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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., (© 2017 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The pharmaceutical industry continues to face significant challenges. Very few compounds that enter development reach the marketplace, and the investment required for each success can surpass $1.8 billion. Despite attempts to improve efficiency and increase productivity, total investment continues to rise whereas the output of new medicines declines. With costs increasing exponentially through each development phase, it is failure in phase II and phase III that is most wasteful. In today's development paradigm, late-stage failure is principally a result of insufficient efficacy. This is manifested as either a failure to differentiate sufficiently from placebo (shown for both novel and precedented mechanisms) or a failure to demonstrate sufficient differentiation from existing compounds. Set in this context, this article will discuss the role model-based drug development (MBDD) approaches can and do play in accelerating and optimizing compound development strategies through a series of illustrative examples.

Systems pharmacology is an emerging approach that sets out to use quantitative concepts rooted in the synergy between modeling and simulation on one hand and large-scale data collection and analysis on the other to investigate biological systems and design therapeutic interventions. Interest in this field has recently increased substantially, but so have perceived challenges and misunderstandings, especially related to implementation. This Commentary explores the opportunities and challenges in the rapidly evolving area of systems pharmacology from a drug discovery and development perspective.