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Objective: To utilize the global system analysis (GSA) in oral absorption modeling to gain a deeper understanding of system behavior, improve model accuracy, and make informed decisions during drug development., Methods: GSA was utilized to give insight into which drug substance (DS), drug product (DP), and/or physiological parameter would have an impact on peak plasma concentration (C max ) and area under the curve (AUC) of dipyridamole as a model weakly basic compound. GSA guided the design of in vitro experiments and oral absorption risk assessment using FormulatedProducts v2202.1.0. The solubility and precipitation profiles of dipyridamole in different bile salt concentrations were measured. The results were then used to build a mechanistic oral absorption model., Results: GSA warranted further investigation into the precipitation kinetics and its link to the levels of bile salt concentrations. Mechanistic modeling studies demonstrated that a precipitation-integrated modeling approach appropriately predicted the mean plasma profiles, C max , and AUC from the clinical studies., Conclusions: This work shows the value of GSA utilization in early development to guide in vitro experimentation and build more confidence in identifying the critical parameters for the mathematical models., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The administration of insulins by subcutaneous injection is nowadays widely prevalent. The injection site is located below the dermis and composed of cells and the extracellular matrix formed of a network of macromolecules such as hyaluronic acid and collagen. Following an injection, the insulins from the formulated products are timely released as drug molecules from the injection site into systemic circulation. In this publication, we show the development of an in vitro setup utilizing a hydrogel composed of a special collagen-hyaluronic acid mixture that mimics the extracellular matrix. Another setup was used for differentiation of the commercially available and research insulin formulations by determining the in vitro permeation characteristics with the results that were correlated with the human in vivo data. Significant differentiation was achieved at 90 % confidence level between the permeation curves of insulin glulisine containing formulations (U100 and a concentrated research formulation), while in case of the insulin lispro containing formulations (U100 and U200) the permeation curves showed similarity. These results demonstrated that the in vitro setup may be used as a tool for formulation development and drug candidate profiling as it is able to differentiate or show similarities between the agglomeration states and concentration of the active pharmaceutical ingredients., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The emergence and spread of Plasmodium falciparum resistance to first-line antimalarials creates an imperative to identify and develop potent preclinical candidates with distinct modes of action. Here, we report the identification of MMV688533, an acylguanidine that was developed following a whole-cell screen with compounds known to hit high-value targets in human cells. MMV688533 displays fast parasite clearance in vitro and is not cross-resistant with known antimalarials. In a P. falciparum NSG mouse model, MMV688533 displays a long-lasting pharmacokinetic profile and excellent safety. Selection studies reveal a low propensity for resistance, with modest loss of potency mediated by point mutations in PfACG1 and PfEHD. These proteins are implicated in intracellular trafficking, lipid utilization, and endocytosis, suggesting interference with these pathways as a potential mode of action. This preclinical candidate may offer the potential for a single low-dose cure for malaria., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Oral drug absorption is a complex process depending on many factors, including the physicochemical properties of the drug, formulation characteristics and their interplay with gastrointestinal physiology and biology. Physiological-based pharmacokinetic (PBPK) models integrate all available information on gastro-intestinal system with drug and formulation data to predict oral drug absorption. The latter together with in vitro-in vivo extrapolation and other preclinical data on drug disposition can be used to predict plasma concentration-time profiles in silico. Despite recent successes of PBPK in many areas of drug development, an improvement in their utility for evaluating oral absorption is much needed. Current status of predictive performance, within the confinement of commonly available in vitro data on drugs and formulations alongside systems information, were tested using 3 PBPK software packages (GI-Sim (ver.4.1), Simcyp® Simulator (ver.15.0.86.0), and GastroPlus™ (ver.9.0.00xx)). This was part of the Innovative Medicines Initiative (IMI) Oral Biopharmaceutics Tools (OrBiTo) project. Fifty eight active pharmaceutical ingredients (APIs) were qualified from the OrBiTo database to be part of the investigation based on a priori set criteria on availability of minimum necessary information to allow modelling exercise. The set entailed over 200 human clinical studies with over 700 study arms. These were simulated using input parameters which had been harmonised by a panel of experts across different software packages prior to conduct of any simulation. Overall prediction performance and software packages comparison were evaluated based on performance indicators (Fold error (FE), Average fold error (AFE) and absolute average fold error (AAFE)) of pharmacokinetic (PK) parameters. On average, PK parameters (Area Under the Concentration-time curve (AUC 0-tlast ), Maximal concentration (C max ), half-life (t 1/2 )) were predicted with AFE values between 1.11 and 1.97. Variability in FEs of these PK parameters was relatively high with AAFE values ranging from 2.08 to 2.74. Around half of the simulations were within the 2-fold error for AUC 0-tlast and around 90% of the simulations were within 10-fold error for AUC 0-tlast . Oral bioavailability (F oral ) predictions, which were limited to 19 APIs having intravenous (i.v.) human data, showed AFE and AAFE of values 1.37 and 1.75 respectively. Across different APIs, AFE of AUC 0-tlast predictions were between 0.22 and 22.76 with 70% of the APIs showing an AFE > 1. When compared across different formulations and routes of administration, AUC 0-tlast for oral controlled release and i.v. administration were better predicted than that for oral immediate release formulations. Average predictive performance did not clearly differ between software packages but some APIs showed a high level of variability in predictive performance across different software packages. This variability could be related to several factors such as compound specific properties, the quality and availability of information, and errors in scaling from in vitro and preclinical in vivo data to human in vivo behaviour which will be explored further. Results were compared with previous similar exercise when the input data selection was carried by the modeller rather than a panel of experts on each in vitro test. Overall, average predictive performance was increased as reflected in smaller AAFE value of 2.8 as compared to AAFE value of 3.8 in case of previous exercise., (Copyright © 2020 Elsevier B.V. All rights reserved.)

A well-defined poly(ethylene glycol) methyl ether-b-poly(lactic acid) copolymer (mPEG-PLA) featuring a new, Y-shaped, architecture with a hydroxyl functional group between the two blocks has been prepared and thoroughly characterized. The functional copolymer was then readily coupled to diglycolyl-cabazitaxel. The resulting copolymer conjugates assembled into stable and monodisperse nanoparticles (NPs) in aqueous suspension. The architecture of the copolymer conjugate is shown to impact the spatial distribution of the drug within the nanoparticles. With the Y-shaped architecture, cabazitaxel was found localized at the interface of the hydrophobic PLA core and the hydrophilic mPEG corona of the NPs, as substantiated by variable temperature NMR analysis of the nanoparticles in D2O. Preliminary in vitro release studies reveal dependence on the architecture of the copolymer conjugate. This new approach offers promising perspectives to finely tune the position of the active ingredient in polymeric nanoparticles.

We describe in this article the development of a new method for the determination of rate constants of reaction of the hydroxyl radical, generated by radiolysis of water, with almost any possible molecule. It has been designed to provide a fast and reliable screening of antioxidant banks using microplates. Our particular approach is based on the use of the coumarin molecule as a competitor against the tested molecules: after a fast pulse of low dose irradiation, the fluorescence of 7-hydroxycoumarin produced by the oxidation of coumarin is measured and is inversely proportional to the scavenging ability of the tested antioxidant. We have validated our protocol using 32 molecules whose rate constants with HO had already been evaluated and found a good agreement between our rate constants and the latter ones. The scopes and limitations of our method, as well as those of other rate constant determination methods, are discussed.