Verena Gotta

Monitoring drug therapy.

Drug development has improved over recent decades, with refinements in analytical techniques, population pharmacokinetic-pharmacodynamic (PK-PD) modelling and simulation, and new biomarkers of efficacy and tolerability. Yet this progress has not yielded improvements in individualization of treatment and monitoring, owing to various obstacles: monitoring is complex and demanding, many monitoring procedures have been instituted without critical assessment of the underlying evidence and rationale, controlled clinical trials are sparse, monitoring procedures are poorly validated and both drug manufacturers and regulatory authorities take insufficient account of the importance of monitoring. Drug concentration and effect data should be increasingly collected, analyzed, aggregated and disseminated in forms suitable for prescribers, along with efficient monitoring tools and evidence-based recommendations regarding their best use. PK-PD observations should be collected for both novel and established critical drugs and applied to observational data, in order to establish whether monitoring would be suitable. Methods for aggregating PK-PD data in systematic reviews should be devised. Observational and intervention studies to evaluate monitoring procedures are needed. Miniaturized monitoring tests for delivery at the point of care should be developed and harnessed to closed-loop regulated drug delivery systems. Intelligent devices would enable unprecedented precision in the application of critical treatments, i.e. those with life-saving efficacy, narrow therapeutic margins and high interpatient variability. Pharmaceutical companies, regulatory agencies and academic clinical pharmacologists share the responsibility of leading such developments, in order to ensure that patients obtain the greatest benefit and suffer the least harm from their medicines.

Inter-study variability of preclinical in vivo safety studies and translational exposure-QTc relationships--a PKPD meta-analysis.

Preclinical cardiovascular safety studies (CVS) have been compared between facilities with respect to their sensitivity to detect drug‐induced QTc prolongation (ΔQTc). Little is known about the consistency of quantitative ΔQTc predictions that are relevant for translation to humans.

Representation of Medical Guidelines with a Computer Interpretable Model

Nowadays medical software is tightly coupled with medical devices that perform patient state monitoring and lately even some basic treatment procedures. Medical guidelines (GLs) can be seen as specification of a medical system which requires their computer-interpretable representation of medical GLs. Until now most of the medical GLs are often represented in a textual format and therefore often suffer from such structural problems as incompleteness, inconsistencies, ambiguity and redundancy, which makes the translation process to the machine-interpretable language more complicated. Computer-based interpretation of GLs can improve the quality of protocols as well as the quality of medical service. Several GLs formal representation methods have been presented recently. Only some of them enable automatic formal verification by introducing an additional translation path to the existing model checking environments. However, if a verified property fails it is difficult to trace back the result needed to change the model. Moreover, these formalisms provide the notion of time mostly in terms of actions order. In this paper we preset the application of a well-know formal behaviour representation approach of embedded systems design domain to medical GLs interpretation. We use Timed Automata extended with Tasks (TAT) and TIMES toolbox to represent medical GLs as a system behaviour in a computer interpretable form. We discuss the verification issues with the help of the anticancer drug imatinib case study.

Application of a systems pharmacology model for translational prediction of hERG-mediated QTc prolongation.

Drug‐induced QTc interval prolongation (ΔQTc) is a main surrogate for proarrhythmic risk assessment. A higher in vivo than in vitro potency for hERG‐mediated QTc prolongation has been suggested. Also, in vivo between‐species and patient populations’ sensitivity to drug‐induced QTc prolongation seems to differ. Here, a systems pharmacology model integrating preclinical in vitro (hERG binding) and in vivo (conscious dog ΔQTc) data of three hERG blockers (dofetilide, sotalol, moxifloxacin) was applied (1) to compare the operational efficacy of the three drugs in vivo and (2) to quantify dog–human differences in sensitivity to drug‐induced QTc prolongation (for dofetilide only). Scaling parameters for translational in vivo extrapolation of drug effects were derived based on the assumption of system‐specific myocardial ion channel densities and transduction of ion channel block: the operational efficacy (transduction of hERG block) in dogs was drug specific (1–19% hERG block corresponded to ≥10 msec ΔQTc). System‐specific maximal achievable ΔQTc was estimated to 28% from baseline in both dog and human, while %hERG block leading to half‐maximal effects was 58% lower in human, suggesting a higher contribution of hERG‐mediated potassium current to cardiac repolarization. These results suggest that differences in sensitivity to drug‐induced QTc prolongation may be well explained by drug‐ and system‐specific differences in operational efficacy (transduction of hERG block), consistent with experimental reports. The proposed scaling approach may thus assist the translational risk assessment of QTc prolongation in different species and patient populations, if mediated by the hERG channel.

Drivers of antibiotic prescribing in children and adolescents with febrile lower respiratory tract infections

Background Knowledge of key drivers for antibiotic prescribing in pediatric lower respiratory tract infection (LRTI) could support rational antibiotic use. Thus, we aimed to determine the impact of clinical and laboratory factors on antibiotic prescribing in children and adolescents with febrile LRTI. Methods Pediatric patients from the standard care control group of a randomized controlled trial (ProPAED) investigating procalcitonin guided antibiotic treatment in febrile LRTI were included in a multivariate logistic regression analysis to evaluate the impact of laboratory and clinical factors on antibiotic prescribing. Results The standard care control group of the ProPAED study comprised 165 LRTI patients (median age: 2.7 years, range: 0.1–16), out of which 88 (55%) received antibiotic treatment. Factors significantly associated with antibiotic prescribing in patients with complete clinical and laboratory documentation (n = 158) were C-reactive protein (OR 5.8 for a 10-fold increase, 95%CI 2.2–14.9), white blood count beyond age-dependent reference range (OR 3.9, 95%CI 1.4–11.4), body temperature (OR 1.7 for an increase by 1°C, 95%CI 1.02–2.68), and pleuritic pain (OR 2.8, 95%CI 1.1–7.6). Dyspnea (OR 0.3, 95%CI 0.1–0.7) and wheezing (OR 0.3, 95%CI 0.13–0.95) were inversely associated with antibiotic prescribing. Conclusion Laboratory markers were strong drivers of antibiotic prescribing in children with febrile lower respiratory tract infections, in spite of their known poor prediction of antibiotic need. Building on current guidelines for antibiotic treatment in children with febrile LRTI, a reliable decision algorithm for safe antibiotic withholding considering the laboratory and clinical factors evaluated in this study has the potential to further reduce antibiotic prescribing.

A SYSTEMS PHARMACOLOGY MODEL TO EXPLAIN DEVELOPMENTAL DIFFERENCES IN SENSITIVITY TO DRUG-INDUCED QT PROLONGATION

Background Neonates have been reported to be more sensitive to drugs prolonging the QT-interval than adults. As explanation a developmental change in myocardial ion-channel density has been proposed. Here we explore changes in ion-channel density using a mechanistic pharmacodynamic model and clinical sotalol literature data. Materials and Methods The applied model relates in vitro and in vivo drug potency (regarding IKr-receptor occupancy and QTc-prolongation, respectively) by a system-specific transducer function. We characterized this function first for preclinical dog and in vitro data (moxifloxacin, sotalol, dofetilide). From a corresponding dofetilide model in adults we derived scaling factors for the system-specific parameters (maximal in vivo QTc-effect Em,dog/Em,adults, transducer ratio τ,dog/τ,adults; τ is proportional to the receptor density in vivo). The derived relationship was used to predict clinical sotalol pharmacodynamics in adults. Literature data was used to evaluate this scaling approach. Simulations of different τ values were performed to explore pharmacodynamic differences in neonates. Results In adults, the agonistic activity of dofetilide was higher than in dogs (τ,adults≈2x τ,dogs), while the estimated maximal in vivo QTc-prolongation was similar (Em≈27% from baseline). This relationship could also predict clinical sotalol pharmacodynamics in adults and children. The steeper PD profile in neonates could be explained by a higher IKr-receptor density (τ, neonates≈2x τ, adults). Conclusion This model-based approach allowed to integrate and scale in vitro and in vivo (preclinical, clinical adult and neonate) drug effects on the QTc-interval. The preliminary results confirm the hypothesis that IKr-receptor density is higher (≈2 times) in neonates than in adults and children.

An agenda for UK clinical pharmacology: Monitoring drug therapy: Commentary

Drug development has improved over recent decades, with refinements in analytical techniques, population pharmacokinetic-pharmacodynamic (PK-PD) modelling and simulation, and new biomarkers of efficacy and tolerability. Yet this progress has not yielded improvements in individualization of treatment and monitoring, owing to various obstacles: monitoring is complex and demanding, many monitoring procedures have been instituted without critical assessment of the underlying evidence and rationale, controlled clinical trials are sparse, monitoring procedures are poorly validated and both drug manufacturers and regulatory authorities take insufficient account of the importance of monitoring. Drug concentration and effect data should be increasingly collected, analyzed, aggregated and disseminated in forms suitable for prescribers, along with efficient monitoring tools and evidence-based recommendations regarding their best use. PK-PD observations should be collected for both novel and established critical drugs and applied to observational data, in order to establish whether monitoring would be suitable. Methods for aggregating PK-PD data in systematic reviews should be devised. Observational and intervention studies to evaluate monitoring procedures are needed. Miniaturized monitoring tests for delivery at the point of care should be developed and harnessed to closed-loop regulated drug delivery systems. Intelligent devices would enable unprecedented precision in the application of critical treatments, i.e. those with life-saving efficacy, narrow therapeutic margins and high interpatient variability. Pharmaceutical companies, regulatory agencies and academic clinical pharmacologists share the responsibility of leading such developments, in order to ensure that patients obtain the greatest benefit and suffer the least harm from their medicines.