Advancing medical research through real-world patient experiences

// background

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Endometriosis is a complex, highly individualized condition that remains poorly understood among both society and healthcare providers. In collaboration with Prof. Dr. Sylvia Mechsner at the Endometriosis Center, Charité — Medical University Berlin, we've built one of the largest databases of patient-reported experiences with endometriosis and adenomyosis.

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// research focus

• Mapping diagnostic and treatment pathways from first symptom onward
• Identifying causal factors behind diagnostic delays
• Examining socioeconomic and sociopsychological impacts
• Analysing patient-reported outcomes from multi-modal therapies

// what we capture

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2,800+ real-world journeys from initial symptoms through to diagnosis, medical consultations, and treatments. Aggregated sociodemographic data across all DACH countries. Subjective experiences, advice patients want to share, and outcomes that trial data doesn't capture.

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// eligibility

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Adults with a diagnosis of endometriosis or adenomyosis, or currently undergoing diagnostic work-up. Open to patients across Germany, Austria and Switzerland.

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// research team

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Prof. Dr. Sylvia Mechsner — Principal investigator, Charité
Katrina Holmes — MD, Charité / Tübingen
Ann-Katrin Abeler — Doctoral student, Charité
Zeinab Soleimani — PhD student, HPI

// background

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280 million people worldwide live with major depressive disorder (MDD). Although there is a well-populated therapeutic landscape of antidepressants, fewer than 6% of patients fully benefit from their current therapeutic journey. Remission rates remain stubbornly low. OPADE is developing an AI / ML-driven predictive tool to support clinical decision-making in MDD. The project focuses on the gut–brain axis, studying how genetics, epigenetics, microbiome, and inflammatory networks combine to shape treatment response.

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// research focus

• Identify patient profiles that predict and optimize antidepressant efficacy, increasing remission and reducing functional impairment
• Map correlations between neuroinflammatory indices — microbiome, metabolomics, immune profile, epigenomic and enzymatic markers — and treatment outcomes
• Evaluate molecular and non-molecular biomarkers as predictors of recurrence
• Improve diagnostic accuracy for primary prevention
• Trace the onset of depressive symptoms retrospectively from adolescence
• Establish how blood biomarkers correlate with other disease-specific biomarkers

// what we capture

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Patients share their daily experience through a personalized chatbot — symptoms, medications, therapies, and key events — feeding into the AI / ML predictive tool.

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// eligibility

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Adults and adolescents aged 14–50 with major depressive disorder. Recruitment across six EU and international countries.

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// research team

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Here is the list of research partners

Project is funded by the European Union