late presenters 228 vs 318 IU/L, p = 0.005) compared with the control group. No difference existed between both groups in STR index in early and late presenters. CONCLUSION: IC eptifibatide might improve the reperfusion markers during PPCI for STEMI patients presenting after 3 h from onset of symptoms. A large randomized study is recommended to ascertain the benefits of IC eptifibatide in late presenters on clinical outcomes