Rett syndrome MECP2-activating drug program
preclinicaldrug program · high · Thu Apr 20 2023 00:00:00 GMT+0000 (Coordinated Universal Time)
Develop drugs for Rett syndrome by activating MECP2 expression from a silenced gene.
Use cerebral organoids modeling Rett syndrome to screen compounds that turn on the silenced MECP2 gene.
Herophilus publication listed on March 24, 2023; April 20, 2023 article excerpt reported the company aimed to launch clinical trials the next year.
Company created Rett syndrome organoids and used them to screen for compounds that activate the silenced gene in patients with the neurological condition.
AAV serotype tropism assay in human cortical organoids
exploratoryresearch program · high · Fri Apr 14 2023 00:00:00 GMT+0000 (Coordinated Universal Time)
Assess AAV serotype transduction efficiency, cellular tropism, biodistribution, and organoid health in human cortical organoids for neurological gene therapy development.
Test naturally occurring AAV serotypes in human cortical organoids from multiple donors and quantify GFP transduction of neurons and astrocytes plus overall organoid health.
bioRxiv preprint published April 14, 2023 and listed on Herophilus publications page.
Study found AAV cell tropism varied by serotype and cortical-organoid donor.
AAV serotype tropism testing in human cortical organoids
exploratoryresearch program · high · Thu Apr 13 2023 00:00:00 GMT+0000 (Coordinated Universal Time)
Evaluate human cortical organoids as a physiologically relevant model for assessing gene therapy vector transduction efficiency, cell tropism, and biodistribution in CNS-relevant tissue.
Human cortical organoids from multiple donors exposed to naturally occurring AAV serotypes; quantification of GFP transduction in neurons and astrocytes plus organoid health.
2023 bioRxiv preprint compared cell specificity of AAV serotypes in human cortical organoids.
The study demonstrated that AAV serotype and organoid donor influence cellular tropism, with quantified neuron and astrocyte transduction fractions.
C4A neuroimmune cortical organoid schizophrenia model
exploratoryresearch program · high · Fri Jan 20 2023 00:00:00 GMT+0000 (Coordinated Universal Time)
Model how elevated C4A contributes to schizophrenia risk and support phenotypic discovery and validation of immunomodulating therapies.
Neuroimmune cortical organoids overexpressing C4A, including mature neuronal cells, astrocytes, and functional microglia, used to assess inflammatory genes, cytokine secretion, and microglia-mediated synaptic uptake.
bioRxiv preprint published in 2023 describing the C4A NICO model and schizophrenia endophenotypes.
C4A organoids recapitulated neuroimmune schizophrenia endophenotypes, modulated inflammatory genes, increased cytokine secretion, and increased microglia-mediated synaptic uptake.
Human brain organoid and machine-learning drug discovery platform
undisclosedplatform · high · Sun Jan 01 2023 00:00:00 GMT+0000 (Coordinated Universal Time)
Discover and develop novel drugs for complex brain diseases using human brain models, scaled biology, and machine learning.
Cerebral, cortical, ventral forebrain, and astrocyte-rich organoid systems combined with scaled biology, neuroassays, and machine-learning analysis.
Company described platform and pipeline focus publicly; Herophilus technology was reported as sold to Genentech in 2023.
Platform supports phenotyping disease states and testing pharmaceuticals in patient-derived neural organoids.
Human brain organoid drug discovery platform
exploratoryplatform · high
Discover and develop novel drugs for complex brain diseases by modeling human brain biology and disease states in vitro.
Human stem cell-derived cerebral, cortical, ventral forebrain, and astrocyte-rich organoid systems combined with scaled biology and machine learning for phenotyping disease states and testing pharmaceuticals.
Company site describes the platform and organoid systems used to study neuronal zones, synapses, neuropil, and disease biology.
Rank-to-Group confounder robustness method
exploratoryplatform · medium
Identify hierarchical confounder effects in raw data and machine-learning-derived embeddings to improve robustness in experiment-analysis cycles.
Non-parametric statistical Rank-to-Group score applied to raw data and machine-learning embeddings.
Method described in a data science and therapeutics discovery interview involving Herophilus leaders.
The method is described as generally useful for experiment-analysis cycles and confounder robustness in machine-learning models.
Rank-to-Group score for confounder robustness
exploratoryplatform · medium
Identify hierarchical confounder effects in raw experimental data and machine learning-derived embeddings to improve experiment-analysis cycles and robustness of machine learning models.
Simple non-parametric statistical method applied to raw data and machine learning embeddings to detect confounder effects.
Interview publication described the RTG score method and its intended use in data science for therapeutics discovery.
Reported as generally useful for experiment-analysis cycles and ensuring confounder robustness in machine learning models.
