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Real-World Evidence in Clinical Drug Development

Quanticate

Real-world evidence (RWE) is changing clinical drug development, bridging the gap between controlled clinical trial environments and the complexities of everyday patient experiences.

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Redefining Acceleration of the Drug Development Journey

PPD

It is hard to ignore some of the most pressing, long-term trends driving the push to accelerate innovation and progress in drug development. It demands a comprehensive, collaborative approach that reduces complexity and allows for just-in-time decision-making throughout the drug development journey. billion in 2023 to 1.2

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Prioritizing Patient Centricity in Generic Drug Development

Drug Patent Watch

The pharmaceutical industry has faced significant challenges in recent years, including the loss of patents, increased regulatory scrutiny, and rising research and development costs. Patient centricity involves designing… Source

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The Science Behind Generic Drug Development: A Deep Dive

Drug Patent Watch

Generic drug development is a complex process that involves rigorous scientific research and regulatory assessments. Food and Drug Administration (FDA) plays a crucial role in ensuring the quality and efficacy of generic drugs through various programs and guidelines.

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Deliver Fast, Flexible Clinical Trial Insights with Spotfire

Clinical research has entered a new era, one that requires real-time analytics and visualization to allow trial leaders to work collaboratively and to develop, at the click of a mouse, deep insights that enable proactive study management.

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Q&A: How to jump-start new psychiatric and neurological drug development

Broad Institute

Brain disorders are difficult to study and many drug candidates have failed in clinical trials, causing pharmaceutical companies to reduce their investments or even exit the field entirely. We all recognize the vast, unmet medical need.

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Large language models reshaping molecular biology and drug development

Chemical Biology and Drug Design

Exploring the transformative impact of large language models (LLMs) in molecular biology and drug development, discussing potential areas of applications and breakthroughs in personalized therapies. While enhancing molecular biology aspects, we also address ethical concerns ensuring responsible application of these models.