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Why intelligent automation is the future for regulation

pharmaphorum

To improve data confidence regulatory executives should take a four-step approach to change how they: Collect Data: Life sciences organisations should utilise cloud-based solutions with global access that facilitates one repository with a single source of truth and eliminates the use of local file sharing and servers.

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Life in phase III: How effective data management can support NHS Trusts to hit their targets

pharmaphorum

This document, which went out at the end of July, outlines exactly what providers need to be doing. While there are a number of variables, including clinical and physical capacity, post-COVID-19 social distancing restrictions and scheduling logistics, there is one common thread that ties them all together – data.

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Will AI Replace Pharma Jobs? What Experts Predict

Pharma Marketing Network

Tasks that are repetitive, data-heavy, or rules-based are most vulnerable. For example, medical data entry, pharmacovigilance documentation, and basic regulatory filing are increasingly handled by intelligent systems. Which pharma roles are most affected by AI? Can pharma marketers benefit from AI?

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Achieving commercial excellence with data-driven decisions

pharmaphorum

Together, these groups compile vast amounts of data, including rich information on patient populations, target customers, and the competitive landscape. But after months of effort, in most cases, the usefulness of this data begins and ends in a static slide deck or spreadsheet.

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Revolutionizing Nursing: Eliminating Strain and Burnout Through Technological Efficiency

indispensable health

Liberating Nurses from Administrative Shackles Nurses are skilled caregivers, not data entry specialists. Technology offers a lifeline by automating documentation, report generation, and data entry: A. Technology bridges the gap, enabling swift and accurate exchange of information among healthcare teams: A.

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

pharmaphorum

Indeed, handling such data and finding resources to clean and manage it was overwhelmingly cited by Pharma Intelligence respondents as the most urgent challenge facing researchers over the next five years. Clearing redundant data then becomes difficult, and programming complex edit checks becomes impossible.

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Considerations for safety data migration methods

European Pharmaceutical Review

Any discrepancies should be documented using a Known Difference document and the solutions or acceptance of the discrepancy are then agreed upon. Once all cases have been entered and reviewed and any discrepancies resolved, the data transfer is considered complete and a data migration summary report should be issued.