Remove Clinical Development Remove Clinical Research Remove Trials
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The AI model that is changing clinical trial design

Drug Target Review

Clinical trials are expensive, slow and often limited by outdated design constraints. They offer patient-specific outcome predictions, generated using machine learning models trained on real historical clinical data. Digital twins offer a way forward. Unlearn is one of the few companies applying this approach at scale.

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How FSP Models Help Biotech Companies Augment Their Clinical Development Needs

PPD

Its ability to maneuver persistent drug development challenges, like patient recruitment, trial complexity and rising costs, will ultimately determine its success. This blog explores the value of functional service provider (FSP) models and how they help biotech companies augment their clinical development needs.

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Leveraging AI Solutions for Clinical Trial Efficiencies

PPD

As clinical trials become increasingly complex, particularly in decentralized trials and rare disease studies, sponsors experience increased challenges in site selection, forecasting and resourcing, and patient recruitment and enrollment. Discover how AI is used to optimize key aspects of clinical trial management.

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The rising impact of biomarkers in early clinical development

Drug Target Review

Advanced strategies and tools are being implemented to establish the safety and efficacy of new therapeutic modalities, with the development of new biomarkers becoming one of the most relevant approaches for enhancing the precision and utility of early-stage studies.

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Regulator and Funder? FDA’s Orphan Products Grants Program awards significant funding to help move promising treatments through clinical development

FDA Law Blog: Drug Discovery

Food and Drug Administration (FDA) plays a pivotal role in fostering the development of treatments for rare diseases through its Orphan Products Grants Program. Each year, FDA selects a limited number of clinical trials to fund to help sponsors pursue development of medical products for rare diseases and advance their field.

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Managing Opportunities and Risks in Generative AI Use for Clinical Research

PPD

Generative artificial intelligence (AI) has captured global attention for its transformative potential across industries, and nowhere is the promise greater — or more fraught — than in health care and clinical research. These domains are ripe for innovation. Errors jeopardize patient safety, regulatory compliance and trust.

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Navigating Clinical Development Challenges to Advance Idiopathic Pulmonary Fibrosis Treatments

PPD

The complexity of diagnosing IPF, understanding its root causes, and translating preclinical findings to clinical success make it a challenging disease for drug development. However, recent advancements and strategic approaches in clinical trials offer hope that additional treatments are on the way.