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Principal Investigator: Shashi Murthy
Organization: NANITE INC.
Fiscal Year: 2023
Award: $299,995
Funding agency: National Heart Lung and Blood Institute
PROJECT SUMMARY
Cystic fibrosis (CF) is a debilitating and life-shortening disease affecting more than 70,000 people worldwide,
with ~1,000 new cases expected to be diagnosed every year. This disease is an autosomal recessive genetic
disorder associated with mutations in the CF transmembrane conductance regulator (CFTR). These mutations
impairs the ionic transport across the cell membrane. In the pulmonary epithelium, this impairment results in
an overproduction and accumulation of mucus, leading to airway obstructions and leaving patients vulnerable
to persistent pathogenic infections and severe respiratory failure. In recent years, treatment of CF with small
molecule therapies has been very impactful, however not all patients can be treated with these commercially
available therapies. More recently, advances in gene therapy enable new approaches to the greatment of CF,
such as target the underlying cause of CF lung pathology, and even restore or replace the CFTR gene, with
expectations of improved prognosis and survival outcomes. However, these therapies are typically large,
complex molecules, such as mRNA, which require specialized delivery systems. Viral vectors and lipid
nanoparticles represent the current state of the art in gene delivery, however these methods are limited by
immunogenicity, complex manufacturing, and most crucially, limited ability to traverse the mucus layerThe
three principal obstacles of CF localized delivery are the need to (i) overcome entrapment within the mucosal
barrier, (ii) avoiding recognition and disruption by immune cells such as lung macrophages, and finally, (iii)
effective intracellular entry. We propose to leverage computational optimization and structure-dynamics
modeling to design polymer-based delivery vehicles for mRNA payloads to overcome these obstacles. This
project brings together Nanite’s advanced capabilities in high throughput polymer synthesis and machine
learning together with design of glycopeptides using first-principles computational biology approaches
pioneered by Dr. Srirupa Chakraborty at Northeastern University. The availability of effective delivery vehicles
across virtually all modes of gene therapies across all indications is a well-recognized commercial need.
Nanite’s approach is to address this need by covering the broadest possible design space using a combination
of computational design, high throughput synthesis and screening, and machine learning-based optimization.
Successful completion of this Phase I project will enable us to extend this approach to CF.
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