Anima claims ‘promising’ preclinical data for IPF drug candidate
Drug shows potential for IPF treatment by effectively disrupting the transformation of fibroblasts into fully differentiated myofibroblasts.
AI drug discovery company Anima Biotech has revealed encouraging preclinical results for its drug candidate addressing Idiopathic Pulmonary Fibrosis (IPF), an age-related condition in which the lungs become scarred and makes breathing difficult. The drug, designed to disrupt the transformation of fibroblasts into fully differentiated myofibroblasts, operates through a novel mRNA biology mechanism of action.

Leveraging its AI-powered mRNA platform, Anima identified the preclinical candidate, which showed potential in treating fibrotic diseases by demonstrating efficacy in inhibiting the deposition of extracellular matrix by myofibroblasts. The company says that the oral efficacy of the candidate in mouse IPF models showcased a significant safety-to-activity margin and outperformed standard-of-care drugs, notably reducing collagen production and fibrotic biomarkers in cells and tissue explants derived from IPF patients.

“Our platform’s ability to visualize mRNA biology and decode it with AI technology enables a deeper understanding of disease mechanisms, identification of novel targets, and discovery of drugs that can directly modify the disease phenotype,” said Yochi Slonim, co-founder and CEO of Anima.

Anima’s discovery platform combines mRNA biology with AI imaging technologies to visualize the life cycle of mRNA in cells and decode the underlying mRNA biology of diseases. Leveraging what the company claims is the world’s largest dataset of 2 billion mRNA biology images, the platform employs disease-specific mRNA image analysis neural networks to recognize disease signatures and pathways.

Anima has a range of discovery programs spanning immunology, oncology and neuroscience, and has strategic partnerships with pharmaceutical companies, including AbbVie, Takeda and Eli Lilly.

Anima claims ‘promising’ preclinical data for IPF drug candidate