Webinaires

Part 1. The Future of Ethical Drug Discovery: The Role of Standardized Microenvironments in ex vivo disease models: presented by Arne Faisst, Ph.D.

The assimilation of the 3D CoSeedis in chip multi organoid technology™ heralds a new epoch in ex vivo disease modeling, engendering unprecedented insights into drug response kinetics and reshaping the landscape of pharmaceutical research. By faithfully emulating the intricacies of native tissue physiology within self-assembled microenvironment, this platform empowers investigators to make well-informed decisions across all facets of the drug development continuum. As we navigate towards a future characterized by precision medicine and ethical research imperatives, the 3D CoSeedis in chip technology™ emerges as an emblem of scientific innovation, propelling us towards a more sustainable and ethically conscientious trajectory in biomedical research.

 

Part 2.  Lung organoid imaging enables the capture of complex pathophysiology in pulmonary fibrosis and drug-induced interstitial lung diseases: presented by Yuki Yamamoto, Ph.D. M.D.

The particularly low success rate of phase 2 clinical trials in the respiratory disease area—where a wide variety of pathophysiological mechanisms such as infections, drug-induced injury, and fibrosis are involved—highlights the lack of human-relevant preclinical models for predicting drug efficacy and lung toxicity.

A critical challenge is the need to recapitulate the complex 3D architecture of the lung for accurate disease modeling of intractable respiratory conditions, especially those involving structural alterations such as pulmonary fibrosis.

To address these issues, HiLung has developed and commercialized iPS cell-derived respiratory cell systems, including organoids composed of highly functional cells.

In this presentation, we introduce our initiatives aimed at predicting clinical drug efficacy for pulmonary fibrosis and assessing lung toxicity using human-relevant preclinical lung organoid models. Imaging analysis plays a central role as a predictive readout in these models.

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