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The objective of this investigation was to study the effect of induced vibrations on adhesive mixtures containing budesonide and salbutamol sulphate as active pharmaceutical ingredients (APIs) and Inhalacr 70 as carriers. A series of adhesive mixtures with varied fine concentrations (1–4%) was prepared for each API. Half of the adhesive mixture was stressed on a vibrating sieve under conditions resembling hopper flow. Based on scanning electron micrographs, it was concluded that Inhalacr 70 contains particles of two distinct shapes, one irregular with groves and valleys and the other more regular with well-defined edges. The dispersibility of the control and stressed mixtures was studied using a next generation impactor. The stressed mixtures containing 1 and 1.5% API displayed a significant reduction in fine particle dose (FPD) compared to the control. The reduction in FPD resulted from a loss of fines from the adhesive mixture during vibration and as a consequence of restructuring and self-agglomeration resulting in reduced dispersibility. However, no significant difference was observed for mixtures with larger weight fractions of fines (2 and 4% API) but these have a drawback of reduced fine particle fraction (FPF). It is concluded that vibrations induced on the adhesive mixtures during handling potentially have a significant effect on the dispersibility of the API and the total amount of drug delivered to the lungs. De två första författarna delar förstaförfattarskapet

Background: Sub-Saharan Africa (SSA) population is genetically diverse and heterogenous thus variability in drug response among individuals is predicted to be high. Cytochrome P450 (CYP450) polymorphisms is a major source of variability in drug response. This systematic review presents the influence of CYP450 single nucleotide polymorphisms (SNPs), particularly CYP3A4*1B, CYP2B6*6 and CYP3A5*3 on antimalarial drug plasma concentrations, efficacy and safety in SSA populations. Methods: Searching for relevant studies was done through Google Scholar, Cochrane Central Register of controlled trials (CENTRAL), PubMed, Medline, LILACS, and EMBASE online data bases. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were used. Two independent reviewers extracted data from the studies. Results: Thirteen studies reporting the influence of CYP450 SNPs on plasma concentrations, efficacy and safety were included in the final data synthesis. CYP3A4*1B, CYP3A5*5, CYP2B6*6 and CYP2C8*2 did not affect antimalarial drug plasma concentration significantly. There was no difference in treatment outcomes between malaria patients with variant alleles and those with wild type alleles. Conclusion: This review reports lack of influence of CYP3A4*1B, CYP3A5*3, CYP2C8*3 and CYP2B6*6 SNPs on PK profiles, efficacy and safety in SSA among P. falciparum malaria patients.

The tumor size ratio (TSR), time-to-tumor growth (TTG), and tumor growth rate (kG) are frequently suggested as model-based predictors of overall survival (OS) for different types of tumors. When the tumor metrics are applied in forecasting of the outcome for individual patients at an early stage, the tumor data might be sparse resulting in imprecise prediction. This simulation study aimed to investigate how the tumor follow-up data and estimation approaches influence the accuracy in the tumor size metrics and the predicted hazard of death for individual patients. Longitudinal tumor size and OS data were simulated using tumor growth inhibition and Weibull distribution models, respectively. Based on the model and increasing measurement durations, the accuracy (defined as 80–125% of the simulated “true” value) in individual metrics and hazard was computed. TSR week 6 (TSRw6) accuracy was adequate for 91% of the patients when tumor size was measured up to 12 weeks. For TTG and kG metrics, the highest accuracy observed was lower (43 and 77%, respectively) and occurred later (42 and 60 weeks, respectively). The simultaneous (joint) and sequential estimation approaches resulted in similar accuracies, however, in general, the sequential approach where individual tumor size parameters are fixed, demonstrated inferior estimation properties. The TSRw6 and the model-predicted tumor time course (absolute or relative change) had better forecasting properties than TTG or kG. The population pharmacokinetic (PK) parameters and data approach performed similarly or better than the simultaneous approach and had a better accuracy in estimating individuals' hazard of death than the individual PK parameters method. Title in thesis list of papers of Sreenath Madathil Krishnan: Bayesian forecasting of tumor size metrics and survival

Objectives: New drugs and methods to efficiently fight carbapenem-resistant gram-negative pathogens are sorely needed. In this study, we characterized the preclinical pharmacokinetics (PK) and pharmacodynamics of the clinical stage drug candidate apramycin in time kill and mouse lung infection models. Based on in vitro and in vivo data, we developed a mathematical model to predict human efficacy. Methods: Three pneumonia-inducing gram-negative species Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae were studied. Bactericidal kinetics were evaluated with time-kill curves; in vivo PK were studied in healthy and infected mice, with sampling in plasma and epithelial lining fluid after subcutaneous administration; in vivo efficacy was measured in a neutropenic mouse pneumonia model. A pharmacokinetic-pharmacodynamic model, integrating all the data, was developed and simulations were performed. Results: Good lung penetration of apramycin in epithelial lining fluid (ELF) was shown (area under the curve (AUC)(ELF)/ALI(Cplasma) = 88%). Plasma clearance was 48% lower in lung infected mice compared to healthy mice. For two out of five strains studied, a delay in growth (similar to 5 h) was observed in vivo but not in vitro. The mathematical model enabled integration of lung PK to drive mouse PK and pharmacodynamics. Simulations predicted that 30 mg/kg of apramycin once daily would result in bacteriostasis in patients. Discussion: Apramycin is a candidate for treatment of carbapenem-resistant gram-negative pneumonia as demonstrated in an integrated modeling framework for three bacterial species. We show that mathematical modelling is a useful tool for simultaneous inclusion of multiple data sources, notably plasma and lung in vivo PK and simulation of expected scenarios in a clinical setting, notably lung infections.

Proteins, and in particular whey proteins, have recently been introduced as a promising excipient class for stabilizing amorphous solid dispersions. However, despite the efficacy of the approach, the molecular mechanisms behind the stabilization of the drug in the amorphous form are not yet understood. To investigate these, we used experimental and computational techniques to study the impact of drug loading on the stability of protein-stabilized amorphous formulations. β-Lactoglobulin, a major component of whey, was chosen as a model protein and indomethacin as a model drug. Samples, prepared by either ball milling or spray drying, formed single-phase amorphous solid dispersions with one glass transition temperature at drug loadings lower than 40-50%; however, a second glass transition temperature appeared at drug loadings higher than 40-50%. Using molecular dynamics simulations, we found that a drug-rich phase occurred at a loading of 40-50% and higher, in agreement with the experimental data. The simulations revealed that the mechanisms of the indomethacin stabilization by β-lactoglobulin were a combination of (a) reduced mobility of the drug molecules in the first drug shell and (b) hydrogen-bond networks. These networks, formed mostly by glutamic and aspartic acids, are situated at the β-lactoglobulin surface, and dependent on the drug loading (>40%), propagated into the second and subsequent drug layers. The simulations indicate that the reduced mobility dominates at low (

Purpose Orally administered paclitaxel offers increased patient convenience while providing a method to prolong exposure without long continuous, or repeated, intravenous infusions. The oral bioavailability of paclitaxel is improved through co-administration with ritonavir and application of a suitable pharmaceutical formulation, which addresses the dissolution-limited absorption of paclitaxel. We aimed to characterize the pharmacokinetics of different paclitaxel formulations, co-administered with ritonavir, and to investigate a pharmacodynamic relationship between low-dose metronomic (LDM) treatment with oral paclitaxel and the anti-angiogenic marker thrombospondin-1 (TSP-1). Methods Fifty-eight patients treated with different oral paclitaxel formulations were included for pharmacokinetic analysis. Pharmacodynamic data was available for 36 patients. All population pharmacokinetic/pharmacodynamic modelling was performed using non-linear mixed-effects modelling. Results A pharmacokinetic model consisting of gut, liver, central, and peripheral compartments was developed for paclitaxel. The gastrointestinal absorption rate was modelled with a Weibull function. Relative gut bioavailabilities of the tablet and capsule formulations, as fractions of the gut bioavailability of the drinking solution, were estimated to be 0.97 (95%CI: 0.67–1.33) and 0.46 (95%CI: 0.34–0.61), respectively. The pharmacokinetic/pharmacodynamic relationship between paclitaxel and TSP-1 was modelled using a turnover model with paclitaxel plasma concentrations driving an increase in TSP-1 formation rate following an Emax relationship with an EC50 of 284 ng/mL (95%CI: 122–724). Conclusion The developed pharmacokinetic model adequately described the paclitaxel plasma concentrations for the different oral formulations co-administered with ritonavir. This model, and the established pharmacokinetic/pharmacodynamic relationship with TSP-1, may facilitate future development of oral paclitaxel.

Background: A critical step in tuberculosis (TB) drug development is the Phase 2a early bactericidal activity (EBA) study which informs if a new drug or treatment has short-term activity in humans. The aim of this work was to present a standardized pharmacometric model-based early bactericidal activity analysis workflow and determine sample sizes needed to detect early bactericidal activity or a difference between treatment arms.Methods: Seven different steps were identified and developed for a standardized pharmacometric model-based early bactericidal activity analysis approach. Non-linear mixed effects modeling was applied and different scenarios were explored for the sample size calculations. The sample sizes needed to detect early bactericidal activity given different TTP slopes and associated variability was assessed. In addition, the sample sizes needed to detect effect differences between two treatments given the impact of different TTP slopes, variability in TTP slope and effect differences were evaluated.Results: The presented early bactericidal activity analysis approach incorporates estimate of early bactericidal activity with uncertainty through the model-based estimate of TTP slope, variability in TTP slope, impact of covariates and pharmacokinetics on drug efficacy. Further it allows for treatment comparison or dose optimization in Phase 2a. To detect early bactericidal activity with 80% power and at a 5% significance level, 13 and 8 participants/arm were required for a treatment with a TTP-EBA0-14 as low as 11 h when accounting for variability in pharmacokinetics and when variability in TTP slope was 104% [coefficient of variation (CV)] and 22%, respectively. Higher sample sizes are required for smaller early bactericidal activity and when pharmacokinetics is not accounted for. Based on sample size determinations to detect a difference between two groups, TTP slope, variability in TTP slope and effect difference between two treatment arms needs to be considered.Conclusion: In conclusion, a robust standardized pharmacometric model-based EBA analysis approach was established in close collaboration between microbiologists, clinicians and pharmacometricians. The work illustrates the importance of accounting for covariates and drug exposure in EBA analysis in order to increase the power of detecting early bactericidal activity for a single treatment arm as well as differences in EBA between treatments arms in Phase 2a trials of TB drug development.

Cancer cell migration is a driving mechanism of invasion in solid malignant tumors. Anti-migratory treatments provide an alternative approach for managing disease progression. However, we currently lack scalable screening methods for identifying novel anti-migratory drugs. To this end, we develop a method that can estimate cell motility from single end-point images in vitro by estimating differences in the spatial distribution of cells and inferring proliferation and diffusion parameters using agent-based modeling and approximate Bayesian computation. To test the power of our method, we use it to investigate drug responses in a collection of 41 patient-derived glioblastoma cell cultures, identifying migration-associated pathways and drugs with potent anti-migratory effects. We validate our method and result in both in silico and in vitro using time-lapse imaging. Our proposed method applies to standard drug screen experiments, with no change needed, and emerges as a scalable approach to screen for anti-migratory drugs. The spatial positioning of cultured glioblastoma cells is used to estimate cell motility and drug effects from single end-point images in vitro.

Purpose Variability in cytochrome P450 3A4 (CYP3A4) metabolism is mainly caused by non-genetic factors, hence providing a need for accurate phenotype biomarkers. Although 4β-hydroxycholesterol (4βOHC) is a promising endogenous CYP3A4 biomarker, additional investigations are required to evaluate its ability to predict CYP3A4 activity. This study investigated the correlations between 4βOHC concentrations and hepatic and intestinal CYP3A4 protein expression and ex vivo microsomal activity in paired liver and jejunum samples, as well as in vivo CYP3A4 phenotyping (midazolam) in patients with a wide body weight range. Methods The patients (n = 96; 78 with obesity and 18 normal or overweight individuals) were included from the COCKTAIL-study (NCT02386917). Plasma samples for analysis of 4βOHC and midazolam concentrations, and liver (n = 56) and jejunal (n = 38) biopsies were obtained. The biopsies for determination of CYP3A4 protein concentration and microsomal activity were obtained during gastric bypass or cholecystectomy. In vivo CYP3A4 phenotyping was performed using semi-simultaneous oral (1.5 mg) and intravenous (1.0 mg) midazolam. Results 4βOHC concentrations were positively correlated with hepatic microsomal CYP3A4 activity (ρ = 0.53, p ρ = 0.30, p = 0.027), but not with intestinal CYP3A4 concentrations (ρ = 0.18, p = 0.28) or intestinal microsomal CYP3A4 activity (ρ = 0.15, p = 0.53). 4βOHC concentrations correlated weakly with midazolam absolute bioavailability (ρ = − 0.23, p = 0.027) and apparent oral clearance (ρ = 0.28, p = 0.008), but not with systemic clearance (ρ = − 0.03, p = 0.81). Conclusion These findings suggest that 4βOHC concentrations reflect hepatic, but not intestinal, CYP3A4 activity. Further studies should investigate the potential value of 4βOHC as an endogenous biomarker for individual dose requirements of intravenously administered CYP3A4 substrate drugs. Trial registration Clinical.Trials.gov identifier: NCT02386917.

Purpose More than 15 years have passed since the first description of the unbound brain-to-plasma partition coefficient (Kp,uu,brain) by Prof. Margareta Hammarlund-Udenaes, which was enabled by advancements in experimental methodologies including cerebral microdialysis. Since then, growing knowledge and data continue to support the notion that the unbound (free) concentration of a drug at the site of action, such as the brain, is the driving force for pharmacological responses. Towards this end, Kp,uu,brain is the key parameter to obtain unbound brain concentrations from unbound plasma concentrations. Methods To understand the importance and impact of the Kp,uu,brain concept in contemporary drug discovery and development, a survey has been conducted amongst major pharmaceutical companies based in Europe and the USA. Here, we present the results from this survey which consisted of 47 questions addressing: 1) Background information of the companies, 2) Implementation, 3) Application areas, 4) Methodology, 5) Impact and 6) Future perspectives. Results and conclusions From the responses, it is clear that the majority of the companies (93%) has established a common understanding across disciplines of the concept and utility of Kp,uu,brain as compared to other parameters related to brain exposure. Adoption of the Kp,uu,brain concept has been mainly driven by individual scientists advocating its application in the various companies rather than by a top-down approach. Remarkably, 79% of all responders describe the portfolio impact of Kp,uu,brain implementation in their companies as ‘game-changing’. Although most companies (74%) consider the current toolbox for Kp,uu,brain assessment and its validation satisfactory for drug discovery and early development, areas of improvement and future research to better understand human brain pharmacokinetics/pharmacodynamics translation have been identified.

Artificial intelligence (AI) is becoming an integral part of drug discovery. It has the potential to deliver across the drug discovery and development value chain, starting from target identification and reaching through clinical development. In this review, we provide an overview of current AI technologies and a glimpse of how AI is reimagining preclinical drug discovery by highlighting examples where AI has made a real impact. Considering the excitement and hyperbole surrounding AI in drug discovery, we aim to present a realistic view by discussing both opportunities and challenges in adopting AI in drug discovery.

Contains fulltext : 292507.pdf (Publisher’s version ) (Open Access) A milestone in the development of novel antituberculosis drugs is the demonstration of early bactericidal activity (EBA) in a phase IIa clinical trial. The significant variability in measurements of bacterial load complicates data analysis in these trials. A systematic review and evaluation of methods for determination of EBA in pulmonary tuberculosis studies was undertaken. Bacterial load quantification biomarkers, reporting intervals, calculation methods, statistical testing, and handling of negative culture results were extracted. In total, 79 studies were identified in which EBA was determined. Colony-forming units on solid culture media and/or time-to-positivity in liquid media were the biomarkers used most often, reported in 72 (91%) and 34 (43%) studies, respectively. Twenty-two different reporting intervals were presented, and 12 different calculation methods for EBA were identified. Statistical testing for a significant EBA compared with no change was performed in 54 (68%) studies, and between-group testing was performed in 32 (41%) studies. Negative culture result handling was discussed in 34 (43%) studies. Notable variation was found in the analysis methods and reporting of EBA studies. A standardized and clearly reported analysis method, accounting for different levels of variability in the data, could aid the generalization of study results and facilitate comparison between drugs/regimens.

Contains fulltext : 293463.pdf (Publisher’s version ) (Open Access) BACKGROUND: Linezolid is an effective, but toxic anti-tuberculosis drug that is currently recommended for the treatment of drug-resistant tuberculosis. Improved oxazolidinones should have a better safety profile, while preserving efficacy. Delpazolid is a novel oxazolidinone developed by LegoChem Biosciences Inc. that has been evaluated up to phase 2a clinical trials. Since oxazolidinone toxicity can occur late in treatment, LegoChem Biosciences Inc. and the PanACEA Consortium designed DECODE to be an innovative dose-ranging study with long-term follow-up for determining the exposure-response and exposure-toxicity relationship of delpazolid to support dose selection for later studies. Delpazolid is administered in combination with bedaquiline, delamanid and moxifloxacin. METHODS: Seventy-five participants with drug-sensitive, pulmonary tuberculosis will receive bedaquiline, delamanid and moxifloxacin, and will be randomized to delpazolid dosages of 0 mg, 400 mg, 800 mg, 1200 mg once daily, or 800 mg twice daily, for 16 weeks. The primary efficacy endpoint will be the rate of decline of bacterial load on treatment, measured by MGIT liquid culture time to detection from weekly sputum cultures. The primary safety endpoint will be the proportion of oxazolidinone class toxicities; neuropathy, myelosuppression, or tyramine pressor response. Participants who convert to negative liquid media culture by week 8 will stop treatment after the end of their 16-week course and will be observed for relapse until week 52. Participants who do not convert to negative culture will receive continuation phase treatment with rifampicin and isoniazid to complete a six-month treatment course. DISCUSSION: DECODE is an innovative dose-finding trial, designed to support exposure-response modelling for safe and effective dose selection. The trial design allows assessment of occurrence of late toxicities as observed with linezolid, which is necessary in clinical evaluation of novel oxazolidinones. The primary efficacy endpoint is the change in bacterial load, an endpoint conventionally used in shorter dose-finding trials. Long-term follow-up after shortened treatment is possible through a safety rule excluding slow-and non-responders from potentially poorly performing dosages. TRIAL REGISTRATION: DECODE was registered in ClinicalTrials.gov before recruitment start on 22 October 2021 (NCT04550832).

Funding: This clinical trial was conducted within PanACEA, which was part of the European and Developing Countries Clinical Trials Partnership (EDCTP) 1 programme [project code IP. 2007.32011.012 (HIGHRIF)] and the EDCTP2 programme supported by the European Union (grant number TRIA 2015-1102-PanACEA). Biomarkers are quantifiable characteristics of biological processes. In Mycobacterium tuberculosis, common biomarkers used in clinical drug development are colony forming unit (CFU) and time-to-positivity (TTP) from sputum samples. This analysis aimed to develop a combined quantitative tuberculosis biomarker model for CFU and TTP biomarkers for assessing drug efficacy in early bactericidal activity studies. Daily CFU and TTP observations in 83 previously patients with uncomplicated pulmonary tuberculosis after 7 days of different rifampicin monotherapy treatments (10–40 mg/kg) from the HIGHRIF1 study were included in this analysis. The combined quantitative tuberculosis biomarker model employed the Multistate Tuberculosis Pharmacometric model linked to a rifampicin pharmacokinetic model in order to determine drug exposure-response relationships on three bacterial sub-states using both the CFU and TTP data simultaneously. CFU was predicted from the MTP model and TTP was predicted through a time-to-event approach from the TTP model, which was linked to the MTP model through the transfer of all bacterial sub-states in the MTP model to a one bacterial TTP model. The non-linear CFU-TTP relationship over time was well predicted by the final model. The combined quantitative tuberculosis biomarker model provides an efficient approach for assessing drug efficacy informed by both CFU and TTP data in early bactericidal activity studies and to describe the relationship between CFU and TTP over time. Publisher PDF

Contains fulltext : 293273.pdf (Publisher’s version ) (Open Access) BACKGROUND: Higher doses of rifampicin for tuberculosis have been shown to improve early bactericidal activity (EBA) and at the same time increase the intolerability due to high exposure at the beginning of treatment. To support dose optimisation of rifampicin, this study investigated new and innovative staggered dosing of rifampicin using clinical trial simulations to minimise tolerability problems and still achieve good efficacy. METHODS: Rifampicin population pharmacokinetics and time-to-positivity models were applied to data from patients receiving 14 days of daily 10-50 mg/kg rifampicin to characterise the exposure-response relationship. Furthermore, clinical trial simulations of rifampicin exposure were performed following four different staggered dosing scenarios. The simulated exposure after 35 mg/kg was used as a relative comparison for efficacy. Tolerability was derived from a previous model-based analysis relating exposure at day 7 and the probability of having adverse events. RESULTS: The linear relationship between rifampicin exposure and bacterial killing rate in sputum indicated that the maximum rifampicin EBA was not reached at doses up to 50 mg/kg. Clinical trial simulations of a staggered dosing strategy starting the treatment at a lower dose (20 mg/kg) for 7 days followed by a higher dose (40 mg/kg) predicted a lower initial exposure with lower probability of tolerability problems and better EBA compared with a regimen of 35 mg/kg daily. CONCLUSIONS: Staggered dosing of 20 mg/kg for 7 days followed by 40 mg/kg is predicted to reduce tolerability while maintaining exposure levels associated with better efficacy. 01 juni 2023

A dynamic epithelium and a rich microbiota, separated by multi-layered mucus, make up the complex colonic cellular environment. Both cellular systems are characterized by high inter-and intraindividual differences, but their impact on drug distribution and efficacy remains incompletely understood. This research gap is pressing, as, e.g., inflammatory disorders of the colon are on the rise globally. In an effort to help close this gap, we provide considerations on determining colonic epithelial and microbial cellular parameters, and their impact on drug bioavailability. First, we cover the major cell types found in vivo within the epithelium and microbiota, and discuss how they can be modeled in vitro. We then draw attention to their structural similarities and differences with regard to determinants of drug distribution. Once a drug is solubilized in the luminal fluids, there are two main classes of such determinants: 1) binding processes, and 2) transporters and drug-metabolizing enzymes. Binding lowers the unbound intracellular fraction (fu,cell), which will, in turn, limit the amount of drug available for transport to desired sites. Transporters and drug metabolizing enzymes are ADME proteins impacting intracellular accumulation (Kp). Across cell types, we point out which processes are likely particularly impactful. Together, fu,cell and Kp can be used to describe intracellular bioavailability (Fic), which is a measure of local drug distribution, with consequences for efficacy. Determining these cellular parameters will be beneficial in un-derstanding colonic drug distribution and will advance the field of drug delivery.

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.

Introduction The organic cation transporter 3 (OCT3, SLC22A3) is ubiquitously expressed and interacts with a wide array of compounds including endogenous molecules, environmental toxins and prescription drugs. Understudied as a determinant of pharmacokinetics and pharmacodynamics, OCT3 has the potential to be a major determinant of drug absorption and disposition and to be a target for drug-drug interactions (DDIs). Goal The goal of the current study was to identify prescription drug inhibitors of OCT3. Methods We screened a compound library consisting of 2556 prescription drugs, bioactive molecules, and natural products using a high throughput assay in HEK-293 cells stably expressing OCT3. Results We identified 210 compounds that at 20 μM inhibit 50% or more of OCT3-mediated uptake of 4-Di-1-ASP (2 μM). Of these, nine were predicted to inhibit the transporter at clinically relevant unbound plasma concentrations. A Structure-Activity Relationship (SAR) model included molecular descriptors that could discriminate between inhibitors and non-inhibitors of OCT3 and was used to identify additional OCT3 inhibitors. Proteomics of human brain microvessels (BMVs) indicated that OCT3 is the highest expressed OCT in the human blood-brain barrier (BBB). Conclusions This study represents the largest screen to identify prescription drug inhibitors of OCT3. Several are sufficiently potent to inhibit the transporter at therapeutic unbound plasma levels, potentially leading to DDIs or off-target pharmacologic effects.

BACKGROUND AND INTRODUCTION: The dispersible tablet formulation (DTF) of pretomanid has been developed to facilitate future use in children. This work aimed to assess the pharmacokinetics (PK) and relative bioavailability of the DTF compared to the marketed formulation (MF) and the potential influence of dose. METHODS: Pretomanid DTF was investigated in a single-dose, randomized, four-period, cross-over study, with 7 days of washout between doses. Forty-eight healthy volunteers were enrolled and randomized into one of two panels to receive doses either in the fasted state or after a high-fat meal. Each volunteer received doses of 10, 50, and 200 mg DTF, and 200 mg MF pretomanid. Blood samples for pharmacokinetic assessment were drawn following a rich schedule up to 96 h after each single dose. The study data from the panel receiving the high-fat meal were analyzed using a nonlinear mixed-effects modeling approach, and all data were characterized with noncompartmental methods. RESULTS: A one-compartment model with first-order elimination and absorption through a transit compartment captured the mean and variability of the observed pretomanid concentrations with acceptable precision. No significant difference in bioavailability was found between formulations. The mean absorption time for the DTF was typically 137% (86-171%) of that for the MF. The bioavailability was found to be dose dependent with a small positive and larger negative correlation under fed and fasted conditions, respectively. CONCLUSION: Using data from a relative bioavailability study in healthy adult volunteers, a mathematical model has been developed to inform dose selection for the investigation of pretomanid in children using the new dispersible tablet formulation. Under fed conditions and at the currently marketed adult dose of 200 mg, the formulation type was found to influence the absorption rate, but not the bioavailability. The bioavailability of the DTF was slightly positively correlated with doses when administered with food. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04309656, first posted on 16 March 2020.

In this work, we set out to better understand how the permeation enhancer sodium caprate (C10) influences the intestinal absorption of macromolecules. FITC-dextran 4000 (FD4) was selected as a model compound and formulated with 50-300 mM C10. Absorption was studied after bolus instillation of liquid formulation to the duodenum of anesthetized rats and intravenously as a reference, whereafter plasma samples were taken and analyzed for FD4 content. It was found that the AUC and C-max of FD4 increased with increasing C10 concentration. Higher C10 concentrations were associated with an increased and extended absorption but also increased epithelial damage. Depending on the C10 concentration, the intestinal epithelium showed significant recovery already at 60-120 min after administration. At the highest studied C10 concentrations (100 and 300 mM), the absorption of FD4 was not affected by the colloidal structures of C10, with similar absorption obtained when C10 was administered as micelles (pH 8.5) and as vesicles (pH 6.5). In contrast, the FD4 absorption was lower when C10 was administered at 50 mM formulated as micelles as compared to vesicles. Intestinal dilution of C10 and FD4 revealed a trend of decreasing FD4 absorption with increasing intestinal dilution. However, the effect was smaller than that of altering the total administered C10 dose. Absorption was similar when the formulations were prepared in simulated intestinal fluids containing mixed micelles of bile salts and phospholipids and in simple buffer solution. The findings in this study suggest that in order to optimally enhance the absorption of macromolecules, high (>= 100 mM) initial intestinal C10 concentrations are likely needed and that both the concentration and total dose of C10 are important parameters.

Contains fulltext : 248642.pdf (Publisher’s version ) (Open Access) Moxifloxacin has an important role in the treatment of tuberculosis (TB). Unfortunately, coadministration with the cornerstone TB drug rifampicin results in suboptimal plasma exposure. We aimed to gain insight into the moxifloxacin pharmacokinetics and the interaction with rifampicin. Moreover, we provided a mechanistic framework to understand moxifloxacin pharmacokinetics. We developed a physiologically based pharmacokinetic model in Simcyp version 19, with available and newly generated in vitro and in vivo data, to estimate pharmacokinetic parameters of moxifloxacin alone and when administered with rifampicin. By combining these strategies, we illustrate that the role of P-glycoprotein in moxifloxacin transport is limited and implicate MRP2 as transporter of moxifloxacin-glucuronide followed by rapid hydrolysis in the gut. Simulations of multiple dose area under the plasma concentration-time curve (AUC) of moxifloxacin (400 mg once daily) with and without rifampicin (600 mg once daily) were in accordance with clinically observed data (predicted/observed [P/O] ratio of 0.87 and 0.80, respectively). Importantly, increasing the moxifloxacin dose to 600 mg restored the plasma exposure both in actual patients with TB as well as in our simulations. Furthermore, we extrapolated the single dose model to pediatric populations (P/O AUC ratios, 1.04-1.52) and the multiple dose model to children with TB (P/O AUC ratio, 1.51). In conclusion, our combined approach resulted in new insights into moxifloxacin pharmacokinetics and accurate simulations of moxifloxacin exposure with and without rifampicin. Finally, various knowledge gaps were identified, which may be considered as avenues for further physiologically based pharmacokinetic refinement.

Antibody therapies are typically based on high-concentration formulations that need to be administered subcutaneously. These conditions induce several challenges, inter alia a viscosity suitable for injection, sufficient solution stability, and preservation of molecular function. To obtain systematic insights into the molecular factors, we study the dynamics on the molecular level under strongly varying solution conditions. In particular, we use solutions of antibodies with poly(ethylene glycol), in which simple cooling from room temperature to freezing temperatures induces a transition from a well-dispersed solution into a phase-separated and macroscopically arrested system. Using quasi-elastic neutron scattering during in situ cooling ramps and in prethermalized measurements, we observe a strong decrease in antibody diffusion, while internal flexibility persists to a significant degree, thus ensuring the movement necessary for the preservation of molecular function. These results are relevant for a more dynamic understanding of antibodies in high-concentration formulations, which affects the formation of transient clusters governing the solution viscosity.

There has been an increased interest in pharmacokinetics and pharmacodynamics (PKPD) of anti-tuberculosis drugs. A better understanding of the relationship between drug exposure, antimicrobial kill and acquired drug resistance is essential not only to optimize current treatment regimens but also to design appropriately dosed regimens with new anti-tuberculosis drugs. Although the interest in PKPD has resulted in an increased number of studies, the actual bench-to-bedside translation is somewhat limited. One of the reasons could be differences in methodologies and outcome assessments that makes it difficult to compare the studies. In this paper we summarize most relevant in vitro, in vivo, in silico and human PKPD studies performed to optimize the drug dose and regimens for treatment of tuberculosis. The in vitro assessment focuses on MIC determination, static time-kill kinetics, and dynamic hollow fibre infection models to investigate acquisition of resistance and killing of Mycobacterium tuberculosis populations in various metabolic states. The in vivo assessment focuses on the various animal models, routes of infection, PK at the site of infection, PD read-outs, biomarkers and differences in treatment outcome evaluation (relapse and death). For human PKPD we focus on early bactericidal activity studies and inclusion of PK and therapeutic drug monitoring in clinical trials. Modelling and simulation approaches that are used to evaluate and link the different data types will be discussed. We also describe the concept of different studies, study design, importance of uniform reporting including microbiological and clinical outcome assessments, and modelling approaches. We aim to encourage researchers to consider methods of assessing and reporting PKPD of anti-tuberculosis drugs when designing studies. This will improve appropriate comparison between studies and accelerate the progress in the field.

4 Cl-cumyl-PINACA (SGT-157), 4 F-cumyl-5F-PINACA (4F-cumyl-5F-PINACA, SGT-65) and 4 F-cumyl-5F-PICA (4F-cumyl-5F-PICA, SGT-64) are a series of new halogenated cumyl synthetic cannabinoid receptor agonists (SCRAs). Due to rapid metabolism, monitoring and screening for SCRAs in biological matrices requires identification of their metabolites. It is an essential tool for estimating their spread and fluctuations in the global illicit market. The purpose of this study was to identify human biotransformations of 4 Cl-cumyl-PINACA, 4 F-cumyl-5F-PINACA and 4 F-cumyl-5F-PICA in vitro and characterize for the first time the metabolic pathways of halogenated cumyl SCRAs. 4 Cl-cumyl-PINACA, 4 F-cumyl-5F-PINACA and 4 F-cumyl-5F-PICA were incubated with human hepatocytes in duplicates for 0, 1, 3 and 5 h. The supernatants were analysed in data-dependent acquisition on a UHPLC-QToF-MS, and the potential metabolites were tentatively identified. A total of 11 metabolites were detected for 4 Cl-cumyl-PINACA, 21 for 4 F-cumyl-5F-PINACA and 10 for 4 F-cumyl-5F-PICA. The main biotransformations were oxidative defluorination, followed by hydroxylation with dehydrogenation, N-dealkylation, dihydrodiol formation and glucuronidation. Hydroxylations were most common at the tail moieties with higher abundancy for indole than indazole compounds. N-dealkylations were more common for fluorinated tail chain compounds than the non-fluorinated 4 Cl-cumyl-PINACA. In conclusion, many metabolites retained halogen groups at the cumyl moieties which, in various combinations, may be suitable as analytical biomarkers. Funding Agencies|VINNOVA [2019-03566]; Eurostars-2 Joint Programme [E! 113377]; European Union; Swedens Innovation Agency Vinnova; Strategic Research Area in Forensic Sciences [2016:7]

The chiral drug ketamine has long-lasting antidepressant effects with a fast onset and is also suitable to treat patients with therapy-resistant depression. The metabolite hydroxynorketamine (HNK) plays an important role in the antidepressant mechanism of action. Hydroxylation at the cyclohexanone ring occurs at positions 4, 5, and 6 and produces a total of 12 stereoisomers. Among those, the four 6HNK stereoisomers have the strongest antidepressant effects. Capillary electrophoresis with highly sulfated γ-cyclodextrin (CD) as a chiral selector in combination with mass spectrometry (MS) was used to develop a method for the enantioselective analysis of HNK stereoisomers with a special focus on the 6HNK stereoisomers. The partial filling approach was applied in order to avoid contamination of the MS with the chiral selector. Concentration of the chiral selector and the length of the separation zone were optimized. With 5% highly sulfated γ-CD in 20 mM ammonium formate with 10% formic acid and a 75% filling the four 6HNK stereoisomers could be separated with a resolution between 0.79 and 3.17. The method was applied to analyze fractionated equine urine collected after a ketamine infusion and to screen the fractions as well as unfractionated urine for the parent drug ketamine and other metabolites, including norketamine and dehydronorketamine.

Background: People with major neurocognitive disorder might be susceptible to drug-induced QT interval prolongation due to the presence of a number of concomitant risk factors. Objective: The aim of this study was to investigate the prevalence of QT-prolonging drugs and QT-prolonging drug–drug interactions and associated factors among older people with major neurocognitive disorder. Methods: In this register-based study, we obtained information regarding QT-prolonging drug use in a large population of older people with major neurocognitive disorder, through record linkage between the Swedish registry for cognitive/dementia disorders, and the Swedish Prescribed Drug Register. QT-prolonging drugs were identified according to the CredibleMeds online database and interactions using the Janusmed interaction database. Drug use was defined as one or more filled prescriptions during a 6-month timeframe, July 01 to December 31, 2017. Associations between people with a QT-prolonging drug and the factors of age and gender were analysed through multiple logistic regression. Results: Of 35,212 people included in the study, 41.6% had one or more QT-prolonging drug prescribed. The most commonly prescribed drug was donepezil, with a prevalence of 25.0%, followed by citalopram and escitalopram, representing 14.5% and 3.9% of prescriptions in the study population, respectively. Significant associations were found between QT-prolonging drug use and the factors of younger age and female gender. The most prevalent interaction was between citalopram and donepezil (2.7%), followed by the combination of escitalopram and donepezil (0.7%). Conclusions: In this population of older people with major neurocognitive disorder, QT-prolonging drugs and interactions that increase the risk of torsade de pointes were prevalent. Due to the presence of many risk factors in this population, it is important to continuously evaluate current QT-prolonging drugs and concomitant drug treatment in each individual.

The Bis-T series of compounds comprise some of the most potent inhibitors of dynamin GTPase activity yet reported, e. g., (2E,2 ' E)-N,N '-(propane-1,3-diyl)bis(2-cyano-3-(3,4-dihydroxyphenyl)acrylamide) (2), Bis-T-22. The catechol moieties are believed to limit cell permeability, rendering these compounds largely inactive in cells. To solve this problem, a prodrug strategy was envisaged and eight ester analogues were synthesised. The shortest and bulkiest esters (acetate and butyl/tert-butyl) were found to be insoluble under physiological conditions, whilst the remaining five were soluble and stable under these conditions. These five were analysed for plasma stability and half-lives ranged from similar to 2.3 min (propionic ester 4), increasing with size and bulk, to greater than 24 hr (dimethyl carbamate 10). Similar profiles where observed with the rate of formation of Bis-T-22 with half-lives ranging from similar to 25 mins (propionic ester 4). Propionic ester 4 was chosen to undergo further testing and was found to inhibit endocytosis in a dose-dependent manner with IC50 similar to 8 mu M, suggesting this compound is able to effectively cross the cell membrane where it is rapidly hydrolysed to the desired Bis-T-22 parent compound.

Dissolution rate impacts the absorption rate of poorly soluble inhaled drugs. In vitro dissolution tests that can capture the impact of changes in critical quality attributes of the drug product on in vivo dissolution are important for the development of products containing poorly soluble drugs, as well as modified release formulations. In this study, an extended mathematical model allowing for dissolution of polydisperse powders and subsequent diffusion of dissolved drug across a membrane is described. In vitro dissolution profiles of budesonide, fluticasone propionate, and beclomethasone dipropionate delivered from three commercial drug products were determined using a membrane-type Transwell dissolution test, which consists of a donor and an acceptor compartment separated by a membrane. Subsequently, the profiles were analyzed using the developed mechanistic model and a semi-empirical model based on the Weibull distribution. The two mathematical models provided the same rank order of the performance of the three drug products in terms of dissolution rates, but the rates were significantly different. The faster rate extracted from the mechanistic model is expected to reflect the true dissolution rate of the drug; the Weibull model provides an effective and slower rate that represents not only drug dissolution but also diffusion across the Transwell membrane. In conclusion, the developed extended model provides superior understanding of the dissolution mechanisms in membrane-type (Transwell) dissolution tests.

Glycated hemoglobin (HbA1c) is the main biomarker of diabetes drug development. However, because of its delayed turnover, trial duration is rarely shorter than 12 weeks, and being able to predict long-term HbA1c with precision using data from shorter studies would be beneficial. The feasibility of reducing study duration was therefore investigated in this study, assuming a model-based analysis. The aim was to investigate the predictive performance of 24- and 52-week extrapolations using data from up to 4, 6, 8 or 12 weeks, with six previously published pharmacometric models of HbA1c. Predictive performance was assessed through simulation-based dose-response predictions and model averaging (MA) with two hypothetical drugs. Results were consistent across the methods of assessment, with MA supporting the results derived from the model-based framework. The models using mean plasma glucose (MPG) or nonlinear fasting plasma glucose (FPG) effect, driving the HbA1c formation, showed good predictive performance despite a reduced study duration. The models, using the linear effect of FPG to drive the HbA1c formation, were sensitive to the limited amount of data in the shorter studies. The MA with bootstrap demonstrated strongly that a 4-week study duration is insufficient for precise predictions of all models. Our findings suggest that if data are analyzed with a pharmacometric model with MPG or FPG with a nonlinear effect to drive HbA1c formation, a study duration of 8 weeks is sufficient with maintained accuracy and precision of dose-response predictions.

Introduction Pharmacologic approaches for promoting angiogenesis have been utilized to accelerate healing of chronic wounds in diabetic patients with varying degrees of success. We hypothesize that the distribution of proangiogenic drugs in the wound area critically impacts the rate of closure of diabetic wounds. To evaluate this hypothesis, we developed a mathematical model that predicts how spatial distribution of VEGF-A produced by delivery of a modified mRNA (AZD8601) accelerates diabetic wound healing. Methods We modified a previously published model of cutaneous wound healing based on coupled partial differential equations that describe the density of sprouting capillary tips, chemoattractant concentration, and density of blood vessels in a circular wound. Key model parameters identified by a sensitivity analysis were fit to data obtained from an in vivo wound healing study performed in the dorsum of diabetic mice, and a pharmacokinetic model was used to simulate mRNA and VEGF-A distribution following injections with AZD8601. Due to the limited availability of data regarding the spatial distribution of AZD8601 in the wound bed, we performed simulations with perturbations to the location of injections and diffusion coefficient of mRNA to understand the impact of these spatial parameters on wound healing. Results When simulating injections delivered at the wound border, the model predicted that injections delivered on day 0 were more effective in accelerating wound healing than injections delivered at later time points. When the location of the injection was varied throughout the wound space, the model predicted that healing could be accelerated by delivering injections a distance of 1-2 mm inside the wound bed when compared to injections delivered on the same day at the wound border. Perturbations to the diffusivity of mRNA predicted that restricting diffusion of mRNA delayed wound healing by creating an accumulation of VEGF-A at the wound border. Alternatively, a high mRNA diffusivity had no effect on wound healing compared to a simulation with vehicle injection due to the rapid loss of mRNA at the wound border to surrounding tissue. Conclusions These findings highlight the critical need to consider the location of drug delivery and diffusivity of the drug, parameters not typically explored in pre-clinical experiments, when designing and testing drugs for treating diabetic wounds. Funding Agencies|AstraZenecaAstraZeneca; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [HL116449, HL137755, AR069393, EY028868, T32LM012416]; National Science FoundationNational Science Foundation (NSF) [1842490, 1716537]; Allen Discovery Center at Stanford University

Pirepemat (IRL752) is a cortical enhancer being developed for the prevention of falls in patients with Parkinson disease. This first-in-human, randomized, double-blind, placebo-controlled phase 1 study evaluated safety, tolerability, and pharmacokinetics (PK) of pirepemat administered as oral single ascending doses (10, 35, 75, 175, 350 mg) and multiple ascending doses (100 and 250 mg 3 times daily) for 7 days to healthy male volunteers. Twenty and 24 subjects were randomly assigned in the single ascending dose and multiple ascending doses parts of the study, respectively. Pirepemat was generally well tolerated, although an increased frequency of adverse events of mild intensity within nervous system disorders (headache and dizziness) was seen after administration of 350 mg as a single dose and after multiple doses of 100 and 250 mg. PK of pirepemat showed a linear relationship over the dose range studied and exhibited dose proportionality after multiple-dose administration. Accumulation after 7 days of multiple dosing was minor. Absorption was rapid, with a median time to maximum concentration of 2.0 hours on day 1 and day 7 (100 and 250 mg) and a mean terminal half-life between 3.7 and 5.2 hours. Food intake had no (obvious) impact on PK. The results support 3-times-daily dosing and further clinical development. Funding Agencies|Integrative Research Laboratories Sweden AB, Gothenburg, Sweden

Product information (PI) is a vital part of any medicinal product approved for use within the European Union and consists of a summary of products characteristics (SmPC) for healthcare professionals and package leaflet (PL) for patients, together with the product packaging. In this study, based on the English corpus of the EMA product information documents for all centrally approved medicinal products within the EU, a BERT sentence embedding model was used together with clustering and dimensional reduction techniques to identify sentence similarity clusters that could be candidates for standardization. A total of 1258 medicinal products were included in the study. From these, a total of 783 K sentences were extracted from SmPC and PL documents which were aggregated into a total of 284 and 129 semantic similarity clusters, respectively. The spread distribution among clusters shows separation into different cluster types. Examples of clusters with low spread include those with identical word embeddings due to current standardization, such as section headings and standard phrases. Others show minor linguistic variations, while the group with the largest variability contains variable wording but with significant semantic overlap. The sentence clusters identified could serve as candidates for further standardization of the PI. Moving from free text human wording to auto-generated text elements based on multiple-choice input for appropriate parts of the package leaflet and summary of product characteristics, could reduce both time and complexity for applicants as well as regulators, and ultimately provide patients and prescribers with documents that are easier to understand and better adapted for search availabilities.

Polygonatum odoratum is a perennial rhizomatous medicinal plant and different plant parts have been used in the treatment of various ailments. Herein, we have investigated the structural compositions of rhizome, leaf, and stem cell walls. We found 30–44% of polysaccharides in these wall preparations were cyclohexanediaminetetraacetic acid (CDTA) extractable, the proportion of heteromannans (HMs) in the rhizome is nearly three-fold compared to that of the leave and stem. The pectic polysaccharides of the rhizome are also structurally more diverse, with arabinans and type I and type II arabinogalactans being richest as shown by linkage study of the sodium carbonate (Na2CO3) extract. In addition, the 2-linked Araf was rhizome-specific, suggesting the cell walls in the rhizome had adapted to a more complex structure compared to that of the leaf and stem. Water-soluble polysaccharide fractions were also investigated, high proportion of Man as in 4-linked Manp indicated high proportion of HMs. The 21.4 kDa pectic polysaccharides and HMs derived from rhizome cell walls induced specific immune response in mice macrophage cells producing IL-1α and hematopoietic growth factors GM-CSF and G-CSF in vitro. QC 20221012

The development of high-throughput approaches for the valid estimation of brain disposition is of great importance in the early drug screening of drug candidates. However, the complexity of brain tissue, which is protected by a unique vasculature formation called the blood–brain barrier (BBB), complicates the development of robust in silico models. In addition, most computational approaches focus only on brain permeability data without considering the crucial factors of plasma and tissue binding. In the present study, we combined experimental data obtained by HPLC using three biomimetic columns, i.e., immobilized artificial membranes, human serum albumin, and α1-acid glycoprotein, with molecular descriptors to model brain disposition of drugs. Kp,uu,brain, as the ratio between the unbound drug concentration in the brain interstitial fluid to the corresponding plasma concentration, brain permeability, the unbound fraction in the brain, and the brain unbound volume of distribution, was collected from literature. Given the complexity of the investigated biological processes, the extracted models displayed high statistical quality (R2 > 0.6), while in the case of the brain fraction unbound, the models showed excellent performance (R2 > 0.9). All models were thoroughly validated, and their applicability domain was estimated. Our approach highlighted the importance of phospholipid, as well as tissue and protein, binding in balance with BBB permeability in brain disposition and suggests biomimetic chromatography as a rapid and simple technique to construct models with experimental evidence for the early evaluation of CNS drug candidates.

There is a growing interest in the psychiatric properties of the dissociative anaesthetic ketamine, as single doses have been shown to have fast-acting mood-enhancing and anxiolytic effects, which persist for up to a week after the main psychoactive symptoms have diminished. Therefore, ketamine poses potential beneficial effects in patients with refractory anxiety disorders, where other conventional anxiolytics have been ineffective. Ketamine is a noncompetitive antagonist of the N-methyl-d-aspartate (NMDA) glutamate receptor, which underlies its induction of pain relief and anaesthesia. However, the role of NMDA receptors in anxiety reduction is still relatively unknown. To fill this paucity in the literature, this systematic review assesses the evidence that ketamine significantly reduces refractory anxiety and discusses to what extent this may be mediated by NMDA receptor antagonism and other receptors. We highlight the temporary nature of the anxiolytic effects and discuss the high discrepancy among the study designs regarding many fundamental factors such as administration routes, complementary treatments and other treatments.

Purpose Pharmacometric models provide useful tools to aid the rational design of clinical trials. This study evaluates study design-, drug-, and patient-related features as well as analysis methods for their influence on the power to demonstrate a benefit of pharmacogenomics (PGx)-based dosing regarding myelotoxicity. Methods Two pharmacokinetic and one myelosuppression model were assembled to predict concentrations of irinotecan and its metabolite SN-38 given different UGT1A1 genotypes (poor metabolizers: CLSN-38: -36%) and neutropenia following conventional versus PGx-based dosing (350 versus 245 mg/m2 (-30%)). Study power was assessed given diverse scenarios (n = 50–400 patients/arm, parallel/crossover, varying magnitude of CLSN-38, exposure-response relationship, inter-individual variability) and using model-based data analysis versus conventional statistical testing. Results The magnitude of CLSN-38 reduction in poor metabolizers and the myelosuppressive potency of SN-38 markedly influenced the power to show a difference in grade 4 neutropenia (9 cells/L) after PGx-based versus standard dosing. To achieve >80% power with traditional statistical analysis (χ2/McNemar’s test, α = 0.05), 220/100 patients per treatment arm/sequence (parallel/crossover study) were required. The model-based analysis resulted in considerably smaller total sample sizes (n = 100/15 given parallel/crossover design) to obtain the same statistical power. Conclusions The presented findings may help to avoid unfeasible trials and to rationalize the design of pharmacogenetic studies.

Contains fulltext : 235795.pdf (Publisher’s version ) (Open Access) Tuberculosis (TB) is still the number one cause of death due to an infectious disease. Pharmacokinetics and pharmacodynamics of anti-TB drugs are key in the optimization of TB treatment and help to prevent slow response to treatment, acquired drug resistance, and adverse drug effects. The aim of this review was to provide an update on the pharmacokinetics and pharmacodynamics of anti-TB drugs and to show how population pharmacokinetics and Bayesian dose adjustment can be used to optimize treatment. We cover aspects on preclinical, clinical, and population pharmacokinetics of different drugs used for drug-susceptible TB and multidrug-resistant TB. Moreover, we include available data to support therapeutic drug monitoring of these drugs and known pharmacokinetic and pharmacodynamic targets that can be used for optimization of therapy. We have identified a wide range of population pharmacokinetic models for first- and second-line drugs used for TB, which included models built on NONMEM, Pmetrics, ADAPT, MWPharm, Monolix, Phoenix, and NPEM2 software. The first population models were built for isoniazid and rifampicin; however, in recent years, more data have emerged for both new anti-TB drugs, but also for defining targets of older anti-TB drugs. Since the introduction of therapeutic drug monitoring for TB over 3 decades ago, further development of therapeutic drug monitoring in TB next steps will again depend on academic and clinical initiatives. We recommend close collaboration between researchers and the World Health Organization to provide important guideline updates regarding therapeutic drug monitoring and pharmacokinetics/pharmacodynamics.

Coiled coils are characterized by an arrangement of two or more alpha-helices into a superhelix and one of few protein motifs where the sequence-to-structure relationship to a large extent have been decoded and understood. The abundance of both natural and de novo designed coil coils provides a rich molecular toolbox for self assembly of elaborate bespoke molecular architectures, nanostructures, and materials. Leveraging on the numerous possibilities to tune both affinities and preferences for polypeptide oligomerization, coiled coils offer unique possibilities to design modular and dynamic assemblies that can respond in a predictable manner to biomolecular interactions and subtle physicochemical cues. In this review, strategies to use coiled coils in design of novel therapeutics and advanced drug delivery systems are discussed. The applications of coiled coils for generating drug carriers and vaccines, and various aspects of using coiled coils for controlling and triggering drug release, and for improving drug targeting and drug uptake are described. The plethora of innovative coiled coil-based molecular systems provide new knowledge and techniques for improving efficacy of existing drugs and can facilitate development of novel therapeutic strategies. (c) 2020 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/). 1. Introduction 27 2. The coiled coil motif 27 3. Coiled coils and coiled coil-hybrids for drug delivery and therapeutics 30 3.1. Coiled coils in liposome drug delivery systems 30 3.2. Lipidated coiled coils for assembly of virus-like particles 31 3.3. Coiled coil nanoparticles 31 3.4. Coiled coil nanocarriers 33 3.5. Coiled coil polymer-hybrids 33 3.6. Coiled coil-based hydrogels 36 3.7. Coiled coil inorganic nanoparticle hybrids 37 3.8. Coiled coils combined with cell penetrating peptides 37 3.9. Coiled coils for improved targeting 38 Funding Agencies|Swedish Foundation for Strategic Research (SFF)Swedish Foundation for Strategic Research [FFL15-0026, RMX18-0039]; Swedish Government Strategic Research Area inMaterials Science on Functional Materials at Linkoping University [2009-00971]; Knut and Alice Wallenberg FoundationKnut & Alice Wallenberg Foundation [KAW 2016.0231]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2017-04475]; Cancer Foundation [17 0534]

In the present work, the determination of omeprazole (OME) enantiomers in oral fluid and plasma samples was carried out utilizing microextraction by packed sorbent (MEPS) and liquid chromatography-tandem mass spectrometry. A chiral column with cellulose-SB phase was used for the first time for enantiomeric separation of OME with an isocratic elution system using 0.2% ammonium hydroxide in hexane-ethanol mixture (70 : 30, v/v) as the mobile phase. OME enantiomers were determined utilizing a triple quadrupole tandem mass spectrometer in positive ion mode (ESI+) monitoring mass transitions: m/z 346.3 ⟶ 198.0 for OME and m/z 369.98 ⟶ 252.0 for internal standard. The limits of detection and quantification of the present method for both enantiomers were 0.1 and 0.4 ng/mL, respectively. The method validation provided good accuracy and precision. The matrix effect factor was less than 5%, and no interfering peaks were observed. The interday precision values ranged from 2.2 to 7.5 (%RSD), and the accuracy of determinations varied from −9.9% to 8.3%. In addition, the pharmacokinetics (PK) of omeprazole enantiomers in healthy subjects after a single oral dose was investigated. (S)-Enantiomers showed higher levels than (R)-enantiomers throughout 24 h. It was found that the mean maximum concentrations of (R)- and (S)-omeprazole in plasma samples were about two times higher than in oral fluid.

Contains fulltext : 235727.pdf (Publisher’s version ) (Open Access) AIMS: Simulations are an essential tool for investigating scenarios in pharmacokinetics-pharmacodynamics. The models used during simulation often include the effect of highly correlated covariates such as weight, height and sex, and for children also age, which complicates the construction of an in silico population. For this reason, a suitable and representative patient population is crucial for the simulations to produce meaningful results. For simulation in paediatric patients, international growth charts from the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC) provide a reference, but these may not always be representative for specific populations, such as malnourished children with HIV or acutely unwell children. METHODS: We present a workflow to construct a virtual paediatric patient population using WHO and CDC growth charts, suggest piecewise linear functions to adjust the median of the growth charts by sex and age, and suggest visual diagnostics to compare with the target population. We applied this workflow in a population of 1206 HIV-positive African children, consisting of 19 742 observations with weight ranging from 3.8 to 79.7 kg, height from 55.5 to 180 cm, and an age between 0.40 and 18 years. RESULTS: Before adjustment, the WHO and CDC charts produced weights and heights higher compared to the observed data. After applying our methodology, we could simulate weight, height, sex and age combinations in good agreement with the observed data. CONCLUSION: The methodology presented here is flexible and may be applied to other scenarios where WHO and CDC growth standards might not be appropriate. In addition we provide R scripts and a large ready-to-use paediatric population.

The Breast Cancer Resistance Protein (BCRP) is a key transporter in drug efflux and drug-drug interactions. However, endogenous expression of Multidrug Resistance Protein 1 (MDR1) confounds the interpretation of BCRP-mediated transport in in vitro models. Here we used a CRISPR-Cas9 edited Madin-Darby canine kidney (MDCK) II cell line (MDCKcMDR1-KO) for stable expression of human BCRP (hBCRP) with no endogenous canine MDR1 (cMDR1) expression (MDCK-hBCRPcMDR1-KO). Targeted quantitative proteomics verified expression of hBCRP, and global analysis of the entire proteome corroborated no or very low background expression of other drug transport proteins or metabolizing enzymes. This new cell line, had similar proteome like MDCKcMDR1-KO and a previously established, corresponding cell line overexpressing human MDR1 (hMDR1), MDCK-hMDR1cMDR1-KO. Functional studies with MDCK-hBCRPcMDR1-KO confirmed high hBCRP activity. The MDCK-hBCRPcMDR1-KO cell line together with the MDCK-hMDR1cMDR1-KO easily and accurately identified shared or specific substrates of the hBCRP and the hMDR1 transporters. These cell lines offer new, improved in vitro tools for the assessment of drug efflux and drug-drug interactions in drug development.

Pulmonary delivery has gained increased interests over the past few decades. For conditions within the respiratory tract, targeted drug delivery directly to the site of action can achieve a high local concentration for efficacy with reduced unwanted systemic exposure and adverse effect. For systemic conditions, the unique physiology of the lung evolutionarily designed for rapid gaseous exchange presents an entry route for systemic drug delivery. Although the development of inhaled formulations has come a long way over the last few decades, many aspects of it remain to be elucidated. In particular, a reliable and well-understood method for in vitro-in vivo correlations remains to be established. With the rapid and ongoing advancement of technology, there is much potential to better utilise computational methods including different types of modelling and simulation approaches to support inhaled formulation development. This review intends to provide an introduction on some fundamental concepts in pulmonary drug delivery and inhaled formulation development followed by discussions on some challenges and opportunities in the translation of inhaled pharmaceuticals from preclinical studies to clinical development. The review concludes with some recent advancements in modelling and simulation approaches that could play an increasingly important role in contemporary formulation development of inhaled pharmaceuticals.

Inflammatory bowel disease (IBD) is a chronic condition resulting in impaired intestinal homeostasis. Current practices for diagnosis of IBD are challenged by invasive, demanding procedures. We hypothesized that proteomics analysis could provide a powerful tool for identifying clinical biomarkers for non-invasive IBD diagnosis. Here, the global intestinal proteomes from commonly used in vitro and in vivo models of IBD were analyzed to identify apical and luminal proteins that can be targeted by orally delivered diagnostic agents. Global proteomics analysis revealed upregulated plasma membrane proteins in intestinal segments of proximal- and distal colon from dextran sulfate sodium-treated mice and also in inflamed human intestinal Caco-2 cells pretreated with pro-inflammatory agents. The upregulated colon proteins in mice were compared to the proteome of the healthy ileum, to ensure targeting of diagnostic agents to the inflamed colon. Promising target proteins for future investigations of non-invasive diagnosis of IBD were found in both systems and included Tgm2/TGM2, Icam1/ICAM1, Ceacam1/CEACAM1, and Anxa1/ANXA1. Ultimately, these findings will guide the selection of appropriate antibodies for surface functionalization of imaging agents aimed to target inflammatory biomarkers in situ. De två första författarna delar förstaförfattarskapet

Large batches of placebo and drug-loaded solid dosage forms were successfully fabricated using selective laser sintering (SLS) 3D printing in this study. The tablet batches were prepared using either copovidone (N-vinyl-2-pyrrolidone and vinyl acetate, PVP/VA) or polyvinyl alcohol (PVA) and activated carbon (AC) as radiation absorbent, which was added to improve the sintering of the polymer. The physical properties of the dosage forms were evaluated at different pigment concentrations (i.e., 0.5 and 1.0 wt%) and at different laser energy inputs. The mass, hardness, and friability of the tablets were found to be tunable and structures with greater mass and mechanical strength were obtained with increasing carbon concentration and energy input. Amorphization of the active pharmaceutical ingredient in the drug-loaded batches, containing 10 wt% naproxen and 1 wt% AC, was achieved in-situ during printing. Thus, amorphous solid dispersions were prepared in a single-step process and produced tablets with mass losses below 1 wt%. These findings show how the properties of dosage forms can be tuned by careful selection of the process parameters and the powder formulation. SLS 3D printing can therefore be considered to be an interesting and promising technique for the fabrication of personalized medicines.

Rheumatoid arthritis (RA) is a long-term autoimmune disease. As nanotechnology has advanced, a growing number of nanodrugs have been used in the treatment of RA due to their unique physical and chemical properties. The purpose of this study was to assess the therapeutic potential of a novel zeolite/vitamin B12 nanocomposite (Nano ZT/Vit B12) formulation in complete Freunds adjuvant (CFA)-induced arthritis. The newly synthesized Nano ZT/Vit B12 was fully characterized using various techniques such as XRD, FT-IR, BET analysis, HERTEM, SEM, practical size, zeta potential, XRF, and EDX. The anti-arthritic, anti-inflammatory, and antioxidant activities as well as the immunomodulation effect of Nano ZT/Vit B12 on the CFA rat model of arthritis were examined. Histopathologic ankle joint injuries caused by CFA intrapedal injection included synovium hyperplasia, inflammatory cell infiltration, and extensive cartilage deterioration. The arthritic rats Nano ZT/Vit B12 supplementation significantly improved these effects. Furthermore, in arthritic rats, Nano ZT/Vit B12 significantly reduced serum levels of RF and CRP, as well as the levels of IL-1 beta, TNF-alpha, IL-17, and ADAMTS-5, while increasing IL-4 and TIMP-3 levels. Nano-ZT/Vit B12 significantly declined the LPO level and increased antioxidant activities, such as GSH content and GST activity, in the arthritic rats. In arthritic rats, Nano ZT/Vit B12 also reduced TGF-beta mRNA gene expression and MMP-13 protein levels. Collectively, Nano ZT/Vit B12 seems to have anti-arthritic, anti-inflammatory, and antioxidant properties, making it a promising option for RA in the future. Funding Agencies|King Salman Center for Disability Research [KSRG-2022-047]

A new modelling approach for dissolution of polydisperse powders is developed within the framework of the classical Noyes-Whitney/Nernst-Brunner analysis. Its distinguishing feature is that the underlying continuous particle-size distribution is retained. Two different but related dependencies of the diffusion-layer thickness on particle size are considered. First, a power-law dependence that interpolates between a thickness that is proportional to (or equals) the particle radius (obtained when the exponent equals 1) and a constant thickness (obtained when the exponent is 0). Second, a piecewise linear function such that the thickness equals the particle radius for sufficiently small particles and is constant for larger ones. The modelling approach is exemplified by consideration of a lognormal particle-size distribution. Highly accurate closed-form expressions for the fraction of dissolved drug are obtained for dissolution under sink conditions (which are exact if the diffusion-layer thickness is radius-independent). Moreover, it is demonstrated that any result derived under sink conditions can be reused to determine the fraction of dissolved/absorbed drug under non-sink conditions, using the concept of a retarded time. Comparison with literature data and experiments are used to validate the modelling approach and to demonstrate its usefulness in a practical context.

Analyses of longitudinal data with non-linear mixed-effects models (NLMEM) are typically associated with high power, but sometimes at the cost of inflated type I error. Approaches to overcome this problem were published recently, such as model-averaging across drug models (MAD), individual model-averaging (IMA), and combined Likelihood Ratio Test (cLRT). This work aimed to assess seven NLMEM approaches in the same framework: treatment effect assessment in balanced two-armed designs using real natural history data with or without the addition of simulated treatment effect. The approaches are MAD, IMA, cLRT, standard model selection (STDs), structural similarity selection (SSs), randomized cLRT (rcLRT), and model-averaging across placebo and drug models (MAPD). The assessment included type I error, using Alzheimer’s Disease Assessment Scale-cognitive (ADAS-cog) scores from 817 untreated patients and power and accuracy in the treatment effect estimates after the addition of simulated treatment effects. The model selection and averaging among a set of pre-selected candidate models were driven by the Akaike information criteria (AIC). The type I error rate was controlled only for IMA and rcLRT; the inflation observed otherwise was explained by the placebo model misspecification and selection bias. Both IMA and rcLRT had reasonable power and accuracy except under a low typical treatment effect.

Nanoparticles are heterologous small composites that are usually between 1 and 100 nanometers in size. They are applied in many areas of medicine with one of them being drug delivery. Nanoparticles have a number of advantages as drug carriers which include reduced toxic effects, increased bioavailability, and their ability to be modified for specific tissues or cells. Due to the exciting development of nanotechnology concomitant with advances in biotechnology and medicine, the number of clinical trials devoted to nanoparticles for drug delivery is growing rapidly. Some nanoparticles, lipid-based types, in particular, played a crucial role in the developing and manufacturing of the two COVID-19 vaccines—Pfizer and Moderna—that are now being widely used. In this analysis, we provide a quantitative survey of clinical trials using nanoparticles during the period from 2002 to 2021 as well as the recent FDA-approved drugs (since 2016). A total of 486 clinical trials were identified using the clinicaltrials.gov database. The prevailing types of nanoparticles were liposomes (44%) and protein-based formulations (26%) during this period. The most commonly investigated content of the nanoparticles were paclitaxel (23%), metals (11%), doxorubicin (9%), bupivacaine and various vaccines (both were 8%). Among the FDA-approved nanoparticle drugs, polymeric (29%), liposomal (22%) and lipid-based (21%) drugs were the most common. In this analysis, we also discuss the differential development of the diverse groups of nanoparticles and their content, as well as the underlying factors behind the trends.

Oblique impact between adhesive units was studied using the Discrete Element Method (DEM)as a means to assess the effective friction coefficient and its dependence on particle shape, surface coverage ratio (SCR; 0.5, 0.75 and 1), and impact angle (15o − 75o) in a low handling velocity regime(0.6 – 1.6 m/s). Adhesive units were created in silico from a spherical carrier particle (100 μm diameter) and monodisperse fine (drug) particles (3 μm large) of a spherical, triangular bipyramidal or tetrahedral shape. The particle interaction was modeled using the Hertz-Mindlin contact model with JKR adhesion (surface energy 0.03 J/m2). A total of over 300 simulations were performed and the effective friction coefficient was extracted from the normal and tangential forces experienced by the carrier particles. The adhered fines resulted in a significantly reduced friction coefficient in comparison to the bare carriers but no additional reduction was observed with increasing SCR, suggesting a saturation already at an SCR of 0.5. The effective friction coefficient was independent of the impact velocity for relative velocities over 1 m/s. The impact angle had a significant effect on the friction coefficient, with head-on type collisions (15o) resulting in the lowest and grazing-type collisions (75o) the highest values. This was especially pronounced for the spherical fines whereas the triangular bipyramidal and especially the tetrahedral fines resulted in a more modest dependence on impact angle but overall considerably higher friction coefficients. These results could be used to better understand and formulate adhesive mixtures.