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Research Clinic Research Clinic

Research

More than a decade of work on safer, more precise drug therapy. From research with universities and insurers to software that runs at the point of care.

University Hospital Zurich

2009 to 2013

At the Department of Clinical Pharmacology and Toxicology, we started where drug harm becomes visible: in hospital data. We compared how well different data sources detect adverse drug events, and built a transparent model to rate drug interactions.

Performance of different data sources in identifying adverse drug events in hospitalized patients
Egbring M, Far E, Knuth A, Roos M, Kirch W, Kullak-Ublick GA. European Journal of Clinical Pharmacology. 2011;67(9):909-918.
DOI 10.1007/s00228-011-1020-9 · PMID 21394526

Validation of a transparent decision model to rate drug interactions
Far E, Curkovic I, Byrne K, Roos M, Egloff I, Dietrich M, Kirch W, Kullak-Ublick GA, Egbring M. BMC Pharmacology and Toxicology. 2012;13(1):7.
DOI 10.1186/2050-6511-13-7 · PMID 22950884

Innovation Prize of Swiss Insurances

2014

Our Sanitas TeleHealth project, under the patronage of Otto Bitterli, received the Innovation Prize of Swiss Insurances. It offered personalised telemedical support to patients taking multiple medications, to improve safety, adherence and clinical outcomes.

Helsana Innovation Fund

2014 to 2017

Together with the University of Zurich, ETH Zurich and Helsana, and under the patronage of Prof. Dr. med. Thomas Szucs, we researched medication safety. We built predictive models for drug-drug-gene interactions that set new standards in risk prediction.

Large-scale data analysis identified patients at risk and proved that dangerous interactions can be detected early. It also showed the limit: in daily practice, the case volumes can only be managed with clinical intelligence at the moment of prescribing, inside the workflow of physicians and pharmacists.

Analysis of drug-drug interactions in Swiss claims data using tizanidine and ciprofloxacin as a prototypical contraindicated combination
Jödicke AM, Curkovic I, Zellweger U, Tomka IT, Neuer T, Kullak-Ublick GA, Roos M, Egbring M. Annals of Pharmacotherapy. 2018;52(10):983-991.
DOI 10.1177/1060028018775914 · PMID 29749261

Prediction of health care expenditure increase: how does pharmacotherapy contribute?
Jödicke AM, Zellweger U, Tomka IT, Neuer T, Curkovic I, Roos M, Kullak-Ublick GA, Sargsyan H, Egbring M. BMC Health Services Research. 2019;19(1):953.
DOI 10.1186/s12913-019-4616-x · PMID 31829224

Medication as a risk factor for hospitalization due to heart failure and shock: a series of case-crossover studies in Swiss claims data
Jödicke AM, Burden AM, Zellweger U, Tomka IT, Neuer T, Roos M, Kullak-Ublick GA, Curkovic I, Egbring M. European Journal of Clinical Pharmacology. 2020;76(7):979-989.
DOI 10.1007/s00228-020-02835-x · PMID 32270213

Preventable patient harm Big data analytics Case management Patients at risk Partners Technology overview Prescription view Interaction matrix Interactions in 3D Clinical intelligence, 2011 to 2021 Receptor in 3D

Lohfert Prize

2017

The Lohfert Prize went to the mobile app developed by the Clinical Pharmacology and Toxicology team at the University Hospital Zurich together with the Swiss Tumor Institute, under the patronage of Prof. Andreas Trojan. It records symptoms and treatment side effects during cancer therapy.

A mobile app to stabilize daily functional activity of breast cancer patients in collaboration with the physician: a randomized controlled clinical trial
Egbring M, Far E, Roos M, Dietrich M, Brauchbar M, Kullak-Ublick GA, Trojan A. Journal of Medical Internet Research. 2016;18(9):e238.
DOI 10.2196/jmir.6414 · PMID 27601354

Effect of collaborative review of electronic patient-reported outcomes for shared reporting in breast cancer patients: descriptive comparative study
Trojan A, Bättig B, Mannhart M, Seifert B, Brauchbar MN, Egbring M. JMIR Cancer. 2021;7(1):e26950.
DOI 10.2196/26950 · PMID 33729162

epha.health

2017 to 2021

Entirely self-funded, we built a digital assistant that combines language models with mechanistic simulations to predict the risk of drug-drug-gene interactions. With epha.health, we reached the top 10 of the Swiss Innovation Challenge 2021, among more than 100 innovations from all sectors.

Our medical services funded this work. That kept us independent and in direct contact with the people who use our reviews every day: physicians and pharmacists.

Predictive drug safety, 2021 Market awareness Web traffic, 2022 Static mechanistic model Model code Model generalization Performance for drugs and genes Mechanistic static models for regulatory filing Team

Clinical consultations

Since 2022

Our research now reaches patients directly. We review complex medication plans, assess drug interactions, give second opinions on drug therapy, and determine when pharmacogenetic testing helps and what its results mean for treatment.

In Switzerland, our consultations are reimbursed by health insurance. Privately insured patients can reach us from anywhere in the world.

A decade of research, applied to one patient at a time.

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