Pre-clinical delivery of gene therapy products to the cerebrospinal fluid: challenges and considerations for clinical translation

While the majority of gene therapy studies in neurological indications have focused on direct gene transfer to the central nervous system (CNS), there is growing interest in the delivery of therapeutics using the cerebrospinal fluid (CSF) as a conduit. Historically, direct CNS routes-of-administration (RoAs) have relied on tissue dynamics, displacement of interstitial fluid, and regional specificity to achieve focal delivery into regions of interest, such as the brain. While intraparenchymal delivery minimizes peripheral organ exposure, one perceived drawback is the relative invasiveness of this approach to drug delivery. In this mini review, we examine the CSF as an alternative RoA to target CNS tissue and discuss considerations associated with the safety of performing such procedures, biodistribution of therapeutics following single administration, and translation of findings given differences between small and large animals. These factors will help delineate key considerations for translating data obtained from animal studies into clinical settings that may be useful in the treatment of neurological conditions

Neurophysiological Biomarkers of Parkinson's Disease.

BackgroundThere is a need for reliable and robust Parkinson's disease biomarkers that reflect severity and are sensitive to disease modifying investigational therapeutics.ObjectiveTo demonstrate the utility of EEG as a reliable, quantitative biomarker with potential as a pharmacodynamic endpoint for use in clinical assessments of neuroprotective therapeutics for Parkison's disease.MethodsA multi modal study was performed including aquisition of resting state EEG data and dopamine transporter PET imaging from Parkinson's disease patients off medication and compared against age-matched controls.ResultsQualitative and test/retest analysis of the EEG data demonstrated the reliability of the methods. Source localization using low resolution brain electromagnetic tomography identified significant differences in Parkinson's patients versus control subjects in the anterior cingulate and temporal lobe, areas with established association to Parkinson's disease pathology. Changes in cortico-cortical and cortico-thalamic coupling were observed as excessive EEG beta coherence in Parkinson's disease patients, and correlated with UPDRS scores and dopamine transporter activity, supporting the potential for cortical EEG coherence to serve as a reliable measure of disease severity. Using machine learning approaches, an EEG discriminant function analysis classifier was identified that parallels the loss of dopamine synapses as measured by dopamine transporter PET.ConclusionOur results support the utility of EEG in characterizing alterations in neurophysiological oscillatory activity associated with Parkinson's disease and highlight potential as a reliable method for monitoring disease progression and as a pharmacodynamic endpoint for Parkinson's disease modification therapy

Neurophysiological Biomarkers of Parkinson's Disease.

BACKGROUND:There is a need for reliable and robust Parkinson's disease biomarkers that reflect severity and are sensitive to disease modifying investigational therapeutics. OBJECTIVE:To demonstrate the utility of EEG as a reliable, quantitative biomarker with potential as a pharmacodynamic endpoint for use in clinical assessments of neuroprotective therapeutics for Parkison's disease. METHODS:A multi modal study was performed including aquisition of resting state EEG data and dopamine transporter PET imaging from Parkinson's disease patients off medication and compared against age-matched controls. RESULTS:Qualitative and test/retest analysis of the EEG data demonstrated the reliability of the methods. Source localization using low resolution brain electromagnetic tomography identified significant differences in Parkinson's patients versus control subjects in the anterior cingulate and temporal lobe, areas with established association to Parkinson's disease pathology. Changes in cortico-cortical and cortico-thalamic coupling were observed as excessive EEG beta coherence in Parkinson's disease patients, and correlated with UPDRS scores and dopamine transporter activity, supporting the potential for cortical EEG coherence to serve as a reliable measure of disease severity. Using machine learning approaches, an EEG discriminant function analysis classifier was identified that parallels the loss of dopamine synapses as measured by dopamine transporter PET. CONCLUSION:Our results support the utility of EEG in characterizing alterations in neurophysiological oscillatory activity associated with Parkinson's disease and highlight potential as a reliable method for monitoring disease progression and as a pharmacodynamic endpoint for Parkinson's disease modification therapy