RA Abbiati, JLS Au
Computer Aided Chemical Engineering, 2018;42:239-270
Approval of generic drugs by the US Food and Drug Administration (FDA) requires the product to be pharmaceutically equivalent to the reference listed drug (RLD) and demonstrate bioequivalence (BE) in effectiveness when administered to patients under the conditions in the RLD product labeling. Effectiveness is determined by drug exposure at the target sites. However, since such measurement is usually unavailable, systemic exposure is assumed to equal target site exposure and systemic BE to equal target site BE. This assumption, while it often applies to small molecule drug products that are readily dissolved in biological fluids and systemically absorbed, is unlikely to apply to nanotechnology products (NP) that exist as heterogeneous systems and are subjected to dimension- and material-dependent changes. This commentary provides an overview of the intersecting and spatial-dependent processes and variables governing the delivery and residence of oncologic NP in solid tumors. In order to provide a quantitative perspective of the collective effects of these processes, we used quantitative systems pharmacology (QSP) multi-scale modeling to capture the physicochemical and biological events on several scales (whole-body, organ/suborgan, cell/subcellular, spatial locations, time). QSP is an emerging field that entails using modeling and computation to facilitate drug development; an analogous approach (i.e., model-informed drug development) is advocated by to FDA. The QSP model-based simulations illustrated that small changes in NP attributes (e.g., size variations during manufacturing, interactions with proteins in biological milieu) could lead to disproportionately large differences in target site exposure, rending systemic BE unlikely to equal target site BE.
L Fang, MJ Kim, Z Li, Y Wang, CE DiLiberti, JLS Au, A Hooker, MP Ducharme, R Lionberger, L Zhao
Clinical Pharmacology and Therapeutics, 2018; 104:27-30
On October 2nd and 3rd, 2017, the US Food and Drug Administration (FDA) hosted a public workshop titled “Leveraging Quantitative Methods and Modeling to Modernize Generic Drug Development and Review.”1 This report summarizes Session 2 of the public workshop: “Model Informed Drug Development and Review for Generic Products.” The session focused on the application of quantitative methods and modeling in modernizing the generic drug development and review.
P Jaiprasart, BZ Yeung, Z Lu, MG Wientjes, M Cui, CM Hsieh, S Woo, JLS Au
Journal of Controlled Release, 2018;270:101-113
RNA Interference (RNAi) is a potentially useful tool to correct the detrimental effects of faulty genes; several RNAi are undergoing clinical evaluation in various diseases. The present study identified the relative contributions of three mechanisms by which polyanion drugs reduced the gene silencing activity of Lipoplex, a complex of small interfering RNA (siRNA) and cationic liposomes. The study used a siRNA against the chemoresistance gene survivin and two model polyanion drugs (suramin, heparin). Products of Lipoplex destabilization were separated, identified, and/or quantified using ultrafiltration, gel electrophoresis, and RT-qPCR (quantitative reverse transcription polymerase chain reaction). Cell binding and endocytosis of fluorescence-labeled Lipoplex and the amount of siRNA at its site of action RISC (RNA-induced silencing complex) were evaluated using endocytosis markers, confocal microscopy, quantitative image analysis, immunoprecipitation, and RT-qPCR. The results show suramin and heparin exerted multiple concentration-dependent effects. First, these agents altered several Lipoplex properties (i.e., reduced particle size, changed surface charge, modified composition of protein biocorona). Second, both caused Lipoplex destabilization to release double- and single-strand siRNA and/or smaller siRNA-lipid complexes with reduced siRNA cargo. Third, both prevented the cell surface binding and internalization of Lipoplex, diminished the siRNA concentration in RISC, and retarded the mRNA knockdown. Suramin and heparin yielded qualitatively and quantitatively different results. Analysis of the experimental results of suramin using quantitative pharmacology (QP) modeling indicated the major cause of gene silencing activity loss depended on drug concentration, changing from inhibition of endocytosis at lower concentration (accounting for 60% loss at ~9μM) to inhibition of cell surface binding and loss of siRNA cargo at higher concentrations (accounting for 64% and 27%, respectively, at 70μM). In summary, the present study demonstrates the complex and dynamic interactions between polyanions and Lipoplex, and the use of QP modeling to delineate the contributions of three mechanisms to the eventual loss of gene silencing activity.