Real-world evidence in drug development and evaluation / authored by Harry Yang and Binbing Yu.

Real-world evidence in drug development and evaluation / authored by Harry Yang and Binbing Yu.

First edition.

9780429676819 (electronic book)
0429676816 (electronic book)
9780429676826 (electronic book)
0429676824 (electronic book)
9780429398674 (electronic book)
0429398670 (electronic book)
9780429676802 (electronic book)
0429676808 (electronic book)
9780367026219

Boca Raton, FL : Chapman & Hall/CRC, 2021.

©2021

English

1 online resource ( xii, 178 pages) : illustrations (black and white)

10.1201/9780429398674 doi

RM301.25 .Y36 2021

615.1/9

1. Using Real-world Evidence to Transform Drug Development: Opportunities and ChallengesHarry YangIntroductionTraditional Drug Development ParadigmDrug Development ProgressLimitations of Traditional Randomized Controlled TrialsReal World Data and Real World EvidenceReal World DataReal World EvidenceDifferences between RWE and Outcomes of RCTRegulatory PerspectiveProductivity ChallengeFDA Critical Path InitiativeRegulatory Perspectives Pertaining to RWEHistorical Approval Based on RWEAccess to RWDOpportunities of RWE in Drug DevelopmentEarly DiscoveryClinical Study Design and FeasibilityStudy ExecutionMarketing ApplicationProduct LaunchProduct Lifecycle ManagementChallenges with RWE Data Access and QualityTechnological BarriersMethodological ChallengesLack of Data TalentsRegulatory RisksConcluding Remarks2. Evidence derived from real world data: utility, constraints and cautionsDeepak Khatry What is RWD in the context of drug development and clinical practiceWhy is RWD important? For what purposes can RWD be useful? What study designs and statistical methods will be necessary to ensure high quality RWE? Some application examples 3. Real-world evidence from population-based cancer registry Binbing Yu Introduction Statistical methods for population-based cancer registry Application to small cell lung cancer survivalDiscussions 4. External Control using RWE and Historical Data in Clinical Development Qing Li, Guang Chen, Jianchang Lin, Andy Chi and Simon DaviesIntroduction of using RWE and Historical Data in Clinical Development Single Arm Trial Using External Control for Initial Indication Comparison Across Trials with External Control for Label Expansion Important Considerations When Designing Studies and Analyzing Data UsingExternal Control in Clinical Development 5. Bayesian method for assessing drug safety using real-world evidence Binbing Yu IntroductionBayesian sensitivity analysis for unobserved confoundersBayesian evidence synthesis using meta-analysisDiscussion 6. Real-World Evidence for Coverage and Payment Decisions Saurabh Aggarwal*, Hui Huang*, Ozlem Topaloglu, Ross SelbyIntroductionDefining valueContracting trend/value-based agreementImportance of RWE for demonstrating valueUse of RWE by payers and health technology assessment agencies7: Causal Inference for Observational Studies/Real-World Data Bo LuCausal Inference with Real-World DataPropensity Score Adjustment for Observational StudiesSensitivity Analysis for Hidden BiasCase study: Propensity Score Matching Design and Sensitivity Analysis for Trauma Care Evaluation 8. Introduction to Artificial Intelligence and Deep Learning with a Case Study in Analyzing Electronic Health Records for Drug Development Xiaomao Li and Qi Tang Introduction to AI and overview of break-throughts of AI in drug developmentA minimalist overview of deep learning methodsIntroduction of the big data in clinical space: electronic health record A case study of using deep learning to analyze HER Introduction to Python and cloud computing

Includes bibliographical references and index.

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Electronic reproduction. Ann Arbor, MI Available via World Wide Web.

Description based on online resource; title from digital title page (viewed on March 19, 2021).

Chapman & Hall/CRC biostatistics series.

Print version: 9780367026219

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