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Very little has been published on optimization of pharmaceutical portfolios. Moreover, most of published literature is coming from the commercial side, where probability of technical success (PoS) is treated as fixed, and not as a consequence of development strategy or design. In this book there is a strong focus on impact of study design on PoS and ultimately on the value of portfolio. Design options that are discussed in different chapters are dose-selection strategies, adaptive design and enrichment. Some development strategies that are discussed are indication sequencing, optimal number of programs and optimal decision criteria. This book includes chapters written by authors with very broad backgrounds including financial, clinical, statistical, decision sciences, commercial and regulatory. Many authors have long held executive positions and have been involved with decision making at a product or at a portfolio level. As such, it is expected that this book will attract a very broad audience, including decision makers in pharmaceutical R&D, commercial and financial departments. The intended audience also includes portfolio planners and managers, statisticians, decision scientists and clinicians. Early chapters describe approaches to portfolio optimization from big Pharma and Venture Capital standpoints. They have stronger focus on finances and processes. Later chapters present selected statistical and decision analysis methods for optimizing drug development programs and portfolios. Some methodological chapters are technical; however, with a few exceptions they require a relatively basic knowledge of statistics by a reader.
Since the early 2000s, there has been increasing interest within the pharmaceutical industry in the application of Bayesian methods at various stages of the research, development, manufacturing, and health economic evaluation of new health care interventions. In 2010, the first Applied Bayesian Biostatistics conference was held, with the primary objective to stimulate the practical implementation of Bayesian statistics, and to promote the added-value for accelerating the discovery and the delivery of new cures to patients. This book is a synthesis of the conferences and debates, providing an overview of Bayesian methods applied to nearly all stages of research and development, from early discovery to portfolio management. It highlights the value associated with sharing a vision with the regulatory authorities, academia, and pharmaceutical industry, with a view to setting up a common strategy for the appropriate use of Bayesian statistics for the benefit of patients. The book covers: Theory, methods, applications, and computing Bayesian biostatistics for clinical innovative designs Adding value with Real World Evidence Opportunities for rare, orphan diseases, and pediatric development Applied Bayesian biostatistics in manufacturing Decision making and Portfolio management Regulatory perspective and public health policies Statisticians and data scientists involved in the research, development, and approval of new cures will be inspired by the possible applications of Bayesian methods covered in the book. The methods, applications, and computational guidance will enable the reader to apply Bayesian methods in their own pharmaceutical research.
If where an organization allocates its resources determines its strategy, why is it that so few companies actively manage the resource allocation process? "Optimizing Corporate Portfolio Management: Aligning Investment Proposals with Organizational Strategy" goes beyond platitudes about why you should use corporate portfolio management (CPM) by offering a practical methodology to bring this powerful discipline to your organization. "Optimizing Corporate Portfolio Management" takes an expansive view of where CPM can be utilized by demonstrating that it can be used across any business line, product group or functional area, e.g., IT, R&D, innovation, marketing, salesforce, capital expenditure, etc. CPM is appropriate anywhere discretionary investments are being selected and executed. As a result, other terms used to describe portfolio management such as IT portfolio management, enterprise portfolio management, and project portfolio management are all merely subsets or slices of CPM. The book is written by Anand Sanwal, an expert on CPM, who has led American Express' CPM discipline (referred to as American Express Investment Optimization). American Express' CPM efforts are widely recognized as the most extensive, substantial and progressive deployment of CPM across any organization. Sanwal avoids academic theories and consultant jargon to ultimately deliver pragmatic and proven recommendations on how to make CPM a reality. The book features a foreword by Gary Crittenden, former CFO and EVP of American Express, and several case studies from leading financial services, technology, and government organizations utilizing CPM. Additionally, the book has received significant praise from thought leaders at Google, HP, American Express, The CFO Executive Board, Gartner, Accenture Marketing Sciences, The Wharton School of Business and many others.
This unique guide and professional reference presents a structured framework for practitioners and students of project, program, and portfolio management to enhance their strategic and analytic capabilities in the evolving discipline of project portfolio management (PPM). It provides a practical, step-by-step approach to building competencies in categorizing, evaluating, optimizing, prioritizing, and managing an IT, pharmaceutical, biotech or other complex R&D-oriented portfolio of investments.
Portfolio Decision Analysis: Improved Methods for Resource Allocation provides an extensive, up-to-date coverage of decision analytic methods which help firms and public organizations allocate resources to 'lumpy' investment opportunities while explicitly recognizing relevant financial and non-financial evaluation criteria and the presence of alternative investment opportunities. In particular, it discusses the evolution of these methods, presents new methodological advances and illustrates their use across several application domains. The book offers a many-faceted treatment of portfolio decision analysis (PDA). Among other things, it (i) synthesizes the state-of-play in PDA, (ii) describes novel methodologies, (iii) fosters the deployment of these methodologies, and (iv) contributes to the strengthening of research on PDA. Portfolio problems are widely regarded as the single most important application context of decision analysis, and, with its extensive and unique coverage of these problems, this book is a much-needed addition to the literature. The book also presents innovative treatments of new methodological approaches and their uses in applications. The intended audience consists of practitioners and researchers who wish to gain a good understanding of portfolio decision analysis and insights into how PDA methods can be leveraged in different application contexts. The book can also be employed in courses at the post-graduate level.
Platform trials test multiple therapies in one indication, one therapy for multiple indications, or both. These novel clinical trial designs can dramatically increase the cost-effectiveness of drug development, leading to life-altering medicines for people suffering from serious illnesses, possibly at lower cost. Currently, the cost of drug development is unsustainable. Furthermore, there are particular problems in rare diseases and small biomarker defined subsets in oncology, where the required sample sizes for traditional clinical trial designs may not be feasible. The editors recruited the key innovators in this domain. The 20 articles discuss trial designs from perspectives as diverse as quantum computing, patient’s rights to information, and international health. The book begins with an overview of platform trials from multiple perspectives. It then describes impacts of platform trials on the pharmaceutical industry’s key stakeholders: patients, regulators, and payers. Next it provides advanced statistical methods that address multiple aspects of platform trials, before concluding with a pharmaceutical executive’s perspective on platform trials. Except for the statistical methods section, only a basic qualitative knowledge of clinical trials is needed to appreciate the important concepts and novel ideas presented.
This book focuses on important decision points and evidence needed for making decisions at these points during the development of a new drug. It takes a holistic approach towards drug development by incorporating explicitly knowledge learned from the earlier part of the development and available historical information into decisions at later stages. In addition, the book shares lessons learned from several select examples published in the literature since the publication of the first edition. The second edition reiterates the need for making evidence-based Go/No Go decisions in drug development discussed in the first edition. It substantially expands several topics that have seen great advances since the publication of the first edition. The most noticeable additions include three adaptive trials conducted in recent years that offer excellent learning opportunities, the use of historical data in the design and analysis of clinical trials, and extending decision criteria to the cases when the primary endpoint is binary. The examples used to illustrate the additional materials all come from real trials with some post-trial reflections offered by the authors. The book begins with an overview of product development and regulatory approval pathways. It then discusses how to incorporate prior knowledge into study design and decision making at different stages of drug development. Prior knowledge includes information pertaining to historical controls. To assist decision making, the book discusses appropriate metrics and the formulation of go/no-go decisions for progressing a drug candidate to the next development stage. Using the concept of the positive predictive value in the field of diagnostics, the book leads readers to the assessment of the probability that an investigational product is effective given positive study outcomes. Lastly, the book points out common mistakes made by drug developers under the current drug-development paradigm. The book offers useful insights to statisticians, clinicians, regulatory affairs managers and decision-makers in the pharmaceutical industry who have a basic understanding of the drug-development process and the clinical trials conducted to support drug-marketing authorization. The authors provide software codes for select analytical approaches discussed in the book. The book includes enough technical details to allow statisticians to replicate the quantitative illustrations so that they can generate information to facilitate decision-making themselves.
This book describes the way that pharmaceutical projects and programs are currently managed, and offers views from many highly experienced practitioners from within the industry on future directions for drug program management. The book integrates portfolio, program, and project management processes as fundamental for effective and efficient drug product development. Contributing expert authors provide their view of how the projectization approach can be taken forward by the drug industry over the coming years.
The pharmaceutical industry is one of today’s most dynamic and complex industries, involving commercialization of cutting-edge scientific research, a huge web of stakeholders (from investors to doctors), multi-stage supply chains, fierce competition in the race to market, and a challenging regulatory environment. The stakes are high, with each new product raising the prospect of spectacular success—or failure. Worldwide revenues are approaching $1 trillion; in the U.S. alone, marketing for pharmaceutical products is, itself, a multi-billion dollar industry. In this volume, the editors showcase contributions from experts around the world to capture the state of the art in research, analysis, and practice, and covering the full spectrum of topics relating to innovation and marketing, including R&D, promotion, pricing, branding, competitive strategy, and portfolio management. Chapters include such features as: · An extensive literature review, including coverage of research from fields other than marketing · an overview of how practitioners have addressed the topic · introduction of relevant analytical tools, such as statistics and ethnographic studies · suggestions for further research by scholars and students The result is a comprehensive, state-of-the-art resource that will be of interest to researchers, policymakers, and practitioners, alike.