Title: Simple Scattering: Lipid nanoparticle structural data repository

Journal Article · · Frontiers in Molecular Biosciences
 [1];  [2];  [3];  [3];  [1];  [1];  [4]
  1. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
  2. David Shin Consulting, Berkeley, CA (United States)
  3. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
  4. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Univ. of California, Santa Cruz, CA (United States)

Lipid nanoparticles (LNPs) are being intensively researched and developed to leverage their ability to safely and effectively deliver therapeutics. To achieve optimal therapeutic delivery, a comprehensive understanding of the relationship between formulation, structure, and efficacy is critical. However, the vast chemical space involved in the production of LNPs and the resulting structural complexity make the structure to function relationship challenging to assess and predict. New components and formulation procedures, which provide new opportunities for the use of LNPs, would be best identified and optimized using high-throughput characterization methods. Recently, a high-throughput workflow, consisting of automated mixing, small-angle X-ray scattering (SAXS), and cellular assays, demonstrated a link between formulation, internal structure, and efficacy for a library of LNPs. As SAXS data can be rapidly collected, the stage is set for the collection of thousands of SAXS profiles from a myriad of LNP formulations. In addition, correlated LNP small-angle neutron scattering (SANS) datasets, where components are systematically deuterated for additional contrast inside, provide complementary structural information. The centralization of SAXS and SANS datasets from LNPs, with appropriate, standardized metadata describing formulation parameters, into a data repository will provide valuable guidance for the formulation of LNPs with desired properties. To this end, we introduce Simple Scattering, an easy-to-use, open data repository for storing and sharing groups of correlated scattering profiles obtained from LNP screening experiments. Here, we discuss the current state of the repository, including limitations and upcoming changes, and our vision towards future usage in developing our collective knowledge base of LNPs.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
National Institute of Health (NIH); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
AC02-05CH11231; AC05-00OR22725
OSTI ID:
2375472
Journal Information:
Frontiers in Molecular Biosciences, Journal Name: Frontiers in Molecular Biosciences Vol. 11; ISSN 2296-889X
Publisher:
Frontiers Media S.A.Copyright Statement
Country of Publication:
United States
Language:
English

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