Efficacy Evaluation in the Era of Precision Medicine: The Scope for AI
Patient stratification and the use of real-world evidence in regulatory decision-making are two key areas where algorithms are having an impact on drug development. The two are linked: increased patient stratification makes it harder to recruit patients into randomized-controlled trials, increasing...
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| Autor principal: | |
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| Formato: | Capítulo de libro |
| Lenguaje: | inglés |
| Publicado: |
IntechOpen
2020
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| Materias: | |
| Acceso en línea: | https://www.intechopen.com/chapters/71925 |
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| Sumario: | Patient stratification and the use of real-world evidence in regulatory decision-making are two key areas where algorithms are having an impact on drug development. The two are linked: increased patient stratification makes it harder to recruit patients into randomized-controlled trials, increasing the pressure on drug developers to find alternative sources of evidence for showing efficacy. In addition to real-world evidence, we are also seeing the emergence of more efficient ‘master protocol trials’, where multiple targeted agents can be evaluated simultaneously. In this chapter, I will review these developments and investigate the limitations for AI in terms of demonstrating the efficacy of novel targeted agents. |
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| ISBN: | 978-1-78984-689-8 |
| DOI: | 10.5772/intechopen.90455 |