Thoughtflow: Standards and Tools for Provenance Capture and Workflow Definition to Support Model-Informed Drug Discovery and Development.

Pharmacometric analyses are complex and multifactorial. It is essential to check, track, and document the vast amounts of data and metadata that are generated during these analyses (and the relationships between them) in order to comply with regulations, support quality control, auditing, and reporting. It is, however, challenging, tedious, error-prone, and time-consuming, and diverts pharmacometricians from the more useful business of doing science. Automating this process would save time, reduce transcriptional errors, support the retention and transfer of knowledge, encourage good practice, and help ensure that pharmacometric analyses appropriately impact decisions. The ability to document, communicate, and reconstruct a complete pharmacometric analysis using an open standard would have considerable benefits. In this article, the Innovative Medicines Initiative (IMI) Drug Disease Model Resources (DDMoRe) consortium proposes a set of standards to facilitate the capture, storage, and reporting of knowledge (including assumptions and decisions) in the context of model-informed drug discovery and development (MID3), as well as to support reproducibility: "Thoughtflow." A prototype software implementation is provided.

Advanced Methods for Dose and Regimen Finding During Drug Development: Summary of the EMA/EFPIA Workshop on Dose Finding (London 4-5 December 2014).

Inadequate dose selection for confirmatory trials is currently still one of the most challenging issues in drug development, as illustrated by high rates of late-stage attritions in clinical development and postmarketing commitments required by regulatory institutions. In an effort to shift the current paradigm in dose and regimen selection and highlight the availability and usefulness of well-established and regulatory-acceptable methods, the European Medicines Agency (EMA) in collaboration with the European Federation of Pharmaceutical Industries Association (EFPIA) hosted a multistakeholder workshop on dose finding (London 4-5 December 2014). Some methodologies that could constitute a toolkit for drug developers and regulators were presented. These methods are described in the present report: they include five advanced methods for data analysis (empirical regression models, pharmacometrics models, quantitative systems pharmacology models, MCP-Mod, and model averaging) and three methods for study design optimization (Fisher information matrix (FIM)-based methods, clinical trial simulations, and adaptive studies). Pairwise comparisons were also discussed during the workshop; however, mostly for historical reasons. This paper discusses the added value and limitations of these methods as well as challenges for their implementation. Some applications in different therapeutic areas are also summarized, in line with the discussions at the workshop. There was agreement at the workshop on the fact that selection of dose for phase III is an estimation problem and should not be addressed via hypothesis testing. Dose selection for phase III trials should be informed by well-designed dose-finding studies; however, the specific choice of method(s) will depend on several aspects and it is not possible to recommend a generalized decision tree. There are many valuable methods available, the methods are not mutually exclusive, and they should be used in conjunction to ensure a scientifically rigorous understanding of the dosing rationale.

Predictive Performance of Physiologically Based Pharmacokinetic and Population Pharmacokinetic Modeling of Renally Cleared Drugs in Children.

Predictive performance of physiologically based pharmacokinetic (PBPK) and population pharmacokinetic (PopPK) models of drugs predominantly eliminated through kidney in the pediatric population was evaluated. After optimization using adult clinical data, the verified PBPK models can predict 33 of 34 drug clearance within twofold of the observed values in children 1 month and older. More specifically, 10 of 11 of predicted clearance values were within 1.5-fold of those observed in children between 1 month and 2 years old. The PopPK approach also predicted 19 of 21 drug clearance within twofold of the observed values in children. In summary, our analysis demonstrated both PBPK and PopPK adult models, after verification with additional adult pharmacokinetic (PK) studies and incorporation of known ontogeny of renal filtration, could be applied for dosing regimen recommendation in children 1 month and older for renally eliminated drugs in a first-in-pediatric study.