Real-World Evidence in Drug Development and Evaluation

By: Harry Yang (Editor), Binbing Yu (Editor)

Write A Review

eText | 11 January 2021 | Edition Number 1

At a Glance

Format
ePUB

eText

$100.10

or 4 interest-free payments of $25.02 with

Instant online reading in your Booktopia eTextbook Library *

Read online on

Desktop

Tablet

Mobile

Not downloadable to your eReader or an app

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

Real-world evidence (RWE) has been at the forefront of pharmaceutical innovations. It plays an important role in transforming drug development from a process aimed at meeting regulatory expectations to an operating model that leverages data from disparate sources to aid business, regulatory, and healthcare decision making. Despite its many benefits, there is no single book systematically covering the latest development in the field.

Written specifically for pharmaceutical practitioners, Real-World Evidence in Drug Development and Evaluation, presents a wide range of RWE applications throughout the lifecycle of drug product development. With contributions from experienced researchers in the pharmaceutical industry, the book discusses at length RWE opportunities, challenges, and solutions.

Features

Provides the first book and a single source of information on RWE in drug development
Covers a broad array of topics on outcomes- and value-based RWE assessments
Demonstrates proper Bayesian application and causal inference for real-world data (RWD)
Presents real-world use cases to illustrate the use of advanced analytics and statistical methods to generate insights
Offers a balanced discussion of practical RWE issues at hand and technical solutions suitable for practitioners with limited data science expertise