Background Lipid Nanoparticles (LNP) are novel vehicles for the delivery of Small and Nucleic acid therapies (gene/mRNA/siRNA) and were vital for the success of COVID-19 mRNA vaccines.1 2 LNPs consist of 1) Ionizable lipid, 2) Helper lipid, 3) Cholesterol, and 4) PEG-lipid3 and their composition affects the observed pharmacokinetic characteristics and efficacy. In addition, physio-chemical properties like the size and charge can be adjusted to improve their distribution.4–7 Some of the major challenges for LNP based programs are 1) Understanding barriers for drug availability at the tissue of interest and how to optimize the formulation to increase the bioavailability? 2) Are animal models good systems for studying bioavailability? 3) How to derive initial human dose from animal models?
The objective of this work is to incorporate the various aspects of LNPs affecting its PK into a mechanistic model to address above challenges with focus on systemic delivery (i.v.).
Methods The proposed mPBPK captures physical properties of LNPs and their impact on 1. Systemic distribution, 2. Availability at site of action 3. Cellular uptake, and 4. Intracellular drug release (figure 1).8–11 The model application is shown through two use cases. In case study 1, we used published preclinical data7 12 from the approved LNP-siRNA Onpattro to predict FIH dosing and validate with the clinical data.13 In case study 2, we predicted the optimal formulation for a hypothetical LNP-mRNA given via i.v. administration to maximize availability in the lung based on published data in mice.14
Results The mechanistic model reported here can predict kinetics of LNPs based on their physio-chemical properties. In case study 1, our predictions for FIH closely matched with the reported doses for Onpattro. In case study 2, we predicted the optimal formulation for a hypothetical LNP-mRNA given intravenously to maximize the bioavailability in Lung. Furthermore, we simulate different dosing strategies and their effect on drug efficacy. In both these cases we discuss modeling uncertainties/knowledge gaps.
Conclusions LNP design optimization is vital for improving the efficacy of nucleic acid therapies and was discussed in the literature.10 15 The proposed model has the potential to support the design of novel LNP based mRNA therapeutics. For e.g. the hypothetical case study 2 presented here is relevant for the treatment of Cystic Fibrosis. Furthermore, the model can be minimally tweaked to capture different administration routes (i.m, s.c. intranasal), different sites of action, and different drugs (mRNA/siRNA).
Akinc A, Maier MA, Manoharan M, Fitzgerald K, Jayaraman M, Barros S, et al. The Onpattro story and the clinical translation of nanomedicines containing nucleic acid-based drugs. Nat Nanotechnol. 2019 Dec;14(12):1084–7.
Suzuki Y, Ishihara H. Difference in the lipid nanoparticle technology employed in three approved siRNA (Patisiran) and mRNA (COVID-19 vaccine) drugs. Drug Metab Pharmacokinet. 2021 Dec;41:100424.
Hald Albertsen C, Kulkarni JA, Witzigmann D, Lind M, Petersson K, Simonsen JB. The role of lipid components in lipid nanoparticles for vaccines and gene therapy. Adv Drug Deliv Rev. 2022 Sep;188:114416.
Chen S, Tam YYC, Lin PJC, Sung MMH, Tam YK, Cullis PR. Influence of particle size on the in vivo potency of lipid nanoparticle formulations of siRNA. J Controlled Release. 2016 Aug;235:236–44.
Nguyen TTL, Maeng HJ. Pharmacokinetics and Pharmacodynamics of Intranasal Solid Lipid Nanoparticles and Nanostructured Lipid Carriers for Nose-to-Brain Delivery. Pharmaceutics. 2022 Mar 5;14(3):572.
Radmand A, Lokugamage MP, Kim H, Dobrowolski C, Zenhausern R, Loughrey D, et al. The Transcriptional Response to Lung-Targeting Lipid Nanoparticles in Vivo. Nano Lett. 2023 Feb 8;23(3):993–1002.
Jayaraman M, Ansell SM, Mui BL, Tam YK, Chen J, Du X, et al. Maximizing the Potency of siRNA Lipid Nanoparticles for Hepatic Gene Silencing In Vivo**. Angew Chem Int Ed. 2012 Aug 20;51(34):8529–33.
Li M, Zou P, Tyner K, Lee S. Physiologically Based Pharmacokinetic (PBPK) Modeling of Pharmaceutical Nanoparticles. AAPS J. 2017 Jan;19(1):26–42.
Cao Y, Balthasar JP, Jusko WJ. Second-generation minimal physiologically-based pharmacokinetic model for monoclonal antibodies. J Pharmacokinet Pharmacodyn. 2013 Oct;40(5):597–607.
Blanco E, Shen H, Ferrari M. Principles of nanoparticle design for overcoming biological barriers to drug delivery. Nat Biotechnol. 2015 Sep;33(9):941–51.
Xie Y, Bagby TR, Cohen M, Forrest ML. Drug delivery to the lymphatic system: importance in future cancer diagnosis and therapies. Expert Opin Drug Deliv. 2009 Aug;6(8):785–92.
Coelho T, Adams D, Silva A, Lozeron P, Hawkins PN, Mant T, et al. Safety and Efficacy of RNAi Therapy for Transthyretin Amyloidosis. N Engl J Med. 2013 Aug 29;369(9):819–29.
Urits I, Swanson D, Swett MC, Patel A, Berardino K, Amgalan A, et al. A Review of Patisiran (ONPATTRO®) for the Treatment of Polyneuropathy in People with Hereditary Transthyretin Amyloidosis. Neurol Ther. 2020 Dec;9(2):301–15.
Pardi N, Tuyishime S, Muramatsu H, Kariko K, Mui BL, Tam YK, et al. Expression kinetics of nucleoside-modified mRNA delivered in lipid nanoparticles to mice by various routes. J Controlled Release. 2015 Nov;217:345–51.
Hassett KJ, Benenato KE, Jacquinet E, Lee A, Woods A, Yuzhakov O, et al. Optimization of Lipid Nanoparticles for Intramuscular Administration of mRNA Vaccines. Mol Ther - Nucleic Acids. 2019 Apr;15:1–11.
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