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Data cleaning and harmonisation: A catalyst for innovation

Express Pharma

Data cleaning, the critical first step? Before scientists can harmonise data, they must clean it. By elim- inating the errors that arise from data entry, miscalculations, sensor malfunctions, or system glitches, scientists can build the data foundation required for harmonisation.

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How using AI in clinical trials accelerates drug development

Pharmaceutical Technology

Drug development is already a difficult endeavor, with the vast majority of R&D efforts failing to produce a market-worthy product. Even reaching the clinical trial phase offers no guarantees, as only 12% of such drugs receive U.S. While this process is essential, it’s also slow, expensive and unpredictable.

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Is a lack of real-time data holding trials back?

pharmaphorum

As the amount and types of data expand exponentially, this problem only intensifies. Yet, ironically, that very growth in data sources may be one reason solutions have been slow to take hold. Clearing redundant data then becomes difficult, and programming complex edit checks becomes impossible. Potentially catastrophic setbacks.

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Data integrity considerations in Pharma and Life Sciences

European Pharmaceutical Review

Data integrity is the term used to describe the accuracy, consistency and reliability of data throughout its lifecycle. In the pharmaceutical/life sciences industries, maintaining data integrity is crucial given its role in making critical decisions that shape outcomes from drug development to human health.

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How a new investment is powering a revolution in clinical trial operations

pharmaphorum

Iddo Peleg (CEO, and one of the four co-founders of YonaLink) and Gav Martell (co-founder and vice president of business development) discussed how a recent $6 million funding round led by Debiopharm Innovation Fund will support their mission to transform clinical trials and bring lifesaving therapies to market faster.

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How blockchain can revolutionise medical records and save lives

pharmaphorum

Many practitioners have expressed the feeling that EHRs cause far too much of their time ultimately being spent on data entry. Additionally, issues such as poor quality documentation due to template-based reporting, and incompatibilities between different systems have further caused headaches and increased inefficiencies.