Drug Discovery 2021 After the Storm: Re-connect, Re-invent, Re-imagine

Coding cells for health: building translational disease models for drug discovery and therapeutics

Tue19 Oct11:30am(30 mins)
Where:
Hall 1C
Speaker:
Speaker:

Abstract

One of the main problems underlying the poor translatability of preclinical findings is the lack of relevant and sustainable human cell models. Developing better tools for drug development could not only improve the relevance and consistency of data, but also reduce the cost and time spent on identifying novel targets. bit.bio offers unique cell models to study healthy and disease biology. Next generation opti-ox™ cellular reprogramming technology* enables the precisely controlled expression of a specific combination of transcription factors. This code drives the deterministic induction of a new cell identity from hiPSCs, resulting in mature cells that are functional within days and provide reliable high quality human cellular models. This innovative “cell coding” approach enables scalable and consistent supply of human cells. Using CRISPR/Cas-9 gene editing we can furthermore introduce pathological mutations into opti-ox reprogrammed glutamatergic neurons. While the mutation(s) drive the disease phenotype, the parental cells serve as a genetically matched control. This isogenic pairing will help to decipher single genetic contributions in CNS disorders such as TAU-driven frontotemporal dementia, Huntington’s or Parkinson’s diseases. The future of CNS research can be transformed with the aid of relevant human disease models. The combination of bit.bio’s innovative cellular reprogramming approach with the introduction of disease-associated mutations has the potential not only to improve clinical translation, but revolutionise drug development workflows. * Pawlowski M, et al. Stem Cell Reports. 8(4), 803-812, 2017

Hosted By

ELRIG

The European Laboratory Research & Innovation Group Our Vision : To provide outstanding, leading edge knowledge to the life sciences community on an open access basis

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