The implementation of a data learning series focused on clinical development teams in a contract research organization

Effective management of a clinical trialrequires having real time access to information that provides useful insightsinto trial progress and that lends itself to collaborative decisionmaking.  Data visualizations using datafrom multiple source systems employed during the conduct of a clinical trialhave become an essential tool in the recent past as support for collaborativedecision making by project teams. Having the ability to access, analyze, read,work with, and present data to support an argument are  important skills that ensure datavisualizations fulfill their purpose in clinical trial management. There is anexpectation that members of the clinical trial team either possess or developthe data literacy skill sets necessary to collaborate on the successfulexecution of a clinical drug development trial. Here we describe thedevelopment of a Data Learning Series program targeted to increase the data literacyskills within a Contract Research Organization in support of the digitalevolution of the drug development industry.

Screening of Hibiscus and Cinnamomum Plants and Identification of Major Phytometabolites in Potential Plant Extracts Responsible for Apoptosis Induction in Skin Melanoma and Lung Adenocarcinoma Cells

Carcinogenesis is a major concern that severely affects the human population. Owing to persistent demand for novel therapies to treat and prohibit this lethal disease, research interest among scientists is drawing its huge focus toward natural products, as they have minimum toxicity comparable with existing treatment methods. The plants produce secondary metabolites, which are known to have the anticancer potential for clinical drug development. Furthermore, the use of nanocarriers could boost the solubility and stability of phytocompounds to obtain site-targeting delivery. The identification of potential phytochemicals in natural compounds would be beneficial for the synthesis of biocompatible nanoemulsions. The present study aimed to investigate the potential cytotoxicity of ethanol extracts of Hibiscus syriacus and Cinnamomum loureirii Nees plant parts on human skin melanoma (G361) and lung adenocarcinoma (A549) cells. Importantly, biochemical analysis results showed the presence of high phenol (50–55 µgGAE/mg) and flavonoids [42–45 µg quercetin equivalents (QE)/mg] contents with good antioxidant activity (40–58%) in C. loureirii Nees plants extracts. This plant possesses potent antiproliferative activity (60–90%) on the malignant G361 and A549 and cell lines correlated with the production of nitric oxide. Especially, C. loureirii plant extracts have major metabolites that exhibit cancer cell death associated with cell cycle arrest. These findings support the potential application of Cinnamomum for the development of therapeutic nanoemulsion in future cancer therapy.

Clinical development innovation in rare diseases: lessons learned and best practices from the DevelopAKUre consortium

New opportunities have arisen for development of therapies for rare diseases with the increased focus and progress in the field. However, standardised framework integrating individual initiatives has not been formed. We present lessons learned and best practice from a collaborative success case in developing a treatment for a rare genetic disease. Our unique consortium model incorporated several of the identified developments under one project, DevelopAKUre, truly bringing together academia, industry and patient organisations in clinical drug development. We found that the equal partnership between all parties in our consortium was a key success factor creating a momentum based on a strong organisational culture where all partners had high engagement and taking ownership of the entire programme. With an agreed mutual objective, this provided synergies through connecting the strengths of the individual parties. Another key success factor was the central role of the patient organisation within the management team, and their unique study participants’ advocacy role securing the understanding and meeting the needs of the clinical study participants in real-time. This resulted in an accelerated enrolment into the clinical studies with a high retention rate allowing for delivery of the programme with significantly improved timelines. Our project was partly funded through an external EU research grant, enabling our model with equal partnership. Further attention within the community should be given to establishing a functional framework where sustainable funding and risk sharing between private and public organisations allow for our model to be replicated.

Identification of a Novel Delta Opioid Receptor Agonist Chemotype with Potential Negative Allosteric Modulator Capabilities

The δ-opioid receptor (δOR) holds great potential as a therapeutic target. Yet, clinical drug development, which has focused on δOR agonists that mimic the potent and selective tool compound SNC80 have largely failed. It has increasingly become apparent that the SNC80 scaffold carries with it potent and efficacious β-arrestin recruitment. Here, we screened a relatively small (5120 molecules) physical drug library to identify δOR agonists that underrecruit β-arrestin, as it has been suggested that compounds that efficaciously recruit β-arrestin are proconvulsant. The screen identified a hit compound and further characterization using cellular binding and signaling assays revealed that this molecule (R995045, compound 1) exhibited ten-fold selectivity over µ- and κ-opioid receptors. Compound 1 represents a novel chemotype at the δOR. A subsequent characterization of fourteen analogs of compound 1, however did not identify a more potent δOR agonist. Computational modeling and in vitro characterization of compound 1 in the presence of the endogenous agonist leu-enkephalin suggest compound 1 may also bind allosterically and negatively modulate the potency of Leu-enkephalin to inhibit cAMP, acting as a ‘NAM-agonist’ in this assay. The potential physiological utility of such a class of compounds will need to be assessed in future in vivo assays.

3-D Culture of Marine Sponge Cells for Production of Bioactive Compounds

Production of sponge-derived bioactive compounds in vitro has been proposed as an alternative to wild harvest, aquaculture, and chemical synthesis to meet the demands of clinical drug development and manufacture. Until recently, this was not possible because there were no marine invertebrate cell lines. Recent breakthroughs in the development of sponge cell lines and rapid cell division in improved nutrient media now make this approach a viable option. We hypothesized that three-dimensional (3-D) cell cultures would better represent how sponges function in nature, including the production of bioactive compounds. We successfully cultured sponge cells in 3-D matrices using FibraCel® disks, thin hydrogel layers, and gel microdroplets (GMDs). For in vitro production of bioactive compounds, the use of GMDs is recommended. Nutrients and sponge products rapidly diffuse into and out of the 3-D matrix, the GMDs may be scaled up in spinner flasks, and cells and/or secreted products can be easily recovered. Research on scale-up and production is in progress in our laboratory.

Review of applications and challenges of quantitative systems pharmacology modeling and machine learning for heart failure

Quantitative systems pharmacology (QSP) is an important approach in pharmaceutical research and development that facilitates in silico generation of quantitative mechanistic hypotheses and enables in silico trials. As demonstrated by applications from numerous industry groups and interest from regulatory authorities, QSP is becoming an increasingly critical component in clinical drug development. With rapidly evolving computational tools and methods, QSP modeling has achieved important progress in pharmaceutical research and development, including for heart failure (HF). However, various challenges exist in the QSP modeling and clinical characterization of HF. Machine/deep learning (ML/DL) methods have had success in a wide variety of fields and disciplines. They provide data-driven approaches in HF diagnosis and modeling, and offer a novel strategy to inform QSP model development and calibration. The combination of ML/DL and QSP modeling becomes an emergent direction in the understanding of HF and clinical development new therapies. In this work, we review the current status and achievement in QSP and ML/DL for HF, and discuss remaining challenges and future perspectives in the field.

Effect of 1,25-Dihydroxyvitamin D3 on Stem Cells from Human Apical Papilla: Adhesion, Spreading, Proliferation, and Osteogenic Differentiation

Currently, it still remains a difficult problem to treat apical insufficiency of young permanent teeth resulted from pulp necrosis or periapical periodontitis. Previous studies have demonstrated that the treatment of revascularization using stem cells from apical papilla (SCAPs) results in increased root length and thickness of traumatized immature teeth and necrotic pulp. In this study, we investigated the role of 1,25-dihydroxyvitamin D3 in regulating the adhesion, spreading, proliferation, and osteogenic differentiation of SCAP, laying the foundation for subsequent clinical drug development. The immature tooth samples were collected in clinical treatment. SCAPs with stable passage ability were isolated and cultured. The multidifferentiation potential was determined by directed induction culture, while the stem cell characteristics were identified by flow cytometry. There were three groups: group A—SCAPs general culture group; group B—SCAPs osteogenesis induction culture group; and group C—SCAPs osteogenesis induction culture+1,25-dihydroxyvitamin D3 group, and the groups were compared statistically. The proliferation of SCAPs in each groups was detected through CCK-8 assay. RT-qPCR was used to detect the transcription levels of Runx2, ALP, Col I, and OCN of SCAPs in each groups. Results exhibited that the isolated SCAPs had multidifferentiation potential and stem cell characteristics. After 24 h culturing, cells in group C spread better than those in groups A and B. The proliferation activity of SCAPs factored by CCK-8 ranked as group C > group B > group A , while the transcription levels of Runx2, ALP, Col I, and OCN leveled as group C > group B > group A . These results suggested that 1,25-dihydroxyvitamin D3 can significantly promote the adhesion, spreading, and proliferation of SACPs and improve the osteogenic differentiation of SCAPs by means of regulating upward the transcription level of osteogenic differentiation marker.

7,8-Dihydroxyflavone and Neuropsychiatric Disorders: A Translational Perspective from the Mechanism to Drug Development

: 7,8-Dihydroxyflavone (7,8-DHF) is a kind of natural flavonoids, with the potential to cross the blood-brain barrier. 7,8-DHF effectively mimics the effect of brain-derived neurotrophic factor (BDNF) in the brain to selectively activate tyrosine kinase receptor B (TrkB) and downstream signaling pathways, thus playing a neuroprotective role. The preclinical effects of 7,8-DHF have been widely investigated in the neuropsychiatric disorders, including Alzheimer’s disease (AD), Parkinson’s disease (PD), depression and memory impairment. Besides the effect on TrkB, 7,8-DHF could also function through fighting against oxidative stress, cooperating with estrogen receptors or regulating intestinal flora. This review focuses on the recent experimental studies on depression, neurodegenerative diseases and learning and memory function. Additionally, the structural modification and preparation of 7,8-DHF were also concluded and proposed, hoping to provide reference for the follow-up research and clinical drug development of 7,8-DHF in the field of neuropsychiatric disorders.

Multiplexed and reproducible high content screening of live and fixed cells using the Dye Drop method

High throughput measurement of cell perturbation, by libraries of small molecules or gene knockouts, is a key step in functional genomics and pre-clinical drug development. However, it is difficult to perform viable, single-cell assays in 384-well plates, limiting many studies to simple well-average measurements (e.g. CellTiter-Glo). Here we describe a public domain "Dye Drop" method in which sequential density displacement is used to perform multi-step assays for cell viability and EdU incorporation followed by immunofluorescence imaging. The method is rapid, reproducible, can be readily customized, and is compatible with either manual or automated laboratory equipment. We demonstrate Dye Drop in the collection of dose-response data for 67 drugs in 58 breast cancer cell lines and separate cytostatic and cytotoxic responses, thereby providing new insight into the effects of specific drugs on cell cycle progression and cell viability. Dye Drop substantially improves the tradeoff between data content and cost, enabling collection of large information-rich datasets.