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Dangerous data delays – a real-time problem

pharmaphorum

Delayed clinical trial data delivery is a growing problem for pharmaceutical companies and one that can have catastrophic consequences for the development of their promising pipeline candidates. But there are ways to improve this situation, as Remarque Systems’ recent Is a lack of real-time data holding trials back?

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Important factors to consider when working with CRFs

pharmaphorum

Well-designed forms must: Gather data that’s complete, accurate, and of high quality. Be unambiguous and allow for accurate data entry. Avoid gathering more data than what is needed. Provide form completion guidelines to reduce data capture and data entry issues. Avoid duplication. Get user feedback.

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Important factors to consider when working with CRFs

pharmaphorum

Well-designed forms must: Gather data that’s complete, accurate, and of high quality. Be unambiguous and allow for accurate data entry. Avoid gathering more data than what is needed. Provide form completion guidelines to reduce data capture and data entry issues. Avoid duplication. Get user feedback.

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Intelligent Automation in Pharmaceutical Industry (AI & ML)

PharmaShots

The article focuses on the integration of automation with Artificial Intelligence (AI) and Machine Learning (ML). This article provides an informative account of intelligent automation, the key differences between AI & ML, their importance, and a potent eight-step roadmap to implementation.

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How data is crucial to the relaunch of the Cancer Moonshot

pharmaphorum

In this article, Ben Hargreaves takes a look at the renewed effort to tackle deaths from cancer in the US through the Cancer Moonshot. Central to the initiative is the aim to gather data from willing participants that can provide greater insights into cancer development and treatment over time.

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Advancement through adversity: how Covid-driven innovations are becoming best practices for pharmacovigilance

Pharmaceutical Technology

The process of actioning case reports is typically split into six stages: case receipt, triage (deciding whether a case should be classified as serious, non-serious or a non-event), data entry, quality review, medical review, and submission. Redesigning the translation process to increase efficiency.

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Methodology to Define a Pharma 4.0™ Roadmap

ISPE

Based on robust data flows, aspects and required controls can be assessed in detail—for example, manual data entry, interfaces between systems, media change, data conversion, data migration, and data archiving. The concepts introduced here will be topics for future articles. ™ environment.