Optimization of Pharmaceutical R&D Programs and Portfolios - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Optimization of Pharmaceutical R&D Programs and Portfolios write by Zoran Antonijevic. This book was released on 2014-10-10. Optimization of Pharmaceutical R&D Programs and Portfolios available in PDF, EPUB and Kindle. 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.
Bayesian Methods in Pharmaceutical Research
Bayesian Methods in Pharmaceutical Research - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Bayesian Methods in Pharmaceutical Research write by Emmanuel Lesaffre. This book was released on 2020-04-15. Bayesian Methods in Pharmaceutical Research available in PDF, EPUB and Kindle. 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.
Portfolio Optimization in Early Drug R&D
Portfolio Optimization in Early Drug R&D - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Portfolio Optimization in Early Drug R&D write by Ravi Badwe. This book was released on 2019. Portfolio Optimization in Early Drug R&D available in PDF, EPUB and Kindle. Pharmaceutical R&D involves significant uncertainty, including high attrition rate and long time for a project to progress from a target identification phase to commercial launch. Despite this uncertainty, senior leaders must make decisions about R&D portfolio, the impact of which may not be observable for many years. Hence the purpose of this thesis is to understand the current state of Pharmaceutical R&D portfolio management and identify the gaps in R&D portfolio management research. The literature survey revealed that though there are many qualitative and quantitative approaches for the portfolio management of projects in the development phase (i.e. from pre-clinical to phase 3.), the topic of portfolio management in the drug discovery phase (i.e. target validation to lead optimization) have not been well covered in the literature. Hence the problem statement of this thesis is to develop a portfolio management approach for drug discovery. Portfolio management in pharmaceutical drug discovery space is not only a mathematics problem but also a representation problem in terms of activities, resources, decisions, dependencies, and uncertainties. There is something about the nature of the scope of early research in pharma which makes it different from downstream phases and respective parallels in other sectors. Improved representation can lead to improved prediction in drug discovery phase. Hence as the first step, structured survey was conducted to listen to insights from an experienced professional in the drug discovery domain at NIBR (Novartis Institute of Biomedical Research) to build the required understanding about discovery phase. The survey results helped in identification of the biology, chemistry, medical, marketing, and strategy factors generally taken into consideration during drug discovery project prioritization. Resource allocation is not considered during project prioritization - even though resource allocation determines the cycle-time that in turn influences the probability of project to reach pre-clinical phase. Proposed semi-quantitative portfolio management approach, which is based on the survey results, incorporates three key aspects of drug discovery project - scope feasibility (science), desirability (market and strategy), and time feasibility (resource allocation and cycle time). Proposed criterion based model for computing scope feasibility and desirability can be uniformly and transparently applied to all the projects across different disease areas and requires discussion between concerned teams to generate required scores. Also, proposed resource allocation model will enable portfolio management teams to generate multiple scenarios (trade spaces) on scope feasibility, time feasibility, and desirability dimensions. Based on the thresholds, which can be calculated from past data, portfolio team and management in conjunction with other teams such as disease area representatives, chemistry team, marketing etc. can decide the best scenario. The future work needs to focus on validating the proposed portfolio management approaches and models with the real data from past projects in the drug discovery phase in order to enable to organization-wide implementation.
Platform Trial Designs in Drug Development
Platform Trial Designs in Drug Development - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Platform Trial Designs in Drug Development write by Zoran Antonijevic. This book was released on 2018-12-07. Platform Trial Designs in Drug Development available in PDF, EPUB and Kindle. 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.
Quantitative Decisions in Drug Development
Quantitative Decisions in Drug Development - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Quantitative Decisions in Drug Development write by Christy Chuang-Stein. This book was released on 2021-09-03. Quantitative Decisions in Drug Development available in PDF, EPUB and Kindle. 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.
