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Young patients’ involvement in a composite endpoint method development on acceptability for paediatric oral dosage forms
No full textBackground: In line with the European Paediatric Regulation, the European Medicines Agency (EMA) asks for investigation of a medicine’s acceptability in paediatric medicines development. A standardised acceptability testing method combining the outcome of “swallowability” and “palatability” assessments to a “composite endpoint on acceptability” was recently developed. Before this method’s suitability for selection of the most acceptable drug formulation of a new medicine for children can be broadly recommended, the acceptance and relevance of such established acceptability needs the critical review and input from young patients with understanding of the medicines development methodology. The benefit of involving patients in drug product development, clinical research and innovation is well established.
Methods: During a focus group meeting with the Kids Barcelona (young people advisory group, age 16-23 years) the suitability of the “composite endpoint on acceptability” methodology was assessed. Via electronic questionnaires the importance of involving patients in the medicines development and in the acceptability method development was investigated. Questions on how best to determine palatability and swallowability were asked. The relevance of all EMA-listed acceptability elements was assessed via coloured and numbered stickers and questionnaires.
Results: The results showed that the involvement of young people in the medicines and acceptability method development was rated high. The group worked out that a 5-point smiley Likert Scale is preferred for assessing acceptability by 6 – 11 year old patients, while a Visual Analogue Scale is preferred for collecting adolescents´ opinion. The ranking of the EMA-listed acceptability elements showed that palatability and swallowability are the most relevant parameters, while colour of the medicine was rated as least relevant. These results, established face-to-face, were confirmed in a repeat of the ranking through an electronic questionnaire, completed by the participants individually and remotely, 5 weeks later.
Conclusion: This work reinforced the need and value to involve young people in the medicines lifecycle, and specifically in this acceptability method development. As next step other focus group meetings with more young people from different European countries are planned.
Trial registration: Not applicable
Therapeutic strategies targeting pro-fibrotic macrophages in interstitial lung disease.
No full textIdiopathic pulmonary fibrosis (IPF) is the representative phenotype of interstitial lung disease where severe scarring develops in the lung interstitium. Although antifibrotic treatments are available and have been shown to slow the progression of IPF, improved therapeutic options are still needed. Recent data indicate that macrophages play essential pro-fibrotic roles in the pathogenesis of pulmonary fibrosis. Historically, macrophages have been classified into two functional subtypes, "M1″ and "M2," and it is well described that "M2″ or "alternatively activated" macrophages contribute to fibrosis via the production of fibrotic mediators, such as TGF-β, CTGF, and CCL18. However, highly plastic macrophages may possess distinct functions and phenotypes in the fibrotic lung environment. Thus, M2-like macrophages in vitro and pro-fibrotic macrophages in vivo are not completely identical cell populations. Recent developments in transcriptome analysis, including single-cell RNA sequencing, have attempted to depic
Recent progress in water-based Sonogashira cross-couplings in water
No full textDuring the past five decades, a number of transition metal catalyzed cross-coupling reactions became indispensable to the toolbox of organic chemists, finding a wide range of applications in all industries, and in particular in the agrochemical and pharmaceutical industry.[1] Specifically, palladium-catalyzed cross-coupling reactions have matured to become highly effective methods for efficient CC bond formation. Since the first procedures in the 1970’s,[2] significant progress was achieved thanks to ligand-design that have been resulting into a wide range of applications. The enormous impact of these broadly applicable CC bond forming reactions was recognized in 2010 with the Nobel Prize attributed to R. F. Heck, E.i. Negishi, and A. Suzuki in 2010.[1b, 3] Among the developed cross-coupling reactions, the Sonogashira reaction has shown to be a powerful procedure to construct valuable internal alkynes predominantly using palladium catalysts and copper as co-catalyst.[4] More recently several copper-free procedures have been developed.[5] Further illustrating the impact of the transformation in biological active compounds or intermediates, the Sonogashira reaction is also often found in their synthesi
Systematic Evaluation of Local and Global Machine Learning Models for the Prediction of ADME Properties.
No full textMachine learning (ML) has become an indispensable tool to predict absorption, distribution, metabolism, and excretion (ADME) properties in pharmaceutical research. ML algorithms are trained on molecular structures and corresponding ADME assay data to develop quantitative structure-property relationship (QSPR) models. Traditional QSPR models were trained on compound sets of limited size. With the advent of more complex ML algorithms and data availability, training sets have become larger and more diverse. Most common training approaches consist in either training a model with a small set of similar compounds, namely, compounds designed for the same drug discovery project or chemical series (local model approach) or with a larger set of diverse compounds (global model approach). Global models are built with all experimental data available for an assay, combining compound data from different projects and disease areas. Despite the ML progress made so far, the choice of the appropriate data composition for building ML models is still unclear. Herein, a systematic evaluation of local and global ML models was performed for 10 different experimental assays and 112 drug discovery projects. Results show a consistent superior performance of global models for ADME property predictions. Diagnostic analyses were also carried out to investigate the influence of training set size, structural diversity, and data shift in the relative performance of local and global ML models. Training set and structural diversity did not have an impact in the relative performance on the methods. Instead, data shift helped to identify the projects with larger performance differences between local and global models. Results presented in this work can be leveraged to improve ML-based ADME properties predictions and thus decision-making in drug discovery projects
Avoid missing pKas: high throughput workflow using solution pH-metric in tandem with UV-metric measurements
No full textWe describe a new high throughput automated pKa workflow using potentiometry starting with 10 mM DMSO stock (solution pH-metric). Two approaches using either neat DMSO stock solution or removal of DMSO were evaluated with different sample amounts and cosolvent schemes. These were validated against traditional potentiometric measurements for optimal conditions. Further, we detail how high throughput solution pH-metric experiments are performed in tandem with established UV-metric measurements to capitalize on the advantages of both approaches. This new workflow maintains the sample and time savings required for measuring large number of samples in a drug discovery setting, while avoiding “missing pKas” due to lack of sufficient UV chromophores. The combination of the two assays is key to tackle the challenges of low solubility, overlapping pKas, and assignment of pKas for SAR understanding
A high-throughput 3D cantilever array to model airway smooth muscle hypercontractility in asthma.
No full textAsthma is often characterized by tissue-level mechanical phenotypes that include remodeling of the airway and an increase in airway tightening, driven by the underlying smooth muscle. Existing therapies only provide symptom relief and do not improve the baseline narrowing of the airway or halt progression of the disease. To investigate such targeted therapeutics, there is a need for models that can recapitulate the 3D environment present in this tissue, provide phenotypic readouts of contractility, and be easily integrated into existing assay plate designs and laboratory automation used in drug discovery campaigns. To address this, we have developed DEFLCT, a high-throughput plate insert that can be paired with standard labware to easily generate high quantities of microscale tissues in vitro for screening applications. Using this platform, we exposed primary human airway smooth muscle cell-derived microtissues to a panel of six inflammatory cytokines present in the asthmatic niche, identifying TGF-β1 and IL-13 as inducers of a hypercontractile phenotype. RNAseq analysis further demonstrated enrichment of contractile and remodeling-relevant pathways in TGF-β1 and IL-13 treated tissues as well as pathways generally associated with asthma. Screening of 78 kinase inhibitors on TGF-β1 treated tissues suggests that inhibition of protein kinase C and mTOR/Akt signaling can prevent this hypercontractile phenotype from emerging, while direct inhibition of myosin light chain kinase does not. Taken together, these data establish a disease-relevant 3D tissue model for the asthmatic airway, which combines niche specific inflammatory cues and complex mechanical readouts that can be utilized in drug discovery efforts
A Study to Evaluate Relative Bioavailability, Food Effect, and Pharmacodynamics of Tropifexor, a Farnesoid X Receptor Agonist, in Healthy Participants.
No full textThis open-label, randomized, 3-treatment, 3-period, 6-sequence, crossover study in healthy subjects compared the pharmacokinetic and pharmacodynamic properties of a lipid-based (soft gelatin capsule) prototype final market image (pFMI) formulation of tropifexor (90-µg) to its clinical service form (CSF) and assessed the food effect for the pFMI formulation. In the fasted state, drug exposure was higher for the pFMI. The geometric mean ratios for pFMI versus CSF of peak concentration and area under the concentration-time curve were 2.0 and 1.5, respectively. No food effect was apparent for the pFMI formulation, and the geometric mean ratios for pFMI fed versus pFMI fasted of peak concentration and area under concentration-time curve were 1.0 and 1.0 respectively. Despite having lower systemic exposure, the CSF formulation provided a higher pharmacological response for the gut biomarker fibroblast growth factor 19. Under fasted conditions, fibroblast growth factor 19 maximum change from baseline serum concentration after drug administration and area under the change from baseline serum concentration-time curve from time 0 to 24 hours were 36% for CSF and 12% for FMI. For a second biomarker, serum 7-alpha hydroxy-4-cholest-3-one, the pharmacological activity was comparable between CSF (fasted) and pFMI (both fasted and fed states). The pFMI offers advantages over the CSF in terms of insensitivity to food effect, lower intersubject variability, and overcoming solubility limitations
Preclinical characterization of the Toll-like receptor 7/8 antagonist MHV370 for lupus therapy.
No full textGenetic and in vivo evidence suggests that aberrant recognition of RNA-containing autoantigens by Toll-like receptors (TLRs) 7 and 8 drives autoimmune diseases. Here we report on the preclinical characterization of MHV370, a selective oral TLR7/8 inhibitor. In vitro, MHV370 inhibits TLR7/8-dependent production of cytokines in human and mouse cells, notably interferon-α, a clinically validated driver of autoimmune diseases. Moreover, MHV370 abrogates B cell, plasmacytoid dendritic cell, monocyte, and neutrophil responses downstream of TLR7/8. In vivo, prophylactic or therapeutic administration of MHV370 blocks secretion of TLR7 responses, including cytokine secretion, B cell activation, and gene expression of, e.g., interferon-stimulated genes. In the NZB/W F1 mouse model of lupus, MHV370 halts disease. Unlike hydroxychloroquine, MHV370 potently blocks interferon responses triggered by specific immune complexes from systemic lupus erythematosus patient sera, suggesting differentiation from clinical standard of care. These data support advancement of MHV370 to an ongoing phase 2 clinical trial
Generating the Right Evidence at the Right Time: Principles of a New Class of Flexible Augmented Clinical Trial Designs.
No full textTo support informed decision making, clear descriptions of the beneficial and harmful effects of a treatment are needed by various stakeholders. The current paradigm is to generate evidence sequentially through different experiments. However, data generated later, perhaps through observational studies, can be difficult to compare with earlier randomized trial data, resulting in confusion in understanding and interpretation of treatment effects. Moreover, the scientific questions these later experiments can serve to answer often remain vague. We propose Flexible Augmented Clinical Trial for Improved eVidence gEneration (FACTIVE), a new class of study designs enabling flexible augmentation of confirmatory randomized controlled trials with concurrent and close-to-real-world elements. Our starting point is to use clearly defined objectives for evidence generation, which are formulated through early discussion with health technology assessment (HTA) bodies and are additional to regulatory requirements for authorization of a new treatment. These enabling designs facilitate estimation of certain well-defined treatment effects in the confirmatory part and other complementary treatment effects in a concurrent real-world part. Each stakeholder should use the evidence that is relevant within their own decision-making framework. High quality data are generated under one single protocol and the use of randomization ensures rigorous statistical inference and interpretation within and between the different parts of the experiment. Evidence for the decision making of HTA bodies could be available earlier than is currently the case
Society for Birth Defects Research and Prevention 2022-2027 strategic plan.
No full textThe sixth Strategic Planning Session of the Society for Birth Defects Research and Prevention (BDRP) was held on April 24-25, 2022, in Alexandria, VA.This effort built upon previous strategic planning sessions, conducted every 5 years.The overall process was designed to identify BDRP's vision, purpose, culture, and potential, as well as to communicate the value that BDRP brings to its members, volunteers, partners, and the greater community.The BDRP 2022-2027 Strategic Plan provides the BDRP leadership, members, and staff with a clearly articulated framework and direction to support long-term sustainability and growth of the society