Precision Cellular Reprogramming for Scalable and Consistent Human Neurodegenerative Disease Models

In this talk, Madeleine Garrett, Field Application Specialist at bit.bio, will discuss the challenges surrounding the methods of generating human disease cell models, and how a new precision cellular reprogramming technology is overcoming inefficiencies and inconsistencies in cell production to enable the generation of highly defined, rapidly maturing human iPSC-derived disease models that are consistent at scale. She will also demonstrate the impact this new class of precision reprogrammed disease model cells is having within research and early drug discovery workflows.

One of the biggest challenges facing CNS scientists today is the need for in vitro cell models that accurately represent the complexity of human diseases. Inconsistent supply and variable performance have also hampered progress.

Human iPSC-derived neurons have great potential as disease models as they offer a physiologically-relevant system. Still, the complexity and length of commonly used directed differentiation protocols results in heterogeneous populations and low scalability, meaning that scientists often battle with the reproducibility of the model. Reproducibility is critical to ensure that the findings from the disease model are robust and can be used to inform future research and drug development.

bit.bio’s first-of-its-kind precision cellular reprogramming technology, opti-ox, addresses the limitations of lot consistency, cell definition and scalability by controlling the precise expression of cell-fate determining genetic factors. With opti-ox, entire populations of iPSCs are precisely and consistently reprogrammed to a chosen cell identity within days. Furthermore, bit.bio has now engineered disease-specific mutations into these cells to generate a range of neurodegenerative disease models for ALS, FTD, and Huntington's disease. 

Hear from Madeleine about her first-hand experience of incorporating these disease models into customer workflows that have enabled them to discover intrinsic phenotypes. In addition, she will discuss the characterisation, and validation of these models and give a sneak preview into the latest disease models in development. You will also learn how to request your own disease models from bit.bio. 


In this talk, you will gain insights into:

• How you can overcome inefficiencies and inconsistencies of current cell generation methods by adopting cells produced by opti-ox precision reprogramming into your workflows
• How bit.bio has used ICC, RT-qPCR, RNA-Seq and functional data to define cell identity and validate disease model genotype, creating a reliable system for in vitro modelling of ALS, FTD, and Huntington's disease
• The identification of disease-related phenotypes in models for FTD and Huntington's disease compared to isogenic controls and how scientists in early drug discovery can now challenge an intrinsic phenotype in the right context