End To End Data Analytics For Product Development
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End-to-end Data Analytics for Product Development
Author: Rosa Arboretti Giancristofaro
language: en
Publisher: John Wiley & Sons
Release Date: 2020-02-14
An interactive guide to the statistical tools used to solve problems during product and process innovation End to End Data Analytics for Product Development is an accessible guide designed for practitioners in the industrial field. It offers an introduction to data analytics and the design of experiments (DoE) whilst covering the basic statistical concepts useful to an understanding of DoE. The text supports product innovation and development across a range of consumer goods and pharmaceutical organizations in order to improve the quality and speed of implementation through data analytics, statistical design and data prediction. The book reviews information on feasibility screening, formulation and packaging development, sensory tests, and more. The authors – noted experts in the field – explore relevant techniques for data analytics and present the guidelines for data interpretation. In addition, the book contains information on process development and product validation that can be optimized through data understanding, analysis and validation. The authors present an accessible, hands-on approach that uses MINITAB and JMP software. The book: • Presents a guide to innovation feasibility and formulation and process development • Contains the statistical tools used to solve challenges faced during product innovation and feasibility • Offers information on stability studies which are common especially in chemical or pharmaceutical fields • Includes a companion website which contains videos summarizing main concepts Written for undergraduate students and practitioners in industry, End to End Data Analytics for Product Development offers resources for the planning, conducting, analyzing and interpreting of controlled tests in order to develop effective products and processes.
Deep Data Analytics for New Product Development
This book presents and develops the deep data analytics for providing the information needed for successful new product development. Deep Data Analytics for New Product Development has a simple theme: information about what customers need and want must be extracted from data to effectively guide new product decisions regarding concept development, design, pricing, and marketing. The benefits of reading this book are twofold. The first is an understanding of the stages of a new product development process from ideation through launching and tracking, each supported by information about customers. The second benefit is an understanding of the deep data analytics for extracting that information from data. These analytics, drawn from the statistics, econometrics, market research, and machine learning spaces, are developed in detail and illustrated at each stage of the process with simulated data. The stages of new product development and the supporting deep data analytics at each stage are not presented in isolation of each other, but are presented as a synergistic whole. This book is recommended reading for analysts involved in new product development. Readers with an analytical bent or who want to develop analytical expertise would also greatly benefit from reading this book, as well as students in business programs.
Sustainable Pharmaceutical Product Development and Optimization Processes
This book offers unparalleled insight into the convergence of sustainability and pharmaceutical product development, with a specific focus on optimization processes. By addressing the urgent demand for more environmentally conscious and efficient strategies in the drug development industry, particularly in an era where the world faces the mounting challenges posed by climate change, the book provides a comprehensive guide for integrating sustainability principles throughout the pharmaceutical product lifecycle, directly contributing to the United Nations Sustainable Development Goals (SDGs), such as SDG 12 (Responsible Consumption and Production) and SDG 13 (Climate Action). The chapters cover key topics, including the application of green chemistry, eco-design principles, sustainable sourcing of raw materials, waste reduction strategies, and the use of renewable energy in pharmaceutical manufacturing processes. Throughout the book, case studies are integrated, offering practical insights and concurrently highlighting the economic and environmental advantages of sustainable practices, thereby addressing skepticism regarding the feasibility and profitability of such initiatives. The book also discusses regulatory considerations, ethical implications, and the challenges and opportunities associated with moving toward more sustainable practices in pharmaceutical development. Importantly, this book seeks to solve the problem of the knowledge gap and lack of practical resources for professionals in the pharmaceutical industry who aspire to implement sustainable and optimized processes. This work consolidates a network of professionals and scholars keenly focused on future sustainability challenges, developing enhancement methodologies, and sharing successful strategies for implementing eco-friendly practices in pharmaceutical sectors worldwide, ultimately contributing to the global effort to achieve the SDGs by 2030. With a focus on pharmaceutical professionals, researchers, academicians, and students, the book serves as a valuable reference for those involved in drug development and process optimization. Policymakers and regulatory bodies might also find it insightful, as it addresses current landscapes, challenges, and future directions in sustainable pharmaceutical product development.