Publications associées à Preclinical combination therapy of the investigational drug NAMI-A(+) with doxorubicin for mammary cancer

Cyclic Peptides for Drug Development

Christian Heinis, Xinjian Ji, Alexander Lund Nielsen

Cyclic peptides are fascinating molecules abundantly found in nature and exploited as molecular format for drug development as well as other applications, ranging from research tools to food additives. Advances in peptide technologies made over many years ...

Wiley-VCH Verlag GmbH2024

Methods for high-throughput synthesis and screening of peptide libraries

Zsolt Bognár

Macrocycles provide an attractive modality for drug development but the identification of ligands to targets of interest is hindered by the lack of large macrocyclic compound libraries for high-throughput screening. A strategy to efficiently synthesize lar ...

EPFL2024

Clinically compliant cryopreservation of differentiated retinal pigment epithelial cells

Gioele La Manno, Alex Russell Lederer, Cheng Zhao

Background aims: Age-related macular degeneration (AMD) is the most common cause of blindness in elderly patients within developed countries, affecting more than 190 million worldwide. In AMD, the retinal pigment epithelial (RPE) cell layer progressively d ...

Elsevier Sci Ltd2024

Unveiling breast cancer metastasis through an advanced X-ray imaging approach

Marianne Liebi

Breast cancer is a significant global health burden, causing a substantial number of deaths. Systemic metastatic tumour cell dissemination is a major cause of poor outcomes. Understanding the mechanisms underlying metastasis is crucial for effective interv ...

Nature Portfolio2024

The predictive capacity of in vitro preclinical models to evaluate drugs for the treatment of retinoblastoma

Paul Joseph Dyson, Irina Sinenko, Roland Christopher Turnell-Ritson

Retinoblastoma is a rare childhood cancer of the eye. Of the small number of drugs are used to treat retinoblastoma, all have been repurposed from drugs developed for other conditions. In order to find drugs or drug combinations better suited to the improv ...

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD2023

Optimised three-dimensional in vitro retinoblastoma models tailored for drug discovery and clinical translatability

Irina Sinenko

Retinoblastoma, while relatively rare, stands as the most prevalent intraocular cancer. In Switzerland, the survival rate approaches 100%, but it drops to less than 50% in low-income countries. The current treatment options for retinoblastoma rely on a lim ...

EPFL2023

Alchemical analysis of FDA approved drugs

Philippe Schwaller, Daniel Probst, Jean-Louis Reymond, Markus Orsi

Chemical space maps help visualize similarities within molecular sets. However, there are many different molecular similarity measures resulting in a confusing number of possible comparisons. To overcome this limitation, we exploit the fact that tools desi ...

2023

Elucidating and modulating regulatory pathways so as to reprogram the immunosuppressive tumor microenvironment for therapeutic benefit

Agnieszka Alicja Chryplewicz

Glioblastoma (GBM) is the most frequent and highly malignant form of brain cancer. New therapeutic regimens are urgently needed as GBM patients present with a minimal response to currently-approved therapies. The goal of this project is to identify new the ...

EPFL2023

A multi-reservoir extruder for time-resolved serial protein crystallography and compound screening at X-ray free-electron lasers

Christoph Bostedt, Camila Bacellar Cases Da Silveira

Serial crystallography at X-ray free-electron lasers (XFELs) permits the determination of radiation-damage free static as well as time-resolved protein structures at room temperature. Efficient sample delivery is a key factor for such experiments. Here, we ...

Nature Portfolio2023

Medical and Personal Characteristics Can Predict the Risk of Lung Metastasis

Michele De Palma, Nahal Mansouri

Aims: Understanding the correlations between underlying medical and personal characteristics of a patient with cancer and the risk of lung metastasis may improve clinical management and outcomes. We used machine learning methodologies to predict the risk o ...

2023