Benjamin Victor Ineichen

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Assistant Professor (Tenure Track) for Medical Data Science

University of Bern

Switzerland

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About

Dr. Benjamin Victor Ineichen is an Assistant Professor (Tenure Track) for Medical Data Science at the University of Bern, Switzerland. His research primarily focuses on systematic reviews in medical studies, particularly concerning animal-to-human translation in drug development and multiple sclerosis. Recent publications address topics such as the completion timelines of systematic reviews, the quality and trends of animal studies, and factors influencing therapeutic interventions' regulatory approval.

Recent Grants

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ANIMONE: An in vivo data warehouse for neuroscience – biocuration of preclinical research to inform optimization and exploitation of preclinical studies

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Exploring comparative effectiveness of disease modulatory treatments and its effect on different types of disease processes in relapsing-remitting multiple sclerosis patients using novel magnetic resonance imaging measures and fluid biomarkers

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Nogo-A Neutralisation as a Potential Novel Therapy for Multiple Sclerosis, Experimental Studies in Rats

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Benchmarking translational performance of 3D culture models against animal models in neuroscience – How well can 3D culture models replace animal experiments for drug testing?

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The Brainbox - a Tool to Facilitate Correlation of Brain Magnetic Resonance lmaging to Histopathology

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Articles (10)

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2025

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2024

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2024

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2024

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2024

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2024

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2024

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2024

Collaborators (1)

Fredrik Piehl

Karolinska Institutet

SWEDEN

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Benjamin Victor Ineichen

Research Interests

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About

Recent Grants

Articles (10)

How long does it take to complete and publish a systematic review of animal studies?

Quality, topics, and demographic trends of animal systematic reviews - an umbrella review

Misdiagnosis and underdiagnosis of multiple sclerosis: A systematic review and meta-analysis

Which experimental factors govern successful animal-to-human translation in multiple sclerosis drug development? A systematic review and meta-analysis

STEED: A data mining tool for automated extraction of experimental parameters and risk of bias items from in vivo publications

Systematic review and meta-analysis of preclinical studies

Analysis of animal-to-human translation shows that only 5% of animal-tested therapeutic interventions obtain regulatory approval for human applications

Clinical and neuroimaging phenotypes of autoimmune glial fibrillary acidic protein astrocytopathy: A systematic review and meta-analysis

Cytotoxic lesions of the corpus callosum: a systematic review

Factors associated with low health-related quality of life in persons with multiple sclerosis: A quantile-based segmentation approach

Collaborators (1)

Fredrik Piehl

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