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Zinc N,N-bis(2-picolyl)amine Chelates Show Substitution-Dependent Cleavage of Phosphodiesters in Models as Well as of PNAzyme-RNA Bulges
No full textPNAzymes are a group of artificial enzymes which show promising results in selective and efficient cleavage of RNA targets. In the present study, we introduce a series of metal chelating groups based on N,N-bis(2-picolyl) groups (parent, 6-methyl and 6-amino substituted) as the active sites of novel PNAzymes. An improved synthetic route for the 6-amino analogues is described. The catalytic activity of the chelating groups for cleaving phosphodiesters were assessed with the model substrate 2-hydroxypropyl p-nitrophenyl phosphate (HPNPP), confirming that the zinc complexes have the reactivity order of parent < 2-methyl < 2-amino. The three ligands were conjugated to a PNA oligomer to form three PNAzymes which showed the same order of reactivity and some sensitivity to the size of the RNA bulge designed into the catalyst–substrate complex. This work demonstrates that the kinetic activity observed for the model substrate HPNPP could be translated onto the PNAzymes, but that more reactive Zn complexes are required for such PNAzymes to be viable therapeutic agents
Does needle clogging change the spatial distribution of injected drug in tissue? New insights by X-ray computed tomography.
No full textPrefilled syringes (PFS) are primary packaging materials that offer convenience and safety for subcutaneous injection of parenteral drug solutions. However, an increasingly common problem with the trend towards higher drug concentrations is the clogging of the needle during storage due to evaporative water loss and consequent solidification of the drug. In contrast to all previous studies on this topic, this work focuses on pharmacokinetically relevant aspects and investigates the effects of needle clogging on the spatial distribution of the injected drug in the tissue. X-ray computed tomography (XCT) (both tube-based and synchrotron-based) was used to visualize and analyze the spreading pattern and the fate of the injected liquid in porcine skin. By using controlled injection and force measurement the tissue distribution was correlated with the plunger force profile and the fluid dynamics of the jet. Studies of monoclonal antibody solution demonstrate that clogs, which are formed by evaporation of water and solidification of drug solution in the needle tip, usually dissolve in the flow of the liquid during injection. In the initial injection phase, the liquid jet starts to escape the needle only through a narrow channel in the clog. The resulting high dynamic pressure can alter the distribution of the liquid in the tissue, causing a long tail of liquid that penetrates deep into the fibrous network of the subcutaneous layer. However, the volume of this tail was calculated to be low relative to the overall volume of the injected drug solution (less than 2.4%) and is therefore unlikely to have a significant effect on the absorption kinetics of the injected drug. In addition, it was shown that if a clog were to enter the tissue, it would quickly dissolve
Nonlinear mixed-effects modeling as a method for causal inference to predict exposures under desired within-subject dose titration schemes.
No full textThe ICH E9 (R1) guidance and the related estimand framework propose to clearly define and separate the clinical question of interest formulated as estimand from the estimation method. With that it becomes important to assess the validity of the estimation method and the assumptions that must be made. When going beyond the intention to treat analyses that can rely on randomization, causal inference is usually used to discuss the validity of estimation methods for the estimand of interest. In pharmacometrics, mixed-effects models are routinely used to analyze longitudinal clinical trial data; however, they are rarely discussed as a method for causal inference. Here, we evaluate nonlinear mixed-effects modeling and simulation (NLME M&S) in the context of causal inference as a standardization method for longitudinal data in the presence of confounders. Standardization is a well-known method in causal inference to correct for confounding by analyzing and combining results from subgroups of patients. We show that nonlinear mixed-effects modeling is a particular implementation of standardization that conditions on individual parameters described by the random effects of the mixed-effects model. As an example, we use a simulated clinical trial with within-subject dose titration. Being interested in the outcome of the hypothetical situation that patients adhere to the planned treatment schedule, we put assumptions in a causal diagram. From the causal diagram, conditional independence assumptions are derived either by conditioning on the individual parameters or on earlier outcomes. With both conditional independencies unbiased estimates can be obtained
The seventh blind test of crystal structure prediction: structure ranking methods.
No full textA seventh blind test of crystal structure prediction has been organized by the Cambridge Crystallographic Data Centre. The results are presented in two parts, with this second part focusing on methods for ranking crystal structures in order of stability. The exercise involved standardized sets of structures seeded from a range of structure generation methods. Participants from 22 groups applied several periodic DFT-D methods, machine learned potentials, force fields derived from empirical data or quantum chemical calculations, and various combinations of the above. In addition, one non-energy-based scoring function was used. Results showed that periodic DFT-D methods overall agreed with experimental data within expected error margins, while one machine learned model, applying system-specific AIMnet potentials, agreed with experiment in many cases demonstrating promise as an efficient alternative to DFT-based methods. For target XXXII, a consensus was reached across periodic DFT methods, with consistently high predicted energies of experimental forms relative to the global minimum (above 4 kJ mol-1 at both low and ambient temperatures) suggesting a more stable polymorph is likely not yet observed. The calculation of free energies at ambient temperatures offered improvement of predictions only in some cases (for targets XXVII and XXXI). Several avenues for future research have been suggested, highlighting the need for greater efficiency considering the vast amounts of resources utilized in many cases
Process Understanding of Transamination Reaction in Chiral Pharmaceutical Intermediate Production Catalyzed by an Engineered Amine Transaminase
No full textChiral amines are key building blocks for the synthesis of many active pharmaceutical ingredients (APIs). Biocatalytic routes offer significant advantages to provide sustainable access to such motifs on commercial scale, with sacubitril valsartan sodium hydrate as a recent example. In this study a deeper mechanistic and kinetic understanding of the central biocatalytic step in the synthesis of sacubitril valsartan sodium hydrate, applying the evolved transaminase CDX-043, was gained. The equilibrium of the transamination reaction was investigated in detail, and two kinetic models (Ping-Pong two-substrate kinetics and Michaelis-Menten double substrate kinetics) were established, considering substrate and product inhibition. The determined equilibrium constant indicates that the equilibrium lies strongly on the product side. The results of the kinetic studies demonstrate that the transaminase reaction is in conformity with the Michaelis-Menten double substrate kinetic model. Product inhibition was found to be more severe than substrate inhibition. In conclusion, the application of a plug flow reactor (PFR) was shown to be the preferred reactor setup to reduce the occurring inhibition
PBBM Considerations for Base Models, Model Validation and Application Steps: Workshop Summary Report
No full textThe proceedings from the 30th August 2023 (Day 2) of the workshop “Physiologically Based Biopharmaceutics Models (PBBM) Best Practices for Drug Product Quality: Regulatory and Industry Perspectives” are provided herein. Day 2 covered PBBM case studies from six regulatory authorities which provided considerations for model verification, validation and application based on the context of use (COU) of the model. PBBM case studies to define critical material attribute (CMA) specification settings such as active pharmaceutical ingredient (API) particle size distributions (PSD) were shared. PBBM case studies to define critical quality attributes (CQA) such as dissolution specification setting or to define the bioequivalence safe space were discussed. PBBM COU examples are described.
Breakout session discussions highlighted current trends and barriers to application of PBBMs including: a) PBBM credibility assessment framework and level of validation, b) use of disposition parameters in PBBM and points to consider when IV data are not available, c) conducting virtual bioequivalence trials and dealing with variability, d) model acceptance criteria and e) application of PBBMs for establishing safe space and failure edges. Examples of PBBM using the credibility assessment framework, COU and model risk assessment as well as scientific learnings from PBBM case studies are provided
What Bottleneck? New Strategies for a Better Glycosylation Profile
No full textEXECUTIVE SUMMARY of a previously approved OAK - Project 5046
Bronchosphere Viability Experiments
No full textWhen Pranjali Beri was a GNF postdoc in 2021-2022, she collaborated with David Rowlands to test the effects of Icenticaftor and Ivacaftor on her CSE-treated bronchospheres system for a paper David was drafting. In May 2022, Pranjali shared a summary powerpoint with David addressing some remaining open questions to her contribution. Unfortunately, the paper was not completed and published before they both left Novartis. We now are seeking permission to share the summary powerpoint and an excel file of the viability data with David Rowlands for potential inclusion in his publication
Therapeutic strategies to target connective tissue growth factor in fibrotic lung diseases.
No full textThe treatment of interstitial lung diseases, including idiopathic pulmonary fibrosis (IPF), remains challenging as current available antifibrotic agents are not effective in halting disease progression. Connective tissue growth factor (CTGF), also known as cellular communication factor 2 (CCN2), is a member of the CCN family of proteins that regulates cell signaling through cell surface receptors such as integrins, the activity of cytokines/growth factors, and the turnover of extracellular matrix (ECM) proteins. Accumulating evidence indicates that CTGF plays a crucial role in promoting lung fibrosis through multiple processes, including inducing transdifferentiation of fibroblasts to myofibroblasts, epithelial-mesenchymal transition (EMT), and cooperating with other fibrotic mediators such as TGF-β. Increased expression of CTGF has been observed in fibrotic lungs and inhibiting CTGF signaling has been shown to suppress lung fibrosis in several animal models. Thus, the CTGF signaling pathway is emerging as a potential therapeutic target in IPF and other pulmonary fibrotic conditions. This review provides a comprehensive overview of the current evidence on the pathogenic role of CTGF in pulmonary fibrosis and discusses the current therapeutic agents targeting CTGF using a systematic review approach
A novel ex vivo approach for investigating profibrotic macrophage polarization using murine precision-cut lung slices
No full textIdiopathic pulmonary fibrosis (IPF) is fatal interstitial lung disease characterized by excessive scarring of the lung tissue and declining respiratory function. Given its short prognosis and limited treatment options, novel strategies to investigate emerging experimental treatments are urgently needed. Macrophages, as the most abundant immune cell in the lung, have key implications in wound healing and lung fibrosis. However, they are highly plastic and adaptive to their surrounding microenvironment, and thus to maximize translation of research to lung disease, there is a need to study macrophages in multifaceted, complex systems that are representative of the lung. Precision-cut lung slices (PCLS) are living tissue preparations derived from the lung that are cultured ex vivo, which bypass the need for artificial recapitulation of the lung milieu and architecture. Macrophage programming studies are traditionally conducted using isolated cells in vitro, thus our objective was to establish and validate a moderate-throughput, biologically-translational, viable model to study profibrotic polarization of pulmonary-resident macrophages using murine PCLS. To achieve this, we used a polarization cocktail (PC), consisting of IL-4, IL-13, and IL-6, over a 72-h time course. We first demonstrated no adverse effects of the PC on PCLS viability and architecture. Next, we showed that multiple markers of macrophage profibrotic polarization, including Arginase-1, CD206, YM1, and CCL17 were induced in PCLS following PC treatment. Through tissue microarray-based histological assessments, we directly visualized and quantified Arginase-1 and CD206 staining in PCLS in a moderate-throughput manner. We further delineated phenotype of polarized macrophages, and using high-plex immunolabelling with the Iterative Bleaching Extends Multiplexity (IBEX) method, showed that the PC effects both interstitial and alveolar macrophages. Substantiating the profibrotic properties of the system, we also showed expression of extracellular matrix components and fibrotic markers in stimulated PCLS. Finally, we demonstrated that clodronate treatment diminishes the PC effects on profibrotic macrophage readouts. Overall, our findings support a suitable complex model for studying ex vivo profibrotic macrophage programming in the lung, with future capacity for investigating experimental therapeutic candidates and disease mechanisms in pulmonary fibrosi