Pharmaceutical Research

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Online ISSN: 1573-904X
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  • Anthony GrelierAnthony Grelier
  • Matej ZadravecMatej Zadravec
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  • Theresa Hörmann-KincsesTheresa Hörmann-Kincses
Introduction With an increased adoption of continuous manufacturing for pharmaceutical production, the ConsiGma® CTL25 wet granulation and tableting line has reached widespread use. In addition to the continuous granulation step, the semi-continuous six-segmented fluid bed dryer is a key unit in the line. The dryer is expected to have an even distribution of the inlet air between the six drying cells. However, process observations during manufacturing runs showed a repeatable pattern in drying time, which suggests a variability in the drying performance between the different cells of the dryer. The aim of this work is to understand the root-cause of this variability. Materials and methods In a first step, the variability in the air temperature and air flow velocity between the dryer cells was measured on an empty dryer. In a second step, the experimental data were interpreted with the help of results from computational fluid dynamics (CFD) simulations to better understand the reasons for the observed variability. Results The CFD simulations were used to identify one cause of the measured difference in the air temperature, showing the impact of the air inlet design on the temperature distribution in the dryer. Conclusions Although the simulation could not predict the exact temperature, the trend was similar to the experimental observations, demonstrating the added value of this type of simulation to guide process development, engineering decisions and troubleshoot equipment performance variability.
Background It is unclear whether Vitamin D is efficacious as a host-directed therapy (HDT) for patients of tuberculosis (TB). We investigated pulmonary delivery of the active metabolite of Vitamin D3, i.e., 1, 25-dihydroxy vitamin D3 (calcitriol) in a mouse model of infection with Mycobacterium tuberculosis (Mtb). Methods We optimized a spray drying process to prepare a dry powder inhalation (DPI) of calcitriol using a Quality by Design (QbD) approach. We then compared outcomes when Mtb-infected mice were treated with inhaled calcitriol at 5 ng/kg as a stand-alone intervention versus DPI as adjunct to standard oral anti-tuberculosis therapy (ATT). Results The DPI with or without concomitant ATT markedly improved the morphology of the lungs and mitigated histopathology in both the lungs and the spleens. The number of nodular lesions on the lung surface decreased from 43.7 ± 3.1 to 22.5 ± 3.9 with the DPI alone and to 9.8 ± 2.5 with DPI + ATT. However, no statistically significant induction of host antimicrobial peptide cathelicidin or reduction in bacterial burden was seen with the DPI alone. DPI + ATT did not significantly reduce the bacterial burden in the lungs compared to ATT alone. Conclusions We concluded that HDT using the low dose calcitriol DPI contributed markedly to mitigation of pathology, but higher dose may be required to evoke significant induction of bactericidal host response and bactericidal activity in the lung.
Purpose The stability of protein drug products frozen during fill finish operations is greatly affected by the freezing rate applied. Non-optimal freezing rates may lead to the denaturation of protein’s complex macromolecular conformation. However, limited work has been done to address the effect of different freezing rates on protein stability at nano-scale level. Methods The stability of a model protein, lysozyme, was investigated at atomic and molecular scale under varying freezing rates and moving ice-water interface. Ice seeding approach was adopted to initiate ice formation in this present simulation. Results The faster freezing rate (11–12 K/490 ns) applied resulted in overall smaller ice fraction within the simulation box with a larger freeze-concentrated liquid (FCL) region. Consequently, the faster freezing rate better maintained protein stability with less secondary structure deviations, higher hydration level and structural compactness, and less fluctuations at individual residues than observed following slow (5–6 K/490 ns) and medium (7–8 K/490 ns) freezing rates. The present study also identified the residues near and within helices 3, 6, 7, and 8 dominate the structural instability of the lysozyme at 247 K freezing temperature. Conclusions For the first time, ice formation in therapeutic protein solution was studied “non-isothermally” at different freezing rates using molecular dynamics simulations. Thus, a good understanding of freezing rates on protein instability was revealed by applying the developed computational model.
In this paper, we focus on providing a discrete formulation for a reduced aggregation population balance equation. The new formulation is simpler, easier to code, and adaptable to any type of grid. The presented method is extended to address a mixed-suspension mixed-product removal (MSMPR) system where aggregation and nucleation are the primary mechanisms that affect particle characteristics (or distributions). The performance of the proposed formulation is checked and verified against the cell average technique using both gelling and non gelling kernels. The testing is carried out on two benchmarking applications, namely batch and MSMPR systems. The new technique is shown to be computationally less expensive (approximately 40%) and predict numerical results with higher precision even on a coarser grid. Even with a revised grid, the new approach tends to outperform the cell average technique while requiring less computational effort. Thus the new approach can be easily adapted to model the crystallization process arising in pharmaceutical sciences and chemical engineering.
Purpose Successful drug therapy in children is contingent upon hassle-free administration of pediatric dosage forms. Pediatric patients suffer from difficulty in swallowing due to weak esophagus muscles in their early age. Considering this challenge liquid formulations are preferred over solid dosage form among pediatric patients to avoid the possibility of choking which can be a serious life-threatening condition in children. The main aim of the present research work was to develop a reconstitutable amorphous acetaminophen spray-dried milk powder (ASDM) as novel pediatric formulation. Methods ASDM was prepared by spray drying process and the spray drying process was optimized using Box-Behnken design to study the effect of spray drying process parameters at X1 [inlet temperature], X2 [aspiration rate] and X3 [feed rate] to Y1 [% yield], Y2 [angle of repose], Y3 [Hausner’s Ratio] and Y4 [Carr’s Index] as dependent variables of ASDM. In addition, each batch was characterized for particle size by polarized light microscopy and drug entrapment. Results Predicted parameters from optimized spray drying process model were successfully employed to manufacture a scale up cum validation batch of ASDM, which showed notably improved yield and desirable flow properties. The scale-up validation batch was further characterized using thermal analysis, diffraction studies, spectroscopic analysis, dispersion studies, stability APAP in dispersion formulation and formulation stability studies to confirm the physico-chemical stability of ASDM. Conclusions Thus, ASDM for oral use can serve as a promising pediatric formulation and the developed prototype formulation can be further extended to future newly discovered drugs with similar characteristics.
Purpose Fluid-bed coating processes make it possible to manufacture pharmaceutical products with tuneable properties. The choice of polymer type and coating thickness provides control over the drug release characteristics, and multi-layer pellet coatings can combine several active ingredients or achieve tailored drug release profiles. However, the fluid-bed coating is a parametrically sensitive process due to the simultaneous occurrence of polymer solution spraying and solvent evaporation. Designing a robust fluid-bed coating process requires the knowledge of thin film drying kinetics, which in turn critically depends on an accurate description of concentration-dependent solvent diffusion in the polymer. Methods This work presents a mathematical model of thin film drying as an enabling tool for fluid-bed process design. A custom-built benchtop drying cell able to record and evaluate the drying kinetics of a chosen polymeric excipient has been constructed, validated, and used for data collection. Results A semi-empirical mathematical model combining heat transfer, mass transfer, and film thickness evolution was formulated and used for estimating the solvent diffusion coefficient and solvent distribution in the polymer layer. The combined experimental and computational methodology was then used for analysing the drying kinetics of common polymeric excipients: poly(vinylpyrrolidone) and two grades of hydroxypropyl methylcellulose. Conclusions The experimental setup together with the mathematical model represents a valuable tool for predictive modeling of pharmaceutical coating processes.
Physics-constrained supervised auto-encoder (PCSAE) model used. The regressor represents the prediction of the process outputs which are constrained by the physics-based boundary conditions.
Comparing total loss of the supervised auto-encoder and physics-constrained auto-encoder during training. Even with an extra regularization term in the PCSAE, the total loss of the system is lower than the SAE indicating that the imposing of boundary conditions not only improved process outcome prediction but also reconstruction.
Parity plot for the SAE and PCSAE models. The PCSAE model predicted the process outcomes better than the SAE models, while both showed similar performance in reconstruction of the inputs.
Sobol sensitivity plots obtained for the SAE and PCSAE models. The blue bars and the red bars indicate the direct effect and the total effect including interactions effects of the inputs on the latent space variables. The effect of inputs on the latent variables in the PCSAE are more in accord with experimental observations.
SVM planes dividing the latent space after the supervised classification. This division creates regions in the latent space to help identify granule growth regimes which can in turn help in assessing risk associated with the process.Sub-figures (a) and (b) are the same plots with images taken at different viewing angles for better representation.
Quality risk management is an important task when it pertains to the pharmaceutical industry, as this is directly related to product performance. With the ICH Q9 guidelines, several regulatory bodies have encouraged the pharmaceutical industry to implement risk management plans using scientific and systemic approaches such as quality-by-design to asses product quality. However, the implementation of such methods has been challenging as assessment of risks requires accurate quantitative models to predict changes in quality when variations occur. This study describes a framework that quantitatively assesses risk for a twin screw wet granulation process. This framework consists of a physics-constrained autoencoder system, whose outputs are constrained using physics-based boundary conditions. The latent variables obtained from the auto-encoder are used in a support vector machine-based classifier to understand the granule growth behavior occurring within the system. This framework is able to predict the process outcomes with 86% accuracy and classify the granule growth regimes with a true positive rate of 0.73. Based on the classification the risk associated with the process can be estimated.
Objective A common issue of freeze drying is the inhomogeneity between samples, both in regards to water content and structure. The purpose of this study is to address this issue, and try to understand the cause of inhomogeneity in the heat transfer and sample temperature. Methods The temperature and the heat transfer was measured using different setups, both with and without vial holders at various positions at different shelf temperature and chamber pressures. By comparing sublimation rate measurements (water sample) with temperature equilibrium measurements with a non-evaporating liquid (oil sample), the heat transfer contribution from radiation and conduction could be separated and investigated individually. Results The oil sample temperature increases each time the pressure is decreased; the increase is highest at lower shelf temperatures. Using vial holder reduces the deviation between the samples but have limited effect on the temperature increase. The sublimation rate for water sample is pressure dependent and samples close to the walls have a higher sublimation rate than vials in the center. The sublimation rate increases slightly when using a vial holder but the deviation between vials becomes more random. Conclusions The heat transfer consists of conduction through rectified vapor and radiation from surrounding walls, about 65–75% of the heat is transferred by conduction and 25–35% by radiation under normal operational conditions. As the vial holder is also influenced by the radiation, the vial inside the holder is indirectly affected by the surrounding radiation.
Distribution of the simulated vancomycin AUC48-72href values used for the development of machine learning algorithms using three different algorithms (AUC is area under the curve in mg*h/L).
Xgboost variable importance plot in the analysis set. “Continous_perfusion” corresponds to the reference dose usually prescribed in our NICU Department at Limoges University Hospital based on post menstrual age and the plasmatic creatinine value
Paired boxplots comparing the log of the 3 dose proposals (reference, literature equation [25] and ML doses) and split into 3 groups: AUC calculated with references doses in the target range (400–600 mg*h/L), below the target (mg*h/L < 400) and above the target (> 600 mg*h/L) in the independent simulated set (n°2).
Paired boxplots comparing the log of the 3 dose proposals (reference, literature equation [25] and ML doses) and split into 3 groups: AUC calculated with references doses in the target range (400–600 mg*h/L), below the target (mg*h/L < 400) and above the target (> 600 mg*h/L) in the external database from actual patients (n = 82).
Introduction Vancomycin is one of the antibiotics most used in neonates. Continuous infusion has many advantages over intermittent infusions, but no consensus has been achieved regarding the optimal initial dose. The objectives of this study were: to develop a Machine learning (ML) algorithm based on pharmacokinetic profiles obtained by Monte Carlo simulations using a population pharmacokinetic model (POPPK) from the literature, in order to derive the best vancomycin initial dose in preterm and term neonates, and to compare ML performances with those of an literature equation (LE) derived from a POPPK previously published. Materials and methods The parameters of a previously published POPPK model of vancomycin in children and neonates were used in the mrgsolve R package to simulate 1900 PK profiles. ML algorithms were developed from these simulations using Xgboost, GLMNET and MARS in parallel, benchmarked and used to calculate the ML first dose. Performances were evaluated in a second simulation set and in an external set of 82 real patients and compared to those of a LE. Results The Xgboost algorithm yielded numerically best performances and target attainment rates: 46.9% in the second simulation set of 400–600 AUC/MIC ratio vs. 41.4% for the LE model (p = 0.0018); and 35.3% vs. 28% in real patients (p = 0.401), respectively). The Xgboost model resulted in less AUC/MIC > 600, thus decreasing the risk of nephrotoxicity. Conclusion The Xgboost algorithm developed to estimate the initial dose of vancomycin in term or preterm infants has better performances than a previous validated LE and should be evaluated prospectively.
Purpose Tobramycin shows synergistic antibacterial activity with colistin and can reduce the toxic effects of colistin. The purpose of this study is to prepare pulmonary powder formulations containing both colistin and tobramycin and to assess their in vitro aerosol performance and storage stability. Methods The dry powder formulations were manufactured using a lab-scale spray dryer. In vitro aerosol performance was measured using a Next Generation Impactor. The storage stability of the dry powder formulations was measured at 22°C and two relative humidity levels – 20 and 55%. Colistin composition on the particle surface was measured using X-ray photoelectron spectroscopy. Results Two combination formulations, with 1:1 and 1:5 molar ratios of colistin and tobramycin, showed fine particle fractions (FPF) of 85%, which was significantly higher than that of the spray dried tobramycin (45%). FPF of the tobramycin formulation increased significantly when stored for four weeks at both 20% and 55% RH. In contrast, FPF values of both combination formulations and spray dried colistin remained stable at both humidity levels. Particle surface of each combination was significantly enriched in colistin molecules; 1:5 combination showed 77% by wt. colistin. Conclusions The superior aerosol performance and aerosolization stability of 1:1 and 1:5 combination formulations of colistin and tobramycin could be attributed to enrichment of colistin on the co-spray dried particle surface. The observed powder properties may be the result of a surfactant-like assembly of these colistin molecules during spray drying, thus forming a hydrophobic particle surface.
Purpose Nanosuspensions have been used for enhancing the bioavailability of poorly soluble drugs. This study explores the temperature evolution during their preparation in a wet stirred media mill using a coupled experimental–enthalpy balance approach. Methods Milling was performed at three levels of stirrer speed, bead loading, and bead sizes. Temperatures were recorded over time, then simulated using an enthalpy balance model by fitting the fraction of power converted to heat ξ. Moreover, initial and final power, ξ, and temperature profiles at 5 different test runs were predicted by power-law (PL) and machine learning (ML) approaches. Results Heat generation was higher at the higher stirrer speed and bead loading/size, which was explained by the higher power consumption. Despite its simplicity with a single fitting parameter ξ, the enthalpy balance model fitted the temperature evolution well with root mean squared error (RMSE) of 0.40–2.34°C. PL and ML approaches provided decent predictions of the temperature profiles in the test runs, with RMSE of 0.93–4.17 and 1.00–2.17°C, respectively. Conclusions We established the impact of milling parameters on heat generation–power and demonstrated the simulation–prediction capability of an enthalpy balance model when coupled to the PL–ML approaches. Graphical abstract
Aim Widespread clinical application of vascularized composite allotransplantation (VCA) has been limited by the need for lifelong systemic immunosuppression to prevent rejection. Our goal was to develop a site-specific immunosuppressive strategy that promotes VCA allograft survival and minimizes the risk of systemic side effects. Methods Tacrolimus loaded polycaprolactone (TAC-PCL) disks were prepared and tested for their efficacy in sustaining VCA allograft survival via site-specific immunosuppression. Brown Norway-to-Lewis rat hind limb transplantations were performed; animals received one TAC disk either in the transplanted (DTx) or in the contralateral non-transplanted (DnonTx) limbs. In another group, animals received DTx and lymphadenectomy on Tx side. Blood and allograft levels of TAC were measured using LC–MS/MS. Systemic toxicity was evaluated. Results Animals that received DTx achieved long-term allograft survival (> 200 days) without signs of metabolic and infectious complications. In these animals, TAC blood levels were low but stable between 2 to 5 ng/mL for nearly 100 days. High concentrations of TAC were achieved in the allografts and the draining lymph nodes (DLN). Animals that underwent lymphadenectomy rejected their allograft by 175 days. Animals that received DnonTx rejected their allografts by day 70. Conclusion Controlled delivery of TAC directly within the allograft (with a single TAC disk) effectively inhibits rejection and prolongs VCA allograft survival, while mitigating the complications of systemic immunosuppression. There was a survival benefit of delivering TAC within the allograft as compared to a remote site. We believe this approach of local drug delivery has significant implications for drug administration in transplantation.
Key processes and rate-determining steps involved in the cellular uptake, disposition, and pharmacodynamic activity of ligand-conjugated siRNA. Abbreviations: Rf, free receptor; BR, cell surface-bound siRNA-receptor complex; BRendosome, siRNA-receptor complex internalized within endosomes; Rf,endosome, free (dissociated) receptor in endosome; Cf,endosome, free (non-conjugated) siRNA in endosome; Cf,cytoplasm, free siRNA in cytoplasm (escaping endosome compartment); RISC, RNA-induced silencing complex. Figure adapted and redrawn based on model by Ayyar VS et al. (17)
The approval of four small interfering RNA (siRNA) products in the past few years has demonstrated unequivocally the therapeutic potential of this novel modality. Three such products (givosiran, lumasiran and inclisiran) are liver-targeted, using tris N-acetylgalactosamine (GalNAc)3 as the targeting ligand. Upon subcutaneous administration, GalNAc-conjugated siRNAs rapidly distribute into the liver via asialoglycoprotein receptor (ASGPR) mediated uptake in the hepatocytes, resulting in fast elimination from the systemic circulation. Patisiran, on the other hand, has been formulated in a lipid nanoparticle for optimal delivery to the liver. While several publications have described preclinical and clinical pharmacokinetic (PK) and pharmacodynamic (PD) results, including absorption, distribution, metabolism, and elimination (ADME) profiles in selected species as well as limited modeling efforts for siRNA therapeutics, there is no systematic review of the PK and PD models developed for these agents or work summarizing the utility and application(s) of such models in drug development and regulatory review. Here, we provide a mini-review of the current state of modeling efforts for siRNA therapeutics within the early preclinical, translational, and clinical stages of siRNA development. Diverse modeling methods including simple compartmental, mechanistic and systems PK/PD, physiologically-based PK (PBPK), population PK/PD, and dose–response-time models are introduced and reviewed. The utility of such models in development and regulatory review for siRNA therapeutics is also discussed with examples. Finally, the current knowledge gaps in mechanism of action of siRNA and resulting challenges in model development are summarized. The goal of this minireview is to trigger cross-functional discussion amongst all key stakeholders to generate key experimental datasets and align on current assumptions, model structures, and approaches to facilitate development and application of robust PK/PD models for siRNA therapeutics.
Purpose To evaluate the duration of effect of rHuPH20 on SC absorption of cetuximab and to develop a mechanistic pharmacokinetic model linking the kinetics of rHuPH20 action with hyaluronan (HA) homeostasis and absorption of cetuximab from the SC space. Methods Serum pharmacokinetics of cetuximab was evaluated after IV and SC dosing at 0.4 and 10 mg/kg (control groups). In test groups, SC cetuximab was administered simultaneously with rHuPH20 (Co-Injection) or 12 h after injection of rHuPH20 (Pre-Injection). Mechanistic pharmacokinetic model was developed to simultaneously capture cetuximab kinetics in all groups. Results Administration of rHuPH20 resulted in a faster absorption of cetuximab; the difference between co-injection and pre-injection groups appeared to be dependent on the dose level. The model combined three major components: kinetics of rHuPH20 at SC site; HA homeostasis and its disruption by rHuPH20; and cetuximab systemic disposition and the effect of HA disruption on cetuximab SC absorption. The model provided good description of experimental data obtained in this study and collected previously. Conclusions Proposed model can serve as a potential translational framework for capturing the effect of rHuPH20 across multiple preclinical species and in human studies and can be used for optimization of SC delivery of biotherapeutics.
Simplified view of the pathways of cellular uptake of particles. Depending on particles size an overlapping of cellular uptake routes is possible. In all endocytic pathways the extracellular material enters the cell through plasma membrane vesicles. The majority of cargo these vesicles internalize is trafficked to the early endosome. At this point soluble or smaller cargo can be recycled back to the cell surface while insoluble and large material continue to the late endosome and subsequently to the lysosome.
Simplified process of particle phagocytosis. Target particles which display a diverse array of ligands on their surface can engage a variety of receptors with various degrees of ligand specificity. The recognizing of these receptors leads to the induction of signaling cascades that promote actin polymerization which in turn is responsible for engulfment of particles and phagosome maturation. Figure adapted from 92.
Physicochemical characteristics of particles for targeting APCs and modulate immune response. Preferentially but not exclusively DCs phagocytose smaller and positive-charged particles regardless of the shape. Macrophages phagocytose larger particles regardless of the charge or smaller particles if the charge decrease. The less spherical and smaller a particle is, the more likely it is to polarize the immune response to Th1. DCs = dendritic cells; Mϕ = macrophages; Th1 = cellular immune response; Th2 = humoral immune response. Ligands, coatings or surfactants that contribute with changes in surface charge are represented as arrows with round and triangular endings on particles.
Distribution and abundance of human phagocytes that can be implicated in recognition and capture of particulate vaccines and drugs by route of administration. ID = intradermal; SC = subcutaneous; IM = intramuscular; IV = intravenous; IN = intranodular; O = oral; N = nasal; P = pulmonary; V = vaginal.
A robust comprehension of phagocytosis is crucial for understanding its importance in innate immunity. A detailed description of the molecular mechanisms that lead to the uptake and clearance of endogenous and exogenous particles has helped elucidate the role of phagocytosis in health and infectious or autoimmune diseases. Furthermore, knowledge about this cellular process is important for the rational design and development of particulate systems for the administration of vaccines or therapeutics. Depending on these specific applications and the required biological responses, particles must be designed to encourage or avoid their phagocytosis and prolong their circulation time. Functionalization with specific polymers or ligands and changes in the size, shape, or surface of particles have important effects on their recognition and internalization by professional and nonprofessional phagocytes and have a major influence on their fate and safety. Here, we review the phagocytosis of particles intended to be used as carrier or delivery systems for vaccines or therapeutics, the cells involved in this process depending on the route of administration, and the strategies employed to obtain the most desirable particles for each application through the manipulation of their physicochemical characteristics. We also offer a view of the challenges and potential opportunities in the field and give some recommendations that we expect will enable the development of improved approaches for the rational design of these systems.
Outline of the method: 10 mg of a commercial formula containing 5% caffeine are applied at T0 on two areas delineated on the skin. The excess formula is removed 30 min after application. Eleven consecutive tape strips are collected immediately after washing on one of the areas (uptake, T30min). Eleven consecutive tape strips are collected on the other treated area 5.5 h after product removal (clearance, 5h30 after washing). The caffeine content is analyzed in each strip and the difference between uptake and clearance corresponds to the amount of active that has diffused.
Comparison of the two washing protocols in study B: quantity of caffeine in each of the tape strips (95% confidence interval of means, n = 20). In dark blue: Up (T0h30), water washing; in light blue: Cl (T6h), water washing, in dark red: Up (T0h30), soap washing; in light red: Cl (T6h), soap washing.
Box plot showing caffeine amount in the 11 consecutive strips (top) and cumulated amount (bottom) between study (A) (in red) and study (B) (in blue) at Up (left) and Cl (right). Investigational area: volar forearm, type of wash: soap. Boxes: 1st to 3rd quartile, middle line: median, diamond: mean; whiskers: min/max (5th and percentiles); red dots: outliers.
Box plot showing caffeine amount in the 11 consecutive strips (top) and cumulated amount (bottom) between study B (in red) and study C on younger group (20–35 years) (in blue) at Up (left) and Cl (right). Investigational area: volar forearm, type of wash: water. Boxes: 1st to 3rd quartile, middle line: median, diamond: mean; whiskers: min/max (5th and percentiles); red dots: outliers.
Box plot showing cumulated caffeine quantities retrieved in the 11 successive strips collected at T30min (Up) and T6h (Cl) on the cheek (a), the forehead (b) and the forearm (c) of the volunteers from the younger group (20–35 years, in red) and the older post-menopausal group (50–65 years, in blue). #: significant difference between age groups (p < 0.05; strong effect size > 1); ns: no significant difference between age groups; t: tendency between age groups (0.05 < p < 0.1; moderate or weak effect size < 1.5); §: significant difference between Up and Cl (p < 0.05, strong or very strong effect size > 1.5); ¥: Cl in tendency (0.05 < p < 0.1; weak effect size < 0.8). Boxes: 1st to 3rd quartile, middle line: median, diamond: mean; whiskers: min/max (5th and percentiles); red dots: outliers.
Purpose Assessing the percutaneous absorption of cosmetic ingredients using in-vitro human skin reveals certain limitations, such as restricted anatomical sites and repeated exposure, and to overcome these issues, in-vivo studies are required. The aim of the study is to develop a robust non-invasive in-vivo protocol that should be applicable to a wide range of application. Methods A robust tape stripping protocol was therefore designed according to recent recommendations, and the impact of two different washing procedures on caffeine distribution in tape strips was investigated to optimise the protocol. The optimised protocol was then used to study the effect of age and anatomical area on the percutaneous absorption of caffeine, including facial areas which are not readily available for in-vitro studies. Results With tape stripping, a difference between the percutaneous absorption on the face (forehead, cheek) and the volar forearm was observed. No obvious difference was observed between percutaneous absorption in young and post-menopausal women, but this could be due to the limited number of subjects. Conclusion This tape stripping protocol is now to be deployed to address many other factors, such as percutaneous absorption in other anatomical areas (e.g. abdomen, axilla, etc.), impact of repeated applications and effect of formulation.
The overall workflow for developing VCZ and VEN models.
Prediction performance of VCZ PBPK model on plasma concentrations in defined CYP2C19 genotype groups. Observed data reported in the literature are shown as black dots (27,31). Population simulation means are shown as lines; The shaded areas illustrate the 90% population prediction intervals; Details of dosing regimens, study populations, predicted versus observed PK parameters are summarized in Table III.
Mean simulated (black lines) and observed (black dots) plasma VEN concencentration-time profile in fed, female healthy subjects following administration of a single 100 mg VEN; The shaded areas illustrate the 90% prediction intervals.
Boxplots showing the predicted exposure of VEN 100 mg qd in subjects of different CYP2C19 genotype when administered with VCZ 200 mg bid under steady state condition. The 400 mg VEN (therapeutic dose) and 1200 mg VEN (maximal administered dose)(40) are shown for reference. qd, once daily; bid, twice daily
Boxplots showing the predicted exposure of VEN 100 mg qd in the presence of VCZ AUC12 of 17.5 or 75.0 μg∙h/ml. 400 mg VEN (therapeutic dose) and 1200 mg VEN (maximal administered dose) are shown for reference. qd, once daily
Purpose Venetoclax (VEN), an anti-tumor drug that is a substrate of cytochrome P450 3A enzyme (CYP3A4), is used to treat leukemia. Voriconazole (VCZ) is an antifungal medication that inhibits CYP3A4. The goal of this study is to predict the effect of VCZ on VEN exposure. Method Two physiological based pharmacokinetics (PBPK) models were developed for VCZ and VEN using the bottom-up and top-down method. VCZ model was also developed to describe the effect of CYP2C19 polymorphism on its pharmacokinetics (PK). The reversible inhibition constant (Ki) of VCZ for CYP3A4 was calibrated using drug-drug interaction (DDI) data of midazolam and VCZ. The clinical verified VCZ and VEN model were used to predict the DDI of VCZ and VEN at clinical dosing scenario. Result VCZ model predicted VCZ exposure in the subjects of different CYP2C19 genotype and DDI related fold changes of sensitive CYP3A substrate with acceptable prediction error. VEN model can capture PK of VEN with acceptable prediction error. The DDI PBPK model predicted that VCZ increased the exposure of VEN by 4.5–9.6 fold. The increase in VEN exposure by VCZ was influenced by subject’s CYP2C19 genotype. According to the therapeutic window, VEN dose should be reduced to 100 mg when co-administered with VCZ. Conclusion The PBPK model developed here could support individual dose adjustment of VEN and DDI risk assessment. Predictions using the robust PBPK model confirmed that the 100 mg dose adjustment is still applicable in the presence of VCZ with high inter-individual viability.
Purpose Increasing the efficiency of unsuccessful immunotherapy methods is one of the most important research fields. Therefore, the use of combination therapy is considered as one of the ways to increase the effectiveness of the dendritic cell (DC) vaccine. In this study, the inhibition of immune checkpoint receptors such as LAG3 and PD-1 on T cells was investigated to increase the efficiency of T cells in response to the DC vaccine. Methods We used trimethyl chitosan-dextran sulfate-lactate (TMC-DS-L) nanoparticles (NPs) loaded with siRNA molecules to quench the PD-1 and LAG3 checkpoints’ expression. Results Appropriate physicochemical characteristics of the generated NPs led to efficient inhibition of LAG3 and PD-1 on T cells, which was associated with increased survival and activity of T cells, ex vivo. Also, treating mice with established breast tumors (4T1) using NPs loaded with siRNA molecules in combination with DC vaccine pulsed with tumor lysate significantly inhibited tumor growth and increased survival in mice. These ameliorative effects were associated with increased anti-tumor T cell responses and downregulation of immunosuppressive cells in the tumor microenvironment and spleen. Conclusion These findings strongly suggest that TMC-DS-L NPs loaded with siRNA could act as a novel tool in inhibiting the expression of immune checkpoints in the tumor microenvironment. Also, combination therapy based on inhibition of PD-1 and LAG3 in combination with DC vaccine is an effective method in treating cancer that needs to be further studied.
Purposes In reducing capillary electrophoresis sodium dodecyl sulfate (CE-SDS) analysis of a monoclonal antibody (mAb-1), the peak area ratio of heavy chain (HC) to light chain (LC) was out of balance, while multiple artifact peaks were observed following the migration of HC. The main purposes of this study were to describe the techniques utilized to eliminate this artifact and clarify the root cause for this interesting phenomenon. Methods We optimized the CE-SDS analysis of mAb-1 by a vairety of techniques including changing the concentration of protein or replacing SDS with a more hydrophobic surfactant (i.e., sodium hexadecyl sulfate (SHS) or sodium tetradecyl sulfate (STS) instead of SDS) in sample and/or the sieving gel buffer. Dynamic light scattering (DLS) and reversed phase high-performance liquid chromatography (RP-HPLC) were used to study the protein-surfactant complex. Results The artifact could be partially mitigated by reducing the protein concentration and replacing SDS with SHS or STS in the sample and/or the sieving gel buffer solutions. Due to replacing a more hydrophobic surfactant, the HC-surfactant complex formed was more resistant to dissociation, preventing additional hydrophobic HC-HC interaction and aggregation, thus eliminating the artifact problem. Conclusions DLS and RP-HPLC are powerful supplementary techniques in characterizing the protein-surfactant complex, and hydrophobic surfactants such as SHS and STS could afford more normal electropherograms during the analysis of mAbs.
Purpose Semaglutide is the only oral GLP-1 RA in the market, but oral bioavailability is generally limited in range of 0.4–1%. In this study, a new GLP-1RA named SHR-2042 was developed to gain higher oral bioavailability than semaglutide. Method Self-association of SHR-2042, semaglutide and liraglutide were assessed using SEC-MALS. The intestinal perfusion test in SD rats was used to select permeation enhancers (PEs) including SNAC, C10 and LCC. ITC, CD and DLS were used to explore the interaction between SHR-2042 and SNAC. Gastric administrated test in SD rats was used to screen SHR-2042 granules with different SHR-2042/SNAC ratios. The oral bioavailability of SHR-2042 was studied in rats and monkeys. Result The designed GLP-1RA, SHR-2042, gives a better solubility and lipophilicity than semaglutide. While it forms a similar oligomer with that of semaglutide. During the selection of PEs, SNAC shows better exposure than the other competing PEs including C10 and LCC. SHR-2042 and SNAC bind quickly and exhibit hydrophobic interaction. SNAC could promote monomerization of SHR-2042 and form micelles to trap the monomerized SHR-2042. The oral bioavailability of SHR-2042 paired with SNAC is 0.041% (1:0, w/w), 0.083% (1:10, w/w), 0.32% (1:30, w/w) and 2.83% (1:60, w/w) in rats. And the oral bioavailability of SHR-2042 matched with SNAC is 3.39% (1:30, w/w) in monkeys, which is over 10 times higher than that of semaglutide. Conclusion We believe that the design and development of oral SHR-2042 will provide a new way to design more and more GLP-1RAs with high oral bioavailability in the future.
Purpose Chlorhexidine digluconate (CHG) is a first-line antiseptic agent typically applied to the skin as a topical solution prior to surgery due to its efficacy and safety profile. However, the physiochemical properties of CHG limits its cutaneous permeation, preventing it from reaching potentially pathogenic bacteria residing within deeper skin layers. Thus, the utility of a solid oscillating microneedle system, Dermapen®, and a CHG-hydroxyethylcellulose (HEC) gel were investigated to improve the intradermal delivery of CHG. Methods Permeation of CHG from the commercial product, Hibiscrub®, and HEC-CHG gels (containing 1% or 4% CHG w/w) was assessed in intact skin, or skin that had been pre-treated with microneedles of different array numbers, using an Franz diffusion cells and Time-of-Flight Secondary Ion Mass Spectrometry (ToF–SIMS). Results Gels containing 1% and 4% CHG resulted in significantly increased depth permeation of CHG compared to Hibiscrub® (4% w/v CHG) when applied to microneedle pre-treated skin, with the effect being more significant with the higher array number. ToF–SIMS analysis indicated that the depth of dermal penetration achieved was sufficient to reach the skin strata that typically harbours pathogenic bacteria, which is currently inaccessible by Hibiscrub®, and showed potential lateral diffusion within the viable epidermis. Conclusions This study indicates that HEC-CHG gels applied to microneedle pre-treated skin may be a viable strategy to improve the permeation CHG into the skin. Such enhanced intradermal delivery may be of significant clinical utility for improved skin antisepsis in those at risk of a skin or soft tissue infection following surgical intervention.
Mean concentration versus time profile of acyclovir in n = 12 participants in the polysorbate 80 and placebo arms. Participants took 400 mg polysorbate 80 or placebo BID for 6 days. On day 7, participants were administered a single dose of 500 mg valacyclovir, 250 mg CDCA, and 20 mg enalaprilat, as well as 400 mg polysorbate 80 in polysorbate 80 arm. Polysorbate 80 had no effect on the plasma concentrations of acyclovir. Data are expressed as mean ± SEM.
Mean concentration versus time profile of CDCA in n = 12 participants in the polysorbate 80 and placebo arms. Polysorbate 80 had no effect on the plasma concentrations of CDCA. Data are not baseline corrected. Data are expressed as mean ± SEM.
Mean concentration versus time profile of enalaprilat in n = 12 participants in the polysorbate 80 and placebo arms. Polysorbate 80 had no effect on the plasma concentrations of enalaprilat. Data are expressed as mean ± SEM.
Purpose Despite no broad, direct evidence in humans, there is a potential concern that surfactants alter active or passive drug intestinal permeation to modulate oral drug absorption. The purpose of this study was to investigate the impact of the surfactant polysorbate 80 on active and passive intestinal drug absorption in humans. Methods The human (n = 12) pharmacokinetics (PK) of three probe substrates of intestinal absorption, valacyclovir, chenodeoxycholic acid (CDCA), and enalaprilat, were assessed. Endogenous bile acid levels were assessed as a secondary measure of transporter and microbiota impact. Results Polysorbate 80 did not inhibit peptide transporter 1 (PepT1)- or apical sodium bile acid transporter (ASBT)-mediated PK of valacyclovir and CDCA, respectively. Polysorbate 80 did not increase enalaprilat absorption. Modest increases in unconjugated secondary bile acid Cmax ratios suggest a potential alteration of the in vivo intestinal microbiota by polysorbate 80. Conclusions Polysorbate 80 did not alter intestinal membrane fluidity or cause intestinal membrane disruption. This finding supports regulatory relief of excipient restrictions for Biopharmaceutics Classification System-based biowaivers.
Purpose The generalizability of numerous tacrolimus population pharmacokinetic (popPK) models constructed to promote optimal tacrolimus dosing in patients with primary nephrotic syndrome (PNS) is unclear. This study aimed to evaluate the predictive performance of published tacrolimus popPK models for PNS patients with an external data set. Methods We prospectively collected 223 concentrations from 50 Chinese adult patients with PNS who were undergoing tacrolimus treatment. Data on published tacrolimus popPK models for adults and children with PNS were extracted from the literature. Model predictability was evaluated with prediction-based and simulation-based diagnostics and Bayesian forecasting. Results In prediction-based evaluation, none of the 11 identified published popPK models of tacrolimus had met a predefined criteria of a mean prediction error ≤ ± 20%, and the prediction error within ± 30% of the identified models didn’t exceed 50%. Simulation-based diagnostics also indicated unsatisfactory predictability. Bayesian forecasting demonstrated amelioration in the model predictability with the inclusion of 2–3 prior observations. Moreover, the predictive performance of nonlinear models was not better than that of one-compartment models. Conclusions The prediction of tacrolimus concentrations for patients with PNS remains challenging; published models are not applicable for extrapolation to other hospitals. Bayesian forecasting significantly improved model predictability and thereby helped to individualize tacrolimus dosing.
Simulation results and clinical data enabling characterization of sub-model behavior and several important aspects of NASH pathophysiology as simulated by NAFLDsym. The relationship between liver fat and plasma ALT in the simulated patients is quite similar to the measured data from Maximos et al. (a); the simulated population retains a distribution of BMI that is comparable to the clinical data reported by Dudekala et al. (b); the relationship between fat mass and adipose fatty acid (FA) release rates is comparable between the simulated patients and the clinical data reported by Mittendorfer et al. Note that there are few simulated patients with adipose FA release rates in excess of 50 mmol/h (c); the ranges of de novo lipogenesis (DNL) and liver fat are comparable between the simulated patients and the clinical data reported by Lambert et al. and Smith et al. (d); the number of lobular macrophages in NAFLD and NASH patients is consistent with the clinical data reported by Tajiri et al. Note that there are minimal differences between patients below or above NAS = 4. (e); the range of TGF-beta levels in simulated patients and clinical cohorts with varying plasma ALT levels, as reported by Dal et al. (f); synthesis rates and quantities of hepatic collagen type I in clinical and simulated patients across a range of fibrosis scores. Clinical data were reported by Decaris et al. and Masugi et al. Clinical patients with fibrosis stage = 4 were excluded from figure, as data for only two patients were reported. (g,h). In each figure, black or grey symbols represent clinical data sets while red symbols represent simulated patients. In figures a, c-h, individual simulated patients are displayed.
Simulation results and clinical data describing the correspondence between the simulated histologic components of NAS with related outputs. The range of cytokeratin-cleaved K18 (cK18) and histologic ballooning (a), liver fat measured by MRI-PDFF and histologic steatosis (b), andCCL3 and histologic lobular inflammation scores. Red bars or symbols denote results from simulated patients while black symbols and black bars denote clinical data from Aida et al. (a), Middleton et al. (b), and du Plessis et al. (c).
Simulation results for untreated simulated patients within SimPops in NAFLDsym, including liver fat (a, units are %), plasma ALT (b, units are U/L), NAS (c), fibrosis stage (d), and BMI (e, units are kg/m²). Note that each simulated patient retains the same position on each radial plot.
Simulation results and clinical data illustrating the appropriate degree of relief in simulated NASH patients in response to 5–10% weight loss achieved via restriction of caloric intake. Liver fat before and after six months of 10% weight loss, as compared with clinical data from Smith et al. Mean responses and individual simulated and clinical patient results displayed (a); absolute change in overall NAS and respective components after 5–7% weight loss over 12 months, as compared with clinical data from Vilar-Gomez et al. and Hameed et al. Note that a negative value indicates reduction relative to initial values (b); fraction of patients with worsened, stabilized, or regressed fibrosis stage after 12 months of 5–7% weight loss, as compared with clinical data from Vilar-Gomez et al. (c). Clinical results are summarized in figure on left, while simulation results are in figure on right Red bars or symbols denote results from SimCohorts while black or gray symbols denote clinical data.
Predicted relative changes (left) in and absolute levels (right) of body weight (a, b), liver fat (c, d), plasma ALT (e, f), and liver collagen (g,h) in NASH SimCohorts over time due to yo-yo dieting. Mean ± standard deviation plotted for all figures.
Nonalcoholic steatohepatitis (NASH) is a widely prevalent disease, but approved pharmaceutical treatments are not available. As such, there is great activity within the pharmaceutical industry to accelerate drug development in this area and improve the quality of life and reduce mortality for NASH patients. The use of quantitative systems pharmacology (QSP) can help make this overall process more efficient. This mechanism-based mathematical modeling approach describes both the pathophysiology of a disease and how pharmacological interventions can modify pathophysiologic mechanisms. Multiple capabilities are provided by QSP modeling, including the use of model predictions to optimize clinical studies. The use of this approach has grown over the last 20 years, motivating discussions between modelers and regulators to agree upon methodologic standards. These include model transparency, documentation, and inclusion of clinical pharmacodynamic biomarkers. Several QSP models have been developed that describe NASH pathophysiology to varying extents. One specific application of NAFLDsym, a QSP model of NASH, is described in this manuscript. Simulations were performed to help understand if patient behaviors could help explain the relatively high rate of fibrosis stage reductions in placebo cohorts. Simulated food intake and body weight fluctuated periodically over time. The relatively slow turnover of liver collagen allowed persistent reductions in predicted fibrosis stage despite return to baseline for liver fat, plasma ALT, and the NAFLD activity score. Mechanistic insights such as this that have been derived from QSP models can help expedite the development of safe and effective treatments for NASH patients.
The use of physiologically based pharmacokinetic (PBPK) modeling to support the drug product quality attributes, also known as physiologically based biopharmaceutics modeling (PBBM) is an evolving field and the interest in using PBBM is increasing. The US-FDA has emphasized on the use of patient centric quality standards and clinically relevant drug product specifications over the years. Establishing an in vitroin vivo link is an important step towards achieving the goal of patient centric quality standard. Such a link can aid in constructing a bioequivalence safe space and establishing clinically relevant drug product specifications. PBBM is an important tool to construct a safe space which can be used during the drug product development and lifecycle management. There are several advantages of using the PBBM approach, though there are also a few challenges, both with in vitro methods and in vivo understanding of drug absorption and disposition, that preclude using this approach and therefore further improvements are needed. In this review we have provided an overview of experience gained so far and the current perspective from regulatory and industry point of view. Collaboration between scientists from regulatory, industry and academic fields can further help to advance this field and deliver on promises that PBBM can offer towards establishing patient centric quality standards.
Selected PBPK modeling applications. AHD: anticipated human dose or dosing regimen; DDI: drug-drug interaction, PPI: proton pump inhibitor, ARA: acid reducing agent.
Selected PBPK model components: frequently used system- and drug-specific parameters in a PBPK Model. Modified after Jamei M et al. (142). pKa: -log10 dissociation constant; B:P: blood to plasma partition ratio; fu: free fraction of drug in plasma; Km: Michaelis constant; Vmax: velocity of enzyme-catalyzed reaction at infinite concentration of substrate; fuinc: incubational binding or the fraction of drug unbound in an in vitro incubation.
Pediatric PBPK workflow modified from Lin W et al. 2016 (143).
of PBPK model performance in organ impairment populations. A. Summary of model predictive performance in renal organ impairment (a) Comparison of predicted to observed AUC ratios of renal impairment (RI) patients to matched healthy control subjects (N = 8 mild, 14 moderate, 25 severe, 3 end stage renal disease [ESRD]). Solid markers represent the major metabolite of N314T. (b) Comparison of predicted to observed Cmax ratios of renal impairment patients to matched healthy control subjects (N = 8 mild, 14 moderate, 25 severe, 3 ESRD). (c) Comparison of predicted to observed fraction unbound in plasma of renal impairment patients (N = 15 healthy, 4 mild, 6 moderate, 15 severe). Figure from Heimbach, Clin Pharmacol Ther. 2021 (79). B. Summary of model predictive performance in hepatic organ impairment. Comparison of predicted to observed AUC ratios of hepatic impairment patients to matched healthy subjects (a) CP-A (N = 18 mild), (b) CP-B (N = 25 moderate), and (c) CP-C (N = 13 severe). Closed symbols represent compounds with CLiv < 20L/h and open symbols represent compounds with CLiv > 20 L/h. Comparison of predicted to observed Cmax ratios of hepatic impairment patients to matched healthy subjects (d) CP-A (N = 18 mild), (e) CP-B (N = 25 moderate), and (f) CP-C (N = 13 severe). Figure from Heimbach, Clin Pharmacol Ther. 2021 (79). C. Summary of the predictive performance of published models for 20 different drugs in hepatic impairment populations with different severities (mild, moderate and severe cirrhosis). Data were obtained from 14 studies. Figures from El-Khateeb, Aliment Pharmacol Ther, 2021(144). D. Summary of predicted AUCR and CLrR vs. observed values for 7 drugs. The black solid line is the unity line. Dashed and dotted lines denote 0.67–1.5 × criterion and 0.8–1.25 × criterion, respectively. ADV, adefovir; AUCR, ratios of area under the curves (CKD [chronic kidney disease]/HS [healthy subject]); AVI, avibactam; CLrR, ratios of renal clearances (CKD/HS); ETV, entecavir; FAM, famotidine; GCV, ganciclovir; OC, oseltamivir carboxylate; SITA, sitagliptin. Figure from Hsueh Clin Pharmacol Ther. 2018 (78). E. Summary of observed versus predicted AUC ratios for 7 drugs in mild, moderate, and severe RI populations compared with healthy subjects using (a) PBPK model, (b) static model. *Figures include case 1 predictions based on phase 1 data, cidofovir predictions with fu adjustment, and both day 1 and day 6 predictions for OC. Solid line represents unity, and dotted lines represent 0.5‐ and twofold changes. Figures from Yee L. Clin Pharma and Therapeutics, 2017 (77).
(A) Example PBPK workflow for ARA-DDI, modified from Mitra et. al (128). (B). Potential workflow for including PBBM/PBPK to assess pH-mediated DDI of new drug candidates using dissolution data and PBPK modeling. Modified from Reference:(53).
Several regulatory guidances on the use of physiologically based pharmacokinetic (PBPK) analyses and physiologically based biopharmaceutics model(s) (PBBM(s)) have been issued. Workshops are routinely held, demonstrating substantial interest in applying these modeling approaches to address scientific questions in drug development. PBPK models and PBBMs have remarkably contributed to model-informed drug development (MIDD) such as anticipating clinical PK outcomes affected by extrinsic and intrinsic factors in general and specific populations. In this review, we proposed practical considerations for a “base” PBPK model construction and development, summarized current status, challenges including model validation and gaps in system models, and future perspectives in PBPK evaluation to assess a) drug metabolizing enzyme(s)- or drug transporter(s)- mediated drug-drug interactions b) dosing regimen prediction, sampling timepoint selection and dose validation in pediatric patients from newborns to adolescents, c) drug exposure in patients with renal and/or and hepatic organ impairment, d) maternal–fetal drug disposition during pregnancy, and e) pH-mediated drug-drug interactions in patients treated with proton pump inhibitors/acid-reducing agents (PPIs/ARAs) intended for gastric protection. Since PBPK can simulate outcomes in clinical studies with enrollment challenges or ethical issues, the impact of PBPK models on waivers and how to strengthen study waiver is discussed.
Evolution of MIDD at the FDA. A brief summary of key highlights for every decade with future aspirations are provided. Abbreviations: ICIVC – in vitro-in vivo correlation; PK/PD – pharmacokinetics/pharmacodynamics; popPK – population pharmacokinetics; D/R – dose-response; E/R – exposure-response; CTS – clinical trial simulations; EOP2A – end of phase 2A; PBPK – physiologically based pharmacokinetics; DDI – drug-drug interactions; DDT – drug development tools; MIDD – model-informed drug development; QCP – quantitative clinical pharmacology; PBBM – physiologically based biopharmaceutics models; RWD/RWE – real world data/real world evidence; RTRT – real time release test; MIE – model-integrated evidence; PDUFA - Prescription Drug User Fee Act.
Relationship between clinical trials and relevant in vitro tests illustrating the concept of nested surrogacy. Abbreviations: S&E – safety and efficacy; PK – pharmacokinetics; PK/PD – pharmacokinetics/pharmacodynamics.
Commonly used MIDD toolsets in generic drug development. Abbreviations: BE – bioequivalence; PK – pharmacokinetics; PBPK – physiologically based pharmacokinetics; ANDA – abbreviated new drug application.
Model-informed drug development (MIDD) is a powerful approach to support drug development and regulatory review. There is a rich history of MIDD applications at the U.S. Food and Drug Administration (FDA). MIDD applications span across the life cycle of the development of new drugs, generics, and biologic products. In new drug development, MIDD approaches are often applied to inform clinical trial design including dose selection/optimization, aid in the evaluation of critical regulatory review questions such as evidence of effectiveness, and development of policy. In the biopharmaceutics space, we see a trend for increasing role of computational modeling to inform formulation development and help strategize future in vivo studies or lifecycle plans in the post approval setting. As more information and knowledge becomes available pre-approval, quantitative mathematical models are becoming indispensable in supporting generic drug development and approval including complex generic drug products and are expected to help reduce overall time and cost. While the application of MIDD to inform the development of cell and gene therapy products is at an early stage, the potential for future application of MIDD include understanding and quantitative evaluation of information related to biological activity/pharmacodynamics, cell expansion/persistence, transgene expression, immune response, safety, and efficacy. With exciting innovations on the horizon, broader adoption of MIDD is poised to revolutionize drug development for greater patient and societal benefit.
Practical challenges faced by the biopharmaceutical industry and considerations that should be part of modern clinical development in oncology (independent of modality)
After a drug molecule enters clinical trials, there are primarily three levers to enhance probability of success: patient selection, dose selection and choice of combination agents. Of these, dose selection remains an under-appreciated aspect in oncology drug development despite numerous peer-reviewed publications. Here, we share practical challenges faced by the biopharmaceutical industry that reduce the willingness to invest in dose finding for oncology drugs. First, randomized dose finding admittedly slows down clinical development. To reduce the size of dose finding study, trend in exposure vs. tumor-size analysis can be assessed, instead of a statistical test for non-inferiority between multiple doses. Second, investment in testing a lower dose when benefit-risk at the higher dose is sufficient for regulatory approval (i.e., efficacy at the higher dose is better than standard of care and safety is acceptable) is perceived as low priority. Changing regulatory landscape must be considered to optimize dose in pre-marketing setting as post-marketing changes in dose can be commercially costly. Third, the risk of exposing patients to subtherapeutic exposures with a lower dose should be assessed scientifically instead of assuming a monotonic relationship between dose and efficacy. Only the doses which are expected to be at the plateau of dose/exposure–response curve should be investigated in Phase 1b/2. Overall, changing the perceptions that have been impeding investment in dose finding in oncology requires pragmatic discourse among biopharmaceutical industry, regulatory agencies and academia. These perceptions should also not deter dose finding for recently emerging modalities, including BITEs and CART cell therapies.
The diagram shows the over-arching strategy in PBPK modeling and its applications. A question of interest and its context of use define the inherent stages of model development. For model building and evaluation, the modeler should consider the balance of ‘bottom-up’ and ‘top-down’ modeling techniques, availability and feasibility of previously established cases and platforms, and apply best practices at every stage. If a model can adequately be verified considering the key property of the model relevant for the intended use, it can be applied. In many cases applications cover conditions, which are untested or untestable at that given time. Hence, ‘validation’ comes at much later stages (if at all) to be of any practical benefit for the intended purpose. However, this can be used as ‘verification set’ for future scenarios. Details on the specific stages of model development are outlined in the respective sections of the section PBPK Modeling Analysis.
Overview on the quality assurance framework of PBPK software platforms. Suppliers of dedicated specialized PBPK platforms should provide a battery of quality assurance documents to demonstrate platform validation and a series of potential platform qualifications for intended purposes. Modelers using such platforms are responsible to ensure that the potential platform qualification is appropriate within a dedicated analysis. Modelers are responsible for platform qualification on its own only if the intended use is a novel application for which the platform provider has no qualification documents. Details are presented in the section PBPK Platform
Questions on how to assess quality of a PBPK modeling analysis. Assessing the quality of a PBPK modeling analysis is a long process and involves several steps. Some elements of quality assessment can be facilitated if the software platform has adequate qualification for the intended use of the PBPK model. However, if the platform does not contain such qualifications (e.g., a novel application of the platform) or the platform is not a purpose-built environment for the PBPK modeling, then the modeler has the extra burden of creating such qualifications. The questions are closely linked to the step-by-step framework for dedicated PBPK modeling analyses from defining a question of interest to arrive at the application of PBPK modeling under the umbrella of qualification presented in the section PBPK Modeling Analysis
Modeling and simulation emerges as a fundamental asset of drug development. Mechanistic modeling builds upon its strength to integrate various data to represent a detailed structural knowledge of a physiological and biological system and is capable of informing numerous drug development and regulatory decisions via extrapolations outside clinically studied scenarios. Herein, physiologically based pharmacokinetic (PBPK) modeling is the fastest growing branch, and its use for particular applications is already expected or explicitly recommended by regulatory agencies. Therefore, appropriate applications of PBPK necessitates trust in the predictive capability of the tool, the underlying software platform, and related models. That has triggered a discussion on concepts of ensuring credibility of model-based derived conclusions. Questions like ‘why’, ‘when’, ‘what’, ‘how’ and ‘by whom’ remain open. We seek for harmonization of recent ideas, perceptions, and related terminology. First, we provide an overview on quality assurance of PBPK platforms with the two following concepts. Platform validation: ensuring software integrity, security, traceability, correctness of mathematical models and accuracy of algorithms. Platform qualification: demonstrating the predictive capability of a PBPK platform within a particular context of use. Second, we provide guidance on executing dedicated PBPK studies. A step-by-step framework focuses on the definition of the question of interest, the context of use, the assessment of impact and risk, the definition of the modeling strategy, the evaluation of the platform, performing model development including model building, evaluation and verification, the evaluation of applicability to address the question, and the model application under the umbrella of a qualified platform.
Components of a Disease Progression Model for Use in Drug Development.
Flow of Information from Data Source to DPM Development Utilization*. *Information Propagates from Data Sources (light green nodes) to Utilization (brown, tan, lavender, and pink nodes) through Data Types (red nodes) and Model Types (light red, purple, and light purple nodes). The Evolution of DPMs is Depicted by Linkage Color. The light blue linkages are the earliest, which expanded to include natural history data sources (dark blue) and Aggregate Level Data Types (green). The Current State Includes Non-clinical Data Sources and Mechanistic DPM (peach). Real World Evidence (orange linkages) is Depicted as Potential Future State.
Schematic of BPD Disease Progression with Variables of Clinical Interest Linked to Stage of Progression.
The use of Disease progression models (DPMs) in Drug Development has been widely adopted across therapeutic areas as a method for integrating previously obtained disease knowledge to elucidate the impact of novel therapeutics or vaccines on disease course, thus quantifying the potential clinical benefit at different stages of drug development programs. This paper provides a brief overview of DPMs and the evolution in data types, analytic methods, and applications that have occurred in their use by Quantitive Clinical Pharmacologists. It also provides examples of how these models have informed decisions and clinical trial design across several therapeutic areas and at various stages of development. It briefly describes potential new applications of DPMs utilizing emerging data sources, and utilizing new analytic techniques, and discuss new challenges faced such as requiring description of multiple endpoints, rapid model development, application of machine learning-based analytics, and use of high dimensional and real-world data. Considerations for the continued evolution future of DPMs to serve as community-maintained expert systems are also provided.
Schematic representation of the workflow for the simulations including parameter uncertainty. Distribution of CFB in RS-Total for each simulation considering 15,000 subjects and the mean (95%CI) CBF in RS-Total obtained from the average CFB of each simulation
Mean (95%CI) CFB in RS-Total at 4-week intervals for observed data (yellow) and predicted values from the IRT (blue). Green dashed line indicates the MCID target
Mean (95%CI) for CFB in RS-Total at 4-week intervals simulated with IRT (blue) and published MMRM values (red). Green dashed line indicates the MCID target. Values correspond to the relative sample size (Eq. 4)
Purpose The current study aimed to illustrate how a non-linear mixed effect (NLME) model-based analysis may improve confidence in a Phase III trial through more precise estimates of the drug effect. Methods The FULFIL clinical trial was a Phase III study that compared 24 weeks of once daily inhaled triple therapy with twice daily inhaled dual therapy in patients with chronic obstructive pulmonary disease (COPD). Patient reported outcome data, obtained by using The Evaluating Respiratory Symptoms in COPD (E-RS:COPD) questionnaire, from the FULFIL study were analyzed using an NLME item-based response theory model (IRT). The change from baseline (CFB) in E-RS:COPD total score over 4-week intervals for each treatment arm was obtained using the IRT and compared with published results obtained with a mixed model repeated measures (MMRM) analysis. Results The IRT included a graded response model characterizing item parameters and a Weibull function combined with an offset function to describe the COPD symptoms-time course in patients receiving either triple therapy (n = 907) or dual therapy (n = 894). The IRT improved precision of the estimated drug effect compared to MMRM, resulting in a sample size of at least 3.64 times larger for the MMRM analysis to achieve the IRT precision in the CFB estimate. Conclusion This study shows the advantage of IRT over MMRM with a direct comparison of the same primary endpoint for the two analyses using the same observed clinical trial data, resulting in an increased confidence in Phase III.
Bar chart of search results of MBMA by year
Case study 1: Comparative MBMA of ICI safety data in monotherapy and combination setting. A Estimation of adjusted ICIs exposure: step 1, using published population PK models to simulate typical ICI exposure in the cohort; step 2, exposure adjustment based on the published ICIs potency data. B Exposure-safety dependence of total grade 3/4 AEs upon PD-1 monotherapy. C Exposure-safety dependence of total grade 3/4 AEs upon CTLA-4 mono- (red) and CTLA-4 + PD-1 combination (green) therapy. Individual trials used for model calibration are shown with circles, diameter corresponds to sample size, and 90% confidence interval are represented by respective bands. D) Simulation of exposure-safety dependence of total grade 3/4 AEs upon PD-1 (green) and PD-L1 (blue) monotherapy. E) Simulation of exposure-safety dependence of total grade 3/4 AEs upon CTLA-4 mono- (red), CTLA-4 + PD-1 (green) and CTLA-4 + PD-L1 (blue) combination therapies
Simulations based on the rheumatoid arthritis MBMA model
Schematic of overall MBMA process
Model-based meta-analysis (MBMA) is a quantitative approach that leverages published summary data along with internal data and can be applied to inform key drug development decisions, including the benefit-risk assessment of a treatment under investigation. These risk–benefit assessments may involve determining an optimal dose compared against historic external comparators of a particular disease indication. MBMA can provide a flexible framework for interpreting aggregated data from historic reference studies and therefore should be a standard tool for the model-informed drug development (MIDD) framework. In addition to pairwise and network meta-analyses, MBMA provides further contributions in the quantitative approaches with its ability to incorporate longitudinal data and the pharmacologic concept of dose–response relationship, as well as to combine individual- and summary-level data and routinely incorporate covariates in the analysis. A common application of MBMA is the selection of optimal dose and dosing regimen of the internal investigational molecule to evaluate external benchmarking and to support comparator selection. Two case studies provided examples in applications of MBMA in biologics (durvalumab + tremelimumab for safety) and small molecule (fenebrutinib for efficacy) to support drug development decision-making in two different but well-studied disease areas, i.e., oncology and rheumatoid arthritis, respectively. Important to the future directions of MBMA include additional recognition and engagement from drug development stakeholders for the MBMA approach, stronger collaboration between pharmacometrics and statistics, expanded data access, and the use of machine learning for database building. Timely, cost-effective, and successful application of MBMA should be part of providing an integrated view of MIDD.
Purpose Recently, docetaxel (DTX) micelles based on retinoic acid derivative surfactants showed lower systemic toxicity and bioequivalence to polysorbate-solubilized docetaxel (Taxotere®) in a phase II clinical study. However, the poor stability of these surfactants in vitro and in vivo led to extremely harsh storage conditions with methanol, and the formed micelles were quickly disintegrated with rapid drug burst release in vivo. To further enhance the stability and accumulation in tumors of DTX micelles, a novel surfactant based on acitretin (ACMeNa) was synthesized and used to prepare DTX micelles to improve anti-tumor efficiency. Methods Novel micelle-forming excipients were synthesized, and the micelles were prepared using the thin film hydration technique. The targeting effect in vitro, distribution in the tumor, and its mechanism were observed. Pharmacokinetics and anti-tumor effect were further investigated in rats and tumor-bearing female mice, respectively. Results The DTX-micelles prepared with ACMeNa (ACM-DTX) exhibited a small size (21.9 ± 0.3 nm), 39% load efficiency, and excellent stability in vitro and in vivo. Long circulation time, sustained and steady accumulation, and strong penetration in the tumor were observed in vivo, contributing to a better anti-tumor effect and lower adverse effects. Conclusions The micelles formed by ACMeNa showed a better balance between anti-tumor and adverse effects. It is a promising system for delivering hydrophobic molecules for cancer therapy. Graphical abstract
This article presents the effects of an imidazolium-based ionic liquid (IL) on the thermodynamics and in-plane viscoelastic properties of model membranes of anionic phospholipids. The negative Zeta potential of multilamellar vesicles of 14 carbon lipid 1,2-dimyristoyl-sn-glycero-3-phospho-(1'-rac-glycerol) (DMPG) is observed to reduce due to the presence of few mole % of an IL 1-butyl-3-methylimidazolium tetrafluoroborate ([BMIM][BF4]). The effect was found to be stronger on enhancing the chain length of the lipid. The surface pressure–area isotherms of lipid monolayer formed at air–water interface are modified by the IL reducing the effective area per molecule. Further, the equilibrium elasticity of the film is altered depending upon the thermodynamic phase of the lipids. While the presence of the IL in the DMPG lipid makes it ordered in the gel phase by reducing the entropy, the effect is opposite in the fluid phase. The in-plane viscoelastic parameters of the lipid film is quantified by dilation rheology using the oscillatory barriers of a Langmuir trough. Even though the low chain lipid DMPG does not show any effect of IL on its storage and loss moduli, the longer chain lipids exhibit a prominent effect in the liquid extended (LE) phase. Further, the dynamic response of the lipid film is found to be distinctly different in the liquid condensed (LC) phase from that of the LE phase.
Schematic diagram of administration operation. (a) Intratracheal aerosol nebulization in mice; (b) Facial inhalation using Jet NE-C28 Nebulizer for Cynomolgus monkeys.
Neutralizing activity of HB27 antibody against SARS-CoV-2 pseudovirus in vitro (Mean ± SD).
Assessment of HB27 stability and binding activity upon nebulization. (a) The purities of the samples prior to nebulization (blue chromatogram) and post nebulization (red chromatogram) were analyzed with SEC-HPLC; (b) The RBD-binding activities were detected by ELISA.
HB27 antibody concentrations in serum and ELF after intravenous administration (i.v.) or intratracheal nebulization (i.t.) in mice (n = 6). (a) Concentration–time profiles in serum and ELF were compared after intravenous administration of 5 mg/kg HB27 antibody in C57BL/6 mice (Mean ± SD). Dashed lines represent in vitro neutralization activity of HB27 against authentic SARS-CoV-2 by plaque reduction neutralization test (PRNT) in Vero cells [1]. (b) The percentages of CELF / Cserum in different time points are shown as Mean ± SD. (c) Concentration–time profiles in serum and ELF were compared after a single dose of 5 mg/kg nebulized HB27 antibody to BALB/c mice. (d) Antibody concentrations (Mean ± SD) in serum and ELF were detected at 24 h after dosing with a single dose of 5 mg/kg HB27 to C57BL/6 mice and BALB/c mice or 5 repeated doses (once daily) in BALB/c mice (N.S., not significant; ∗∗∗∗ , P < 0.0001).
Lung PK and safety profile after single-dose inhalation of HB27 antibody in cynomolgus monkeys. The HB27 antibody concentrations (a) and cytokine levels (b) in ELF were measured at 24, 48 and 72 h after administration. Dashed line represents PRNT90 (1.28 μg/mL) of HB27 against authentic SARS-CoV-2. The data are shown as Mean ± SD. HB27 antibody in serum could not be quantified below the lower limit of detection (0.39 μg/mL).
Purpose Neutralizing antibodies, administrated through intravenous infusion, have shown to be highly efficacious in treating mild and moderate COVID-19 caused by SARS-CoV-2 infection in the lung. However, antibodies do not transport across the plasma-lung barrier efficiently, and up to 100 mg/kg dose was used in human causing significant supply and cost burdens. This study was to explore the feasibility of nebulized antibodies inhalation delivery as an alternative route. Methods HB27, a potent RBD-specific humanized monoclonal antibody (Zhu et al. in National Sci Rev. 8:nwaa297, 2020), showed excellent protection against SARS-CoV-2 in animal model and good safety profile in clinical studies. The pharmacokinetics and preliminary safety of HB27 administrated through the respiratory tract were studied in mice and cynomolgus monkeys here. Results At a single 5 mg/kg dose, the peak HB27 concentration in mice pulmonary epithelial lining fluid (ELF) reached 857.8 μg/mL, 670-fold higher than the PRNT90 value of 1.28 μg/mL, and maintained above PRNT90 over 240 h. In contrast, when administrated by intravenous injection at a 5 mg/kg dose, the antibody concentrations in mice ELF were below PRNT90 value throughout, and were about 50-fold lower than that in the serum. In cynomolgus monkeys administrated with a single dose through inhalation, the antibody concentration in ELF remained high within 3 days. No drug-related safety concerns were observed in the studies. Conclusions The study demonstrated that nebulized neutralizing antibody delivery though inhalation could be a more efficient and efficacious alternative approach for treating COVID-19 and other respiratory infectious diseases, and warrants further evaluation in clinical studies.
Purpose The impact of dry coating on reduced API agglomeration remains underexplored. Therefore, this work quantified fine cohesive API agglomeration reduction through dry coating and its impact on enhanced blend uniformity and processability, i.e., flowability and bulk density of multi-component blends API loading as low as 1 wt%. Methods The impact of dry coating with two different types and amounts of silica was assessed on cohesion, agglomeration, flowability, bulk density, wettability, and surface energy of fine milled ibuprofen (~ 10 µm). API agglomeration, measured using Gradis/QicPic employing gentler gravity-based dispersion, resulted in excellent size resolution. Multi-component blends with fine-sized excipients, selected for reduced segregation potential, were tested for bulk density, cohesion, flowability, and blend content uniformity. Tablets formed using these blends were tested for tensile strength and dissolution. Result All dry coated ibuprofen powders exhibited dramatic agglomeration reduction, corroborated by corresponding decreased cohesion, unconfined yield strength, and improved flowability, regardless of the type and amount of silica coating. Their blends exhibited profound enhancement in flowability and bulk density even at low API loadings, as well as the content uniformity for the lowest drug loading. Moreover, hydrophobic silica coating improved drug dissolution rate without appreciably reducing tablet tensile strength. Conclusion The dry coating based reduced agglomeration of fine APIs for all three low drug loadings improved overall blend properties (uniformity, flowability, API release rate) due to the synergistic impact of a minute amount of silica (0.007 wt %), potentially enabling direct compression tableting and aiding manufacturing of other forms of solid dosing.
Antimicrobial resistance has become a serious threat to global health. New antimicrobials are thus urgently needed. Ionic liquids (ILs), salts consisting of organic cations and anions with melting points less than 100°C, have been recently found to be promising in antimicrobial field as they may disrupt the bacterial wall and membrane and consequently lead to cell leakage and death. Different types of antimicrobial ILs are introduced in the review, including cationic, polymeric, and anionic ILs. Being the main type of the antimicrobial ILs, the review focuses on the structure and the antimicrobial mechanisms of cationic ILs. The quantitative structure-activity relationship (QSAR) models of the cationic ILs are also included. Increase in alkyl chain length and lipophilicity is beneficial to increase the antimicrobial effects of cationic ILs. Polymeric ILs are homopolymers of monomer ILs or copolymers of ILs and other monomers. They have great potential in the field of antibiotics as they provide stronger antimicrobial effects than the sum of the monomer ILs. Anionic ILs are composed of existing anionic antibiotics and organic cations, being capable to enhance the solubility and bioavailability of the original form. Nonetheless, the medical application of antimicrobial ILs is limited by the toxicity. The structural optimization aided by QSAR model and combination with existing antibiotics may provide a solution to this problem and expand the application range of ILs in antimicrobial field. Graphical Abstract
Objective The therapeutic options for severe asthma are limited, and the biological therapies are all parenterally administered. The purpose of this study was to formulate a monoclonal antibody that targets the receptor for IL-4, an interleukin implicated in the pathogenesis of severe asthma, into a dry powder intended for delivery via inhalation. Methods Dehydration was achieved using either spray drying or spray freeze drying, which exposes the thermolabile biomacromolecules to stresses such as shear and adverse temperatures. 2-hydroxypropyl-beta-cyclodextrin was incorporated into the formulation as protein stabiliser and aerosol performance enhancer. The powder formulations were characterised in terms of physical and aerodynamic properties, while the antibody was assessed with regard to its structural stability, antigen-binding ability, and in vitro biological activity after drying. Results The spray-freeze-dried formulations exhibited satisfactory aerosol performance, with emitted fraction exceeding 80% and fine particle fraction of around 50%. The aerosolisation of the spray-dried powders was hindered possibly by high residual moisture. Nevertheless, the antigen-binding ability and inhibitory potency were unaffected for the antibody in the selected spray-dried and spray-freeze-dried formulations, and the antibody was physically stable even after one-year storage at ambient conditions. Conclusions The findings of this study establish the feasibility of developing an inhaled dry powder formulation of an anti-IL-4R antibody using spray drying and spray freeze drying techniques with potential for the treatment of severe asthma.
The present review describes the state of the art in the conversion of pharmaceutically active ingredients (API) in amphiphilic Ionic Liquids (ILs) as alternative drug delivery systems. In particular, we focus our attention on the compounds generated by ionic exchange and without original counterions which generate different systems in comparison with the simple mixtures. In water, these new amphiphiles show similar or even better properties as surfactants in comparison with their precursors. Cations such as 1-alkyl-3-methyl-imidazolium and anions such as dioctyl sulfosuccinate or sodium dodecyl sulfate appear as the amphiphilic components most studied. In conclusion, this work shows interesting information on several promissory compounds and they appear as an interesting challenge to extend the application of ILs in the medical field.
Custom made intratracheal dosator intended for in vivo delivery to mice using assembled components (Panel A) including: a 1 mL syringe with luer lock connection, 3-way stopcock and a 10 µL pipette tip. Spray dried powder is loaded into the pipette tip and all components are assembled tightly together (Panel B). A full experimental set up is pictured in Panel C, showing the syringe, dosator assembly, 3D mouse trachea model and a powder collection vial.
Model predicted, normalized mass distribution of (A) AdHu5 adenoviral vector and (B) dextran within a mannitol-dextran particle. Radial distance refers to the percentage of distance between the particle core (0%) and the particle surface (100%). Mass% of each component was normalized based on the total amount of that component added to the formulation. Excipient formulations include mannitol and dextran in a ratio by mass of either 1:3 or 3:1, respectively, and a dextran molecular weight of either 40 kDa or 500 kDa.
Viral titre log loss (pfu/mg) of spray dried AdHu5 adenoviral vector with excipient formulations using mannitol with dextran (MD) in a ratio by weight of either 1:3 or 3:1 and either a low molecular weight dextran (40 kDa) or high molecular weight dextran (500 kDa). A xylitol-dextran (XD) formulation with a 1:3 ratio using 40 kDa dextran is also shown. Process loss refers to viral titre loss from spray drying compared to the stock viral titre, while aging losses are associated with the additional viral titre loss after samples were stored at 45°C for 72 h prior to in vitro testing. All samples were tested in duplicate and error bars represent the resulting standard error.
Scanning electron microscope (SEM) images showing particle morphology of the following mannitol-dextran (MD) spray dried powders: (A) MD (1:3)–40 kDa dextran, (B) MD (1:3)–500 kDa dextran (C) MD (3:1)–40 kDa dextran and (D) MD (3:1)–500 kDa dextran. Arrows indicate particle dimpling and indentation likely due to hollow shell formation. All images were captured at 2000 X magnification with a scale bar representing 20 µm in length.
Normalized dose of spray dried powder dispersed from custom made dosator device (Fig. 1), for each respective mannitol-dextran formulation in a mass ratio of either 1:3 or 3:1 using a low molecular weight dextran (40 kDa) or high molecular weight dextran (500 kDa). Emitted dose refers to the powder dosage exiting the needle tip of the dosator upon actuation. Delivered dose represents the percentage of powder collected after powder was sprayed from the dosator and directly through a 3D printed mouse trachea, mimicking endotracheal delivery. Both emitted and delivered dose were normalized based on powder mass initially loaded. Error bars represent standard error between replicate measurements (n = 3)
Purpose Thermally stable, spray dried vaccines targeting respiratory diseases are promising candidates for pulmonary delivery, requiring careful excipient formulation to effectively encapsulate and protect labile biologics. This study investigates the impact of dextran mass ratio and molecular weight on activity retention, thermal stability and aerosol behaviour of a labile adenoviral vector (AdHu5) encapsulated within a spray dried mannitol-dextran blend. Methods Comparing formulations using 40 kDa or 500 kDa dextran at mass ratios of 1:3 and 3:1 mannitol to dextran, in vitro quantification of activity losses and powder flowability was used to assess suitability for inhalation. Results Incorporating mannitol in a 1:3 ratio with 500 kDa dextran reduced viral titre processing losses below 0.5 log and displayed strong thermal stability under accelerated aging conditions. Moisture absorption and agglomeration was higher in dextran-rich formulations, but under low humidity the 1:3 ratio with 500 kDa dextran powder had the lowest mass median aerodynamic diameter (4.4 µm) and 84% emitted dose from an intratracheal dosator, indicating strong aerosol performance. Conclusions Overall, dextran-rich formulations increased viscosity during drying which slowed self-diffusion and favorably hindered viral partitioning at the particle surface. Reducing mannitol content also minimized AdHu5 exclusion from crystalline regions that can force the vector to air–solid interfaces where deactivation occurs. Although increased dextran molecular weight improved activity retention at the 1:3 ratio, it was less influential than the ratio parameter. Improving encapsulation ultimately allows inhalable vaccines to be prepared at higher potency, requiring less powder mass per inhaled dose and higher delivery efficiency.
Purpose Cavitation is an undesired phenomenon that may occur in certain types of autoinjectors (AIs). Cavitation happens because of rapid changes of pressure in a liquid, leading to the formation of small vapor-filled cavities, which upon collapsing, can generate an intense shock wave that may damage the device container and the protein drug molecules. Cavitation occurs in the AI because of the syringe-drug relative displacement as a result of the syringe’s sudden acceleration during needle insertion and the ensuing pressure drop at the bottom of the container. Therefore, it’s crucial to analyze the potential effect of cavitation on AI. The goal of the current study is to investigate the effects of syringe and AI design parameters such as air gap size, syringe filling volume, fluid viscosity, and drive spring force (syringe acceleration) on the risk and severity of cavitation. Methods A model autoinjector platform is built to record the syringe and cavitation dynamics which we use to estimate the cavitation intensity in terms of extension rate and to study the effects of design parameters on the severity of cavitation. Results Our results show the generation of an intense shock wave and a high extension rate upon cavitation collapse. The induced extension rate increases with syringe acceleration and filling volume and decreases with viscosity and air gap size. Conclusion The most severe cavitation occurred in an AI device with the larger drive spring force and the syringe of a smaller air gap size filled with a less viscous fluid and a larger filling volume.
Purpose 3D printing (3DP) makes it possible to obtain systems that are not achievable with current conventional methods, one of them, sustained release floating systems. Floating systems using ricobendazole (RBZ) as a model drug and a combination of polymers were designed and obtained by melt solidification printing technique (MESO-PP). Methods Four different MESO-PP inks were formulated based on combinations of the polymers Gelucire 43/01 and Gelucire 50/13 in different ratios. For each of the formulated inks, physicochemical characterization was performed by thermal analysis (thermogravimetric analysis [TGA] and differential scanning calorimetry [DSC]), fourier transform infrared spectrophotometer (FTIR) and X-ray diffraction (XRD). Pharmaceutical characterization was performed by in vitro assays to determine pharmaceutically relevant parameters. These parameters were calculated by applying mathematical models developed to evaluate in vitro drug release profiles. On the other hand, a physiologically based pharmacokinetic (PBPK) model was developed to predict the in vivo performance of RBZ loaded in the different inks by determining the Cmax, and the AUC0-∞. Results By increasing the proportion of Gelucire 50/13 co-surfactant in the mixtures (the proportion in Ink 1 was 33%, while the proportion in Ink 4 was 80%), the dissolution capacity of RBZ increases substantially, decreasing flotation times. Conclusion MESO-PP produced ink 1 (50% Gelucire 43/01, 25% Gelucire 50/13 and 25% RBZ), which has a zero-order release (RR = 0.180%/min) and the longest flotation time (545 ± 23 min), and in turn would produce a significant increase in oral absorption of the drug, with an AUC0-∞ 2.16-fold higher than that obtained in animals treated with RBZ loaded in conventional tablets.
For successful oral drug development, defining a bioequivalence (BE) safe space is critical for the identification of newer bioequivalent formulations or for setting of clinically relevant in vitro specifications to ensure drug product quality. By definition, the safe space delineates the dissolution profile boundaries or other drug product quality attributes, within which the drug product variants are anticipated to be bioequivalent. Defining a BE safe space with physiologically based biopharmaceutics model (PBBM) allows the establishment of mechanistic in vitro and in vivo relationships (IVIVR) to better understand absorption mechanism and critical bioavailability attributes (CBA). Detailed case studies on how to use PBBM to establish a BE safe space for both innovator and generic drugs are described. New case studies and literature examples demonstrate BE safe space applications such as how to set in vitro dissolution/particle size distribution (PSD) specifications, widen dissolution specification to supersede f2 tests, or application toward a scale-up and post-approval changes (SUPAC) biowaiver. A workflow for detailed PBBM set-up and common clinical study data requirements to establish the safe space and knowledge space are discussed. Approaches to model in vitro dissolution profiles i.e. the diffusion layer model (DLM), Takano and Johnson models or the fitted PSD and Weibull function are described with a decision tree. The conduct of parameter sensitivity analyses on kinetic dissolution parameters for safe space and virtual bioequivalence (VBE) modeling for innovator and generic drugs are shared. The necessity for biopredictive dissolution method development and challenges with PBBM development and acceptance criteria are described.
Honokiol (HK), a BCS class II drug with a wide range of pharmacological activities, has poor solubility and low oral bioavailability, severely limiting its clinical application. In the current study, incorporating a water-soluble meglumine (MEG) into the crystal lattice of HK molecule was performed to improve its physicochemical properties. The binary mixture of HK and MEG was obtained by anti-solvent method and characterized by TGA, DSC, FTIR, and PXRD. The SCXRD analysis showed that two HK- molecules and two MEG+ molecules were coupled in each unit cell via the ionic interaction along with intermolecular hydrogen bonds, suggesting the formation of a salt, which was further confirmed by the XPS measurements. However, the ∆pKa value between HK and MEG was found to be less than 1, which did not follow the oft-quoted ∆pKa rule for salt formation. After salification with MEG, the solubility and dissolution rate of HK exhibited 3.50 and 25.33 times improvement than crystalline HK, respectively. Simultaneously, the powder flowability, tabletability and stability of HK-MEG salt was also significantly enhanced, and the salt was not more hygroscopic, and that salt formation did not compromise processability in that regard. Further, in vivo pharmacokinetic study showed that Cmax and AUC0-t of HK-MEG salt were enhanced by 2.92-fold and 2.01-fold compared to those of HK, respectively, indicating a considerable improvement in HK oral bioavailability.
Purpose: The pharmaceutical bioequivalence of generic medicines must be confirmed with corresponding original drugs. Although the in vitro dissolution tests are required, results of the mandatory in vitro study do not necessarily reflect the in vivo performance after oral administration. Then, we have tried to develop the novel "Dissolution-Absorption Prediction (DAP) workflow" to evaluate the in vivo performance of generic medicines. Methods: The DAP workflow consists of an "In vitro two-cell connected dissolution (TCCD) system" mimicking the changes in the luminal pH associated with gastrointestinal transit of medicines, "Evaluation of pharmacokinetics of active pharmaceutical ingredient (API)" and "Prediction of plasma concentration-time profile". TCCD system-evaluated dissolution kinetics of APIs from generic formulations and pharmacokinetic parameters based on human data regarding the original drugs were used to calculate the plasma concentration-time profiles of APIs after the oral administration of generic medicines. Results: The mandatory in vitro dissolution tests indicated that the dissolution properties of valsartan (BCS class II) and fexofenadine (BCS class III/IV) in generic formulations did not coincide with those in the corresponding original formulations. The TCCD system provided the very similar dissolution kinetics for the generic and original formulations for the two APIs. Plasma concentration-time profiles evaluated utilizing the dissolution profiles obtained by the TCCD system were in good agreement with the observed profiles for both the generic and original formulations for each API. Conclusions: The DAP workflow would be valuable for estimating the in vivo performance of generic formulation and deducing their bioequivalence with the original formulation.
A higher biopotency of 26053.93 IU/mg was obtained from the urine of pregnant women using different purification methods. The bioassay of hCG activity was tested on rats based on rat seminal vesicles weight gain. Pregnant women urine was extracted and purified with ion exchange chromatography and were purified from 50 IU to 1500 IU with protein content from 243 mg to 8.12 mg. As a consequence of these results, 4.23 mg of protein content was obtained with a biological activity of 3000 IU/mg. To attain increased purity of HCG, the product was subjected and allowed to pass through the affinity column chromatography. This led to the formation of the highly purified HCG with >26000 IU/mg of biological activity.
Plasma concentration–time profiles of 5′-MeONB in Wistar rats following 10 mg/kg intravenous (A) and 50 mg/kg oral (B) dosing, and in mice following 100 mg/kg oral dosing (C) expressed in semi-logarithimic scale. Blue circles represent the observed plasma concentration. Solid line = prediction based on naïve polled population pharmacokinetic analysis.
Goodness‑of‑fit plots of the final popPK model. (A) Observations vs. population predictions in rats and mice data; (B) conditional weighted residuals vs. population predictions using the allometric approach; (C) conditional weighted residuals vs. time in mice and rats data using the allometric approach.
Effect of 5’-MeONB (10–100 mg/kg, i.g.) on nocifensive behavior induced by intraplantar injection of formalin in mice. The total time spent licking the hind paw was measured during the neurogenic phase (0–5 min, panel A) and the inflammatory phase (15–30 min, panel B). Each column represents the mean value obtained from 7 animals, and the vertical lines indicate the S.E.M. The asterisks denote the significance levels when compared with the control group (one-way ANOVA followed by Bonferroni test), * p < 0.05; ** p < 0.01 and *** p < 0.001.
Time course effect of 5’-MeONB (100 mg/kg, i.g.) on nocifensive behavior induced by intraplantar injection of formalin in mice. The total time spent licking the hind paw was measured during the neurogenic phase (0–5 min, panel A) and the inflammatory phase (15–30 min, panel B). Each point represents the mean value obtained from 6–8 animals, and the vertical lines indicate the S.D. The asterisks denote the significance levels when compared with the control group (one-way ANOVA followed by Bonferroni test), *** p < 0.001.
Purpose: 5'-methoxynobiletin (5'-MeONB), a polymethoxyflavone isolated from A. conyzoides, has shown anti-inflammatory property. Nevertheless, the antinociceptive activity and pre-clinical pharmacokinetics (PK) characteristics of 5'-MeONB remain unknown. Considering the anti-inflammatory potential of the 5'-MeONB, this study aimed to investigate the pre-clinical PK behavior of 5'-MeONB, as well as its time course antinociceptive activity. Methods: 5'-MeONB plasma concentrations were determined in Wistar rats after intravenous (i.v.) (10 mg/kg) and oral (50 mg/kg) administration, and in Swiss mice after oral administration (100 mg/kg). Plasma samples were deproteinization and 5'-MeONB quantified by a validated UPLC-MS method. Additionally, the antinociceptive activity of 5'-MeONB was evaluated after 15, 30, 60, 180 and 360 min following oral administration on the acute nocifensive behavior of mice induced by formalin. Results: 5'-MeONB rats and mice plasma concentration-time profiles were best one-compartment model. After i.v. administration to rats, a short half-life, a high clearance and moderate volume of distribution at steady state were observed. Similar results were obtained after oral administration. The oral bioavailability ranged from 8 to 11%. Additionally, 5'-MeONB exhibited antinociceptive activity in both formalin phases, especially in the inflammatory phase of the model, inhibiting 68% and 91% of neurogenic and inflammatory responses, respectively, after 30 min of oral administration. Conclusions: The results described here provide novel insights on 5'-MeONB pharmacokinetics and pharmacodynamic effect, serving as support for future studies to confirm this compound as anti-nociceptive and anti-inflammatory effective agent.
Purpose Serotonin (5-HT) is important for gastrointestinal functions, but its role in drug absorption remains to be clarified. Therefore, the pharmacokinetics and oral absorption of cephalexin (CEX) were examined under 5-HT-excessive condition to understand the role of 5-HT. Methods 5-HT-excessive rats were prepared by multiple intraperitoneal dosing of 5-HT and clorgyline, an inhibitor for 5-HT metabolism, and utilized to examine the pharmacokinetics, absorption behavior and the intestinal permeability for CEX. Results Higher levels of 5-HT in brain, plasma and small intestines were recognized in 5-HT-excessive rats, where the oral bioavailability of CEX was significantly enhanced. The intestinal mucosal transport via passive diffusion of CEX was significantly increased, while its transport via PEPT1 was markedly decreased specifically in the jejunal segment, which was supported by the decrease in PEPT1 expression on brush border membrane (BBM) of intestinal epithelial cells. Since no change in antipyrine permeability and significant increase in FITC dextran-4 permeability were observed in 5-HT-excessive rats, the enhanced permeability for CEX would be attributed to the opening of tight junction, which was supported by the significant decrease in transmucosal electrical resistance. In 5-HT-excessive rats, furthermore, total body clearance of CEX tended to be larger and the decrease in PEPT2 expression on BBM in kidneys was suggested to be one of the reasons for it. Conclusions 5-HT-excessive condition enhanced the oral bioavailability of CEX in rats, which would be attributed to the enhanced permeability across the intestinal mucosa via passive diffusion through the paracellular route even though the transport via PEPT1 was decreased.
Top-cited authors
Andrea Hawe
  • Coriolis Pharma
Kristofer J. Thurecht
  • The University of Queensland
Daniel Bobo
  • The University of Queensland
Jiaul Islam
  • Monash University (Australia)
Kye Robinson
  • The Commonwealth Scientific and Industrial Research Organisation