Setup of a combined in silico/in cellulo screening platform for the identification of novel anti-fibrotic drugs (Fibro-screen)

Result

During this project, we established Ca²⁺ imaging strategies to monitor intracellular Ca²⁺ signaling in primary fibroblasts derived from fibrosis patients in real time. We demonstrated that inflammatory activation of fibroblasts is associated with a shortening of the Ca²⁺ oscillation period. In addition, we developed an automated image analysis pipeline that enables robust and standardized detection of Ca²⁺ signaling events.

Building on these findings, we now aim to perform a drug screening campaign using these functional readouts to identify novel anti-fibrotic compounds.

Description

Fibrosis, characterized by an excessive connective tissue deposition and organ dysfunction, remains a major unmet medical challenge due to the lack of effective anti-fibrotic therapies. To accelerate drug discovery, we will establish a combined experimental and computational screening platform based on primary fibroblasts isolated from capsules formed around implants in patients suffering from implant associated fibrosis.

Using 3D fibroblast culture and live-cell imaging of intracellular Ca²⁺ dynamics, which change upon fibroblast activation, we will monitor fibroblast-to-myofibroblast transition, a key driver of fibrosis. We will utilize machine learning models trained on Ca²⁺ signaling patterns and single-cell gene expression data to predict fibroblast activation states. The  integrated in silico/in cellulo platform will facilitate the identification of new anti-fibrotic drug candidates and open new avenues for fibrosis therapy.

Key data