Improving and accelerating drug development for nervous system disorders

Recent advances in 3D models of the nervous system for neural regeneration research and drug development

The development of drugs for nervous diseases poses distinctive difficulties owing to the incomplete understanding of the physiology and complex pathogenesis of the multifaceted central (CNS) and peripheral (PNS) nervous systems. Conventional animal tests and in vitro two-dimensional (2D) cell cultures fail to reproduce the sophisticated structure of natural human tissues, hindering the new drug discovery process. The emerging three-dimensional (3D) neural tissue models, including organoids, organ-on-chips and 3D-printed neural scaffolds, can provide an improved reproduction of the critical features, structural complexity, biological functions, dynamic circulation micro-environment and cell-matrix/cell interactions of the nervous systems. This review examines state-of-the-art 3D models for neural physiology/pathology, emphasizing their drug development applications. Fundamental advantages of various in vitro 3D neural models for investigating the mechanisms of nerve regeneration and disorders in both the CNS and PNS are compared in terms of the different modeling techniques. In addition, the applications of 3D neural models in drug development are summarized covering a range of areas such as disease modeling for basic research, pharmacokinetic and pharmacodynamic testing for drug screening and drug safety evaluation. Furthermore, current challenges and future outlook of biomimetic models and the existing bottlenecks hindering their successful translation into clinical use are discussed. STATEMENT OF SIGNIFICANCE: This review highlights the groundbreaking potential of 3D neural models-organoids, organ-on-chips, and 3D-printed scaffolds-to revolutionize neurological research and drug development. Unlike conventional methods, these models replicate the intricate structure and function of human nervous systems, enabling precise study of diseases like Alzheimer's, spinal injuries, and brain tumors. By synthesizing recent advancements, the review compares techniques, their applications in drug screening and personalized medicine, and addresses challenges in model accuracy and scalability. Bridging neuroscience, engineering, and pharmacology, this work provides a roadmap for researchers to innovate therapies. Its insights are critical for accelerating drug discovery and improving treatment outcomes, making it essential for scientists and clinicians tackling neurological disorders.

Neuroprotective effects of macrostemonoside T on glutamate-induced injury in HT22 cells

Glutamate is a critical excitatory neurotransmitter involved in numerous cellular functions. However, excessive glutamate release can lead to neuronal cell death through oxidative stress, which is implicated in the pathogenesis of various neurological disorders. Therefore, strategies aimed at preventing oxidative stress have emerged as promising therapeutic approaches. Macrostemonoside T (MST), a novel steroidal saponin isolated from the traditional Chinese medicine Allii Macrostemon Bulbus, has demonstrated significant antioxidant activity in previous studies. Nevertheless, its neuroprotective effects against oxidative damage and the underlying molecular mechanisms have not yet been fully elucidated. In this study, we established a glutamate-induced cell injury model using mouse hippocampal neurons (HT22) to investigate the neuroprotective effects of MST and explore its potential mechanisms. A variety of techniques, including DCFH-DA staining, JC-1 staining, Hoechst 33,258 staining, flow cytometry, immunofluorescence staining, ELISA, Western blot analysis, and molecular docking, were employed. The results demonstrated that MST treatment significantly improved the survival of HT22 cells exposed to glutamate. Moreover, MST treatment markedly reduced intracellular levels of reactive oxygen species (ROS) and malondialdehyde while enhancing the activity of antioxidant enzymes such as superoxide dismutase, catalase, and glutathione peroxidase. MST also mitigated mitochondrial dysfunction by inhibiting mitochondrial fission and preserving mitochondrial membrane potential. Additionally, MST reduced excessive autophagy by decreasing autophagy markers and inhibiting the transition from LC3I to LC3II. Furthermore, MST decreased apoptosis rates, lowered pro-apoptotic protein BAX levels, increased the expression of the anti-apoptotic protein Bcl-2, and inhibited the release of apoptosis-inducing factors from mitochondria. Molecular docking analysis showed that MST enhanced PKA activity by blocking endogenous inhibition of PKA, which in turn activated the PKA/CREB/BDNF signalling pathway. Subsequent validation using immunofluorescence and Western blotting further confirmed that MST treatment significantly reversed the glutamate-induced reduction of PRKACA, CREB, p-CREB, and BDNF protein levels. In conclusion, MST is a potent neuroprotective agent that ameliorates glutamate-induced neuronal damage by inhibiting oxidative stress, alleviating mitochondrial dysfunction, reducing autophagy and apoptosis, and activating the PKA/CREB/BDNF signaling pathway.

Harnessing the potential of human induced pluripotent stem cells, functional assays and machine learning for neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) affect 4.7% of the global population and are associated with delays in brain development and a spectrum of impairments that can lead to lifelong disability and even mortality. Identification of biomarkers for accurate diagnosis and medications for effective treatment are lacking, in part due to the historical use of preclinical model systems that do not translate well to the clinic for neurological disorders, such as rodents and heterologous cell lines. Human-induced pluripotent stem cells (hiPSCs) are a promising in vitro system for modeling NDDs, providing opportunities to understand mechanisms driving NDDs in human neurons. Functional assays, including patch clamping, multielectrode array, and imaging-based assays, are popular tools employed with hiPSC disease models for disease investigation. Recent progress in machine learning (ML) algorithms also presents unprecedented opportunities to advance the NDD research process. In this review, we compare two-dimensional and three-dimensional hiPSC formats for disease modeling, discuss the applications of functional assays, and offer insights on incorporating ML into hiPSC-based NDD research and drug screening.

Nanotherapeutics for Meningitis: Enhancing Drug Delivery Across the Blood-Brain Barrier

Meningitis is the acute or chronic inflammation of the protective membranes, surrounding the brain and spinal cord, and this inflammatory process spreads throughout the subarachnoid space. The traditional drug delivery methods pose a disadvantage in limiting the capacity of crossing the blood-brain barrier (BBB) to reach the central nervous system (CNS). Hence, it is imperative to develop novel approaches that can overcome these constraints and offer efficient therapy for meningitis. Nanoparticle (NP)-based therapeutic approaches have the potential to address the limitations such as penetrating the BBB and achieving targeted drug release in specific cells and tissues. This review highlights recent advancements in nanotechnology-based approaches, such as functionalized polymeric nanoparticles, solid lipid nanoparticles (SLNs), nanostructured lipid carriers, nanoemulsions, liposomes, transferosomes, and metallic NPs for the treatment of meningitis. Recently, bionics has emerged as a next-generation technology in the development of novel ideas from biological principles, structures, and interactions for neurological and neuroinfectious diseases. Despite their potential, more studies are needed to ensure the safety and efficacy of NP-based drug delivery systems focusing on critical aspects such as toxicity, immunogenicity, and pharmacokinetics. Therefore, this review addresses current treatment strategies and innovative nanoparticle approaches, and it discusses future directions for efficient and targeted meningitis therapies.

Evaluating time-to-event surrogates for time-to-event true endpoints: an information-theoretic approach based on causal inference

Putative surrogate endpoints must undergo a rigorous statistical evaluation before they can be used in clinical trials. Numerous frameworks have been introduced for this purpose. In this study, we extend the scope of the information-theoretic causal-inference approach to encompass scenarios where both outcomes are time-to-event endpoints, using the flexibility provided by D-vine copulas. We evaluate the quality of the putative surrogate using the individual causal association (ICA)-a measure based on the mutual information between the individual causal treatment effects. However, in spite of its appealing mathematical properties, the ICA may be ill defined for composite endpoints. Therefore, we also propose an alternative rank-based metric for assessing the ICA. Due to the fundamental problem of causal inference, the joint distribution of all potential outcomes is only partially identifiable and, consequently, the ICA cannot be estimated without strong unverifiable assumptions. This is addressed by a formal sensitivity analysis that is summarized by the so-called intervals of ignorance and uncertainty. The frequentist properties of these intervals are discussed in detail. Finally, the proposed methods are illustrated with an analysis of pooled data from two advanced colorectal cancer trials. The newly developed techniques have been implemented in the R package Surrogate.

Advances in artificial intelligence for drug delivery and development: A comprehensive review

Artificial intelligence (AI) has emerged as a powerful tool to revolutionize the healthcare sector, including drug delivery and development. This review explores the current and future applications of AI in the pharmaceutical industry, focusing on drug delivery and development. It covers various aspects such as smart drug delivery networks, sensors, drug repurposing, statistical modeling, and simulation of biotechnological and biological systems. The integration of AI with nanotechnologies and nanomedicines is also examined. AI offers significant advancements in drug discovery by efficiently identifying compounds, validating drug targets, streamlining drug structures, and prioritizing response templates. Techniques like data mining, multitask learning, and high-throughput screening contribute to better drug discovery and development innovations. The review discusses AI applications in drug formulation and delivery, clinical trials, drug safety, and pharmacovigilance. It addresses regulatory considerations and challenges associated with AI in pharmaceuticals, including privacy, data security, and interpretability of AI models. The review concludes with future perspectives, highlighting emerging trends, addressing limitations and biases in AI models, and emphasizing the importance of collaboration and knowledge sharing. It provides a comprehensive overview of AI's potential to transform the pharmaceutical industry and improve patient care while identifying further research and development areas.

Deep-PK: deep learning for small molecule pharmacokinetic and toxicity prediction

Evaluating pharmacokinetic properties of small molecules is considered a key feature in most drug development and high-throughput screening processes. Generally, pharmacokinetics, which represent the fate of drugs in the human body, are described from four perspectives: absorption, distribution, metabolism and excretion-all of which are closely related to a fifth perspective, toxicity (ADMET). Since obtaining ADMET data from in vitro, in vivo or pre-clinical stages is time consuming and expensive, many efforts have been made to predict ADMET properties via computational approaches. However, the majority of available methods are limited in their ability to provide pharmacokinetics and toxicity for diverse targets, ensure good overall accuracy, and offer ease of use, interpretability and extensibility for further optimizations. Here, we introduce Deep-PK, a deep learning-based pharmacokinetic and toxicity prediction, analysis and optimization platform. We applied graph neural networks and graph-based signatures as a graph-level feature to yield the best predictive performance across 73 endpoints, including 64 ADMET and 9 general properties. With these powerful models, Deep-PK supports molecular optimization and interpretation, aiding users in optimizing and understanding pharmacokinetics and toxicity for given input molecules. The Deep-PK is freely available at https://biosig.lab.uq.edu.au/deeppk/.

Modeling blood-brain barrier formation and cerebral cavernous malformations in human PSC-derived organoids

The human blood-brain barrier (hBBB) is a highly specialized structure that regulates passage across blood and central nervous system (CNS) compartments. Despite its critical physiological role, there are no reliable in vitro models that can mimic hBBB development and function. Here, we constructed hBBB assembloids from brain and blood vessel organoids derived from human pluripotent stem cells. We validated the acquisition of blood-brain barrier (BBB)-specific molecular, cellular, transcriptomic, and functional characteristics and uncovered an extensive neuro-vascular crosstalk with a spatial pattern within hBBB assembloids. When we used patient-derived hBBB assembloids to model cerebral cavernous malformations (CCMs), we found that these assembloids recapitulated the cavernoma anatomy and BBB breakdown observed in patients. Upon comparison of phenotypes and transcriptome between patient-derived hBBB assembloids and primary human cavernoma tissues, we uncovered CCM-related molecular and cellular alterations. Taken together, we report hBBB assembloids that mimic the core properties of the hBBB and identify a potentially underlying cause of CCMs.

Chronic Opioid Treatment Arrests Neurodevelopment and Alters Synaptic Activity in Human Midbrain Organoids

Understanding the impact of long-term opioid exposure on the embryonic brain is critical due to the surging number of pregnant mothers with opioid dependency. However, this has been limited by human brain inaccessibility and cross-species differences in animal models. Here, a human midbrain model is established that uses hiPSC-derived midbrain organoids to assess cell-type-specific responses to acute and chronic fentanyl treatment and fentanyl withdrawal. Single-cell mRNA sequencing of 25,510 cells from organoids in different treatment groups reveals that chronic fentanyl treatment arrests neuronal subtype specification during early midbrain development and alters synaptic activity and neuron projection. In contrast, acute fentanyl treatment increases dopamine release but does not significantly alter gene expression related to cell lineage development. These results provide the first examination of the effects of opioid exposure on human midbrain development at the single-cell level.

Improving drug delivery to the brain: the prodrug approach

INTRODUCTION

The prodrug approach has been thought to be a simple solution to improve brain drug delivery for decades. Nevertheless, it still comes as a surprise that there is relatively little success in the field. The best example anti-parkinsonian drug levodopa has been serendipitously discovered to be a transporter-utilizing brain-delivered prodrug rather than a rationally developed one.

AREAS COVERED

The lack of success can mainly be explained by the insufficient understanding of the role of membrane proteins that can facilitate drug delivery at dynamic barriers, such as the blood-brain barrier (BBB), but also by the sparse knowledge of prodrug bioconverting enzymes in the brain. This review summarizes the current status of the prodrug attempts that have been developed in the past to improve brain drug delivery.

EXPERT OPINION

With the expandingly improved analytical and computational technologies, it is anticipated that enhanced brain drug delivery will be eventually achieved for most of the central nervous system (CNS) acting drugs. However, this requires that carrier-mediated (pro)drug delivery methods are implemented in the very early phases of the drug development processes and not as a last step to survive a problematic investigational drug candidate.

ADAR Family Proteins: A Structural Review

This review aims to highlight the structures of ADAR proteins that have been crucial in the discernment of their functions and are relevant to future therapeutic development. ADAR proteins can correct or diversify genetic information, underscoring their pivotal contribution to protein diversity and the sophistication of neuronal networks. ADAR proteins have numerous functions in RNA editing independent roles and through the mechanisms of A-I RNA editing that continue to be revealed. Provided is a detailed examination of the ADAR family members-ADAR1, ADAR2, and ADAR3-each characterized by distinct isoforms that offer both structural diversity and functional variability, significantly affecting RNA editing mechanisms and exhibiting tissue-specific regulatory patterns, highlighting their shared features, such as double-stranded RNA binding domains (dsRBD) and a catalytic deaminase domain (CDD). Moreover, it explores ADARs' extensive roles in immunity, RNA interference, and disease modulation, demonstrating their ambivalent nature in both the advancement and inhibition of diseases. Through this comprehensive analysis, the review seeks to underline the potential of targeting ADAR proteins in therapeutic strategies, urging continued investigation into their biological mechanisms and health implications.

Therapeutic mechanisms of psychedelics and entactogens

Recent clinical and preclinical evidence suggests that psychedelics and entactogens may produce both rapid and sustained therapeutic effects across several indications. Currently, there is a disconnect between how these compounds are used in the clinic and how they are studied in preclinical species, which has led to a gap in our mechanistic understanding of how these compounds might positively impact mental health. Human studies have emphasized extra-pharmacological factors that could modulate psychedelic-induced therapeutic responses including set, setting, and integration-factors that are poorly modelled in current animal experiments. In contrast, animal studies have focused on changes in neuronal activation and structural plasticity-outcomes that are challenging to measure in humans. Here, we describe several hypotheses that might explain how psychedelics rescue neuropsychiatric disease symptoms, and we propose ways to bridge the gap between human and rodent studies. Given the diverse pharmacological profiles of psychedelics and entactogens, we suggest that their rapid and sustained therapeutic mechanisms of action might best be described by the collection of circuits that they modulate rather than their actions at any single molecular target. Thus, approaches focusing on selective circuit modulation of behavioral phenotypes might prove more fruitful than target-based methods for identifying novel compounds with rapid and sustained therapeutic effects similar to psychedelics and entactogens.

Pharmacological modulation of conditioned fear in the fear-potentiated startle test: a systematic review and meta-analysis of animal studies

RATIONALE AND OBJECTIVES

Fear conditioning is an important aspect in the pathophysiology of anxiety disorders. The fear-potentiated startle test is based on classical fear conditioning and over the years, a broad range of drugs have been tested in this test. Synthesis of the available data may further our understanding of the neurotransmitter systems that are involved in the expression of conditioned fear.

METHODS

Following a comprehensive search in Medline and Embase, we included 68 research articles that reported on 103 drugs, covering 56 different drug classes. The systematic review was limited to studies using acute, systemic drug administration in naive animals.

RESULTS

Qualitative data synthesis showed that most clinically active anxiolytics, but not serotonin-reuptake inhibitors, reduced cued fear. Anxiogenic drugs increased fear potentiation in 35% of the experiments, reduced fear potentiation in 29% of the experiments, and were without effect in 29% of the experiments. Meta-analyses could be performed for five drug classes and showed that benzodiazepines, buspirone, 5-HT1A agonists, 5-HT1A antagonists, and mGluR2,3 agonists reduced cued conditioned fear. The non-cued baseline startle response, which may reflect contextual anxiety, was only significantly reduced by benzodiazepines and 5-HT1A antagonists. No associations were found between drug effects and methodological characteristics, except for strain.

CONCLUSIONS

The fear-potentiated startle test appears to have moderate to high predictive validity and may serve as a valuable tool for the development of novel anxiolytics. Given the limited available data, the generally low study quality and high heterogeneity additional studies are warranted to corroborate the findings of this review.

Adipose-Derived Stem Cells Spontaneously Express Neural Markers When Grown in a PEG-Based 3D Matrix

Neurological diseases are among the leading causes of disability and death worldwide and remain difficult to treat. Tissue engineering offers avenues to test potential treatments; however, the development of biologically accurate models of brain tissues remains challenging. Given their neurogenic potential and availability, adipose-derived stem cells (ADSCs) are of interest for creating neural models. While progress has been made in differentiating ADSCs into neural cells, their differentiation in 3D environments, which are more representative of the in vivo physiological conditions of the nervous system, is crucial. This can be achieved by modulating the 3D matrix composition and stiffness. Human ADSCs were cultured for 14 days in a 1.1 kPa polyethylene glycol-based 3D hydrogel matrix to assess effects on cell morphology, cell viability, proteome changes and spontaneous neural differentiation. Results showed that cells continued to proliferate over the 14-day period and presented a different morphology to 2D cultures, with the cells elongating and aligning with one another. The proteome analysis revealed 439 proteins changed in abundance by >1.5 fold. Cyclic nucleotide 3'-phosphodiesterase (CNPase) markers were identified using immunocytochemistry and confirmed with proteomics. Findings indicate that ADSCs spontaneously increase neural marker expression when grown in an environment with similar mechanical properties to the central nervous system.

The Canadian Open Neuroscience Platform-An open science framework for the neuroscience community

The Canadian Open Neuroscience Platform (CONP) takes a multifaceted approach to enabling open neuroscience, aiming to make research, data, and tools accessible to everyone, with the ultimate objective of accelerating discovery. Its core infrastructure is the CONP Portal, a repository with a decentralized design, where datasets and analysis tools across disparate platforms can be browsed, searched, accessed, and shared in accordance with FAIR principles. Another key piece of CONP infrastructure is NeuroLibre, a preprint server capable of creating and hosting executable and fully reproducible scientific publications that embed text, figures, and code. As part of its holistic approach, the CONP has also constructed frameworks and guidance for ethics and data governance, provided support and developed resources to help train the next generation of neuroscientists, and has fostered and grown an engaged community through outreach and communications. In this manuscript, we provide a high-level overview of this multipronged platform and its vision of lowering the barriers to the practice of open neuroscience and yielding the associated benefits for both individual researchers and the wider community.

Potential role of a novel biphenanthrene derivative isolated from Aerides falcata in central nervous system diseases

Central nervous system (CNS) diseases are a significant health burden globally, with the development of novel drugs lagging behind clinical needs. Orchidaceae plants have been traditionally used to treat CNS diseases, leading to the identification of therapeutic leads against CNS diseases from the Aerides falcata orchid plant in the present study. The study isolated and characterized ten compounds, including a previously undescribed biphenanthrene derivative, Aerifalcatin (1), for the first time from the A. falcata extract. The novel compound 1 and known compounds, such as 2,7-dihydroxy-3,4,6-trimethoxyphenanthrene (5), agrostonin (7), and syringaresinol (9), showed potential activity in CNS-associated disease models. Notably, compounds 1, 5, 7, and 9 demonstrated the ability to alleviate LPS-induced NO release in BV-2 microglial cells, with IC50 values of 0.9, 2.5, 2.6, and 1.4 μM, respectively. These compounds also significantly inhibited the release of pro-inflammatory cytokines, IL-6 and TNF-α, reflecting their potential anti-neuroinflammatory effects. Additionally, compounds 1, 7, and 9 were found to reduce cell growth and migration of glioblastoma and neuroblastoma cells, indicating their potential use as anticancer agents in the CNS. In summary, the bioactive agents isolated from the A. falcata extract offer plausible therapeutic options for CNS diseases.

Alleviating anxiety and taming trauma: Novel pharmacotherapeutics for anxiety disorders and posttraumatic stress disorder

Psychiatric disorders associated with psychological trauma, stress and anxiety are a highly prevalent and increasing cause of morbidity worldwide. Current therapeutic approaches, including medication, are effective in alleviating symptoms of anxiety disorders and posttraumatic stress disorder (PTSD), at least in some individuals, but have unwanted side-effects and do not resolve underlying pathophysiology. After a period of stagnation, there is renewed enthusiasm from public, academic and commercial parties in designing and developing drug treatments for these disorders. Here, we aim to provide a snapshot of the current state of this field that is written for neuropharmacologists, but also practicing clinicians and the interested lay-reader. After introducing currently available drug treatments, we summarize recent/ongoing clinical assessment of novel medicines for anxiety and PTSD, grouped according to primary neurochemical targets and their potential to produce acute and/or enduring therapeutic effects. The evaluation of putative treatments targeting monoamine (including psychedelics), GABA, glutamate, cannabinoid, cholinergic and neuropeptide systems, amongst others, are discussed. We emphasize the importance of designing and clinically assessing new medications based on a firm understanding of the underlying neurobiology stemming from the rapid advances being made in neuroscience. This includes harnessing neuroplasticity to bring about lasting beneficial changes in the brain rather than - as many current medications do - produce a transient attenuation of symptoms, as exemplified by combining psychotropic/cognitive enhancing drugs with psychotherapeutic approaches. We conclude by noting some of the other emerging trends in this promising new phase of drug development.

Human mini-brains for reconstituting central nervous system disorders

Neurological disorders in the central nervous system (CNS) are progressive and irreversible diseases leading to devastating impacts on patients' life as they cause cognitive impairment, dementia, and even loss of essential body functions. The development of effective medicines curing CNS disorders is, however, one of the most ambitious challenges due to the extremely complex functions and structures of the human brain. In this regard, there are unmet needs to develop simplified but physiopathologically-relevant brain models. Recent advances in the microfluidic techniques allow multicellular culture forming miniaturized 3D human brains by aligning parts of brain regions with specific cells serving suitable functions. In this review, we overview designs and strategies of microfluidics-based human mini-brains for reconstituting CNS disorders, particularly Alzheimer's disease (AD), Parkinson's disease (PD), traumatic brain injury (TBI), vascular dementia (VD), and environmental risk factor-driven dementia (ERFD). Afterward, the applications of the mini-brains in the area of medical science are introduced in terms of the clarification of pathogenic mechanisms and identification of promising biomarkers. We also present expanded model systems ranging from the CNS to CNS-connecting organ axes to study the entry pathways of pathological risk factors into the brain. Lastly, the advantages and potential challenges of current model systems are addressed with future perspectives.

Zebrafish, a biological model for pharmaceutical research for the management of anxiety

The zebrafish (Danio rerio) is a valuable animal model rapidly becoming more commonly used in pharmaceutical studies. Due to its low-cost maintenance and high breeding potential, the zebrafish is a suitable substitute for most adult rodents (mice and rats) in neuroscience research. It is widely used in various anxiety models. This species has been used to develop a conceptual framework for anxiety behavior studies with broad applications in the laboratory, including the study of herbal and chemical drugs. This review discusses the latest studies of anxiety-related behavior in the zebrafish model.

Recent Advances in Brain Organoid Technology for Human Brain Research

Brain organoids are self-assembled three-dimensional aggregates with brain-like cell types and structures and have emerged as new model systems that can be used to investigate human neurodevelopment and neurological disorders. However, brain organoids are not as mature and functional as real human brains due to limitations of the culture system with insufficient developmental patterning signals and a lack of components that are important for brain development and function, such as the non-neural population and vasculature. In addition, establishing the desired brain-like environment and monitoring the complex neural networks and physiological functions of the brain organoids remain challenging. The current protocols to generate brain organoids also have problems with heterogeneity and batch variation due to spontaneous self-organization of brain organoids into complex architectures of the brain. To address these limitations of current brain organoid technologies, various engineering platforms, such as extracellular matrices, fluidic devices, three-dimensional bioprinting, bioreactors, polymeric scaffolds, microelectrodes, and biochemical sensors, have been employed to improve neuronal development and maturation, reduce structural heterogeneity, and facilitate functional analysis and monitoring. In this review, we provide an overview of the latest engineering techniques that overcome these limitations in the production and application of brain organoids.

Experimental Medicine Approaches in Early-Phase CNS Drug Development

Traditionally, Phase 1 clinical trials were largely conducted in healthy normal volunteers and focused on collection of safety, tolerability, and pharmacokinetic data. However, in the CNS therapeutic area, with more drugs failing in later phase development, Phase 1 trials have undergone an evolution that includes incorporation of novel approaches involving novel study designs, inclusion of biomarkers, and early inclusion of patients to improve the pharmacologic understanding of novel CNS-active compounds early in clinical development with the hope of improving success in later phase pivotal trials. In this chapter, the authors will discuss the changing landscape of Phase 1 clinical trials in CNS, including novel trial methodology, inclusion of pharmacodynamic biomarkers, and experimental medicine approaches to inform early decision-making in clinical development.

Research progress of fibroblast growth factor in nervous system diseases

Fibroblast growth factors (FGF) are a group of structurally related polypeptides which constitute an elaborate signaling system with their receptors. Evidence accumulated in the years suggests that the FGF family plays a key role in the repair of central nervous system injury. The main protective mechanisms include activating the expression of PI3K-Akt, peroxisome proliferator-activated receptor (PPARγ) and other signals; inhibiting NF-κB-mediated inflammatory response, oxidative stress and apoptosis; regulating neuronal differentiation and neuronal excitability as well as participating in protection of neurovascular units and nerve function repair. This paper comprehensively summarizes the latest research progress in FGF signaling related to diseases of the central nervous system such as cerebral infarction, cerebral hemorrhage, traumatic brain injury, Alzheimer's disease, Parkinson's disease, epilepsy and depression, aiming to provide scientific basis and reference for the development of innovative FGF drugs for the prevention and treatment of neurological diseases.

Efficacy of eicosapentaenoic acid in inflammatory depression: study protocol for a match-mismatch trial

BACKGROUND

Most antidepressant treatment studies have included patients strictly based on the Diagnostic and Statistical Manual of Mental Disorders definition of Major Depressive Disorder (MDD). Given the heterogeneity of MDD, this approach may have obscured inter-patient differences and hampered the development of novel and targeted treatment strategies. An alternative strategy is ​​to use biomarkers to delineate endophenotypes of depression and test if these can be targeted via mechanism-based interventions. Several lines of evidence suggest that "inflammatory depression" is a clinically meaningful subtype of depression. Preliminary data indicate that omega-3 fatty acids, with their anti-inflammatory and neuroprotective properties, may be efficacious in this subtype of depression, and this study aims to test this hypothesis.

METHOD

We conduct a match-mismatch-trial to test if add-on omega-3 fatty acid eicosapentaenoic acid (EPA) reduces depressive symptoms in patients with MDD and systemic low-grade inflammation. MDD patients on a stable antidepressant treatment are stratified at baseline on high sensitivity-C-reactive protein (hs-CRP) levels to a high-inflammation group (hs-CRP ≥ 3 mg/L) or a low-inflammation group (hs-CRP < 3 mg/L). Both groups receive add-on EPA (2 g per day) for 8 weeks with three study visits, all including blood draws. Patients and raters are blind to inflammation status. Primary outcome measure is change in Hamilton Depression Rating Scale score between baseline and week 8. We hypothesize that the inflammation group has a superior antidepressant response to EPA compared to the non-inflammation group. Secondary outcomes include a composite score of "inflammatory depressive symptoms", quality of life, anxiety, anhedonia, sleep disturbances, fatigue, cognitive performance and change in biomarkers relating to inflammation, oxidative stress, metabolomics and cellular aging.

DISCUSSION

In this study we will, for the first time using a match-mismatch trial design, test if omega-3 is an efficacious treatment for inflammatory depression. If our study is successful, it could add to the field of precision psychiatry.

TRIAL REGISTRATION

This trial was registered May 8, 2017 on clinicaltrials.gov under the reference number NCT03143075.

Phenotype-based drug screening: An in vivo strategy to classify and identify the chemical compounds modulating zebrafish M-cell regeneration

Several disease-modulatory FDA-approved drugs are being used in patients with neurodegenerative diseases. However, information on their toxicity-related profiles is very limited. Therefore, measurement of drug toxicity is essential to increase the knowledge of their side effects. This study aimed to identify compounds that can modulate M-cell regeneration by causing neuro-protection and -toxicity. Here, we developed a simple and efficient in vivo assay using Tg (hsp: Gal4FF62A; UAS: nfsB-mCherry) transgenic zebrafish larvae. Interestingly, via the phenotype-based drug screening approach, we rapidly investigated 1,260 compounds from the United States drug collection and validated these in large numbers, including 14 compounds, that were obstructing this regeneration process. Next, 4 FDA-approved drugs out of 14 compounds were selected as the lead hits for in silico analysis to clarify their binding patterns with PTEN and SOCS3 signaling due to their significant potential in the inhibition of axon regeneration. Molecular docking studies indicated good binding affinity of all 4 drugs with the respective signaling molecules. This may point to PTEN and SOCS3 as the signaling molecules responsible for reducing axon regeneration. Moreover, the acute effect of compounds in reducing M-cell regeneration delineated their toxic effect. In conclusion, our in vivo along with in silico screening strategy will promote the rapid translation of new therapeutics to improve knowledge of the toxicity profile of approved/non-approved drugs efficiently.

Influence of microchannel geometry on device performance and electrophysiological recording fidelity during long-term studies of connected neural populations

Compartmentalized microfluidic neural cell culture platforms, which physically separate axons from the neural soma using a series of microchannels, have been used for studying a wide range of pathological conditions and basic neuroscience questions. While each study has different experimental needs, the fundamental design of these devices has largely remained unchanged and a systematic study to establish long-term neural cultures in this format is lacking. Here, we investigate the influence of microchannel geometry and cell seeding density on device performance particularly in the context of long-term studies of synaptically-connected, yet fluidically-isolated neural populations of neurons and glia. Of the different experimental parameters, the microchannel height was the principal determinant of device performance, where the other parameters offer additional degrees of freedom in customizing such devices for specific applications. We condense the effects of these parameters into design rules and demonstrate their utility in engineering a microfluidic neural culture platform with integrated microelectrode arrays. The engineered device successfully recorded from primary rat cortical cells for 59 days in vitro with more than on order of magnitude enhancement in signal-to-noise ratio in the microchannels.

Differential vulnerability of anterior cingulate cortex cell types to diseases and drugs

In psychiatric disorders, mismatches between disease states and therapeutic strategies are highly pronounced, largely because of unanswered questions regarding specific vulnerabilities of different cell types and therapeutic responses. Which cellular events (housekeeping or salient) are most affected? Which cell types succumb first to challenges, and which exhibit the strongest response to drugs? Are these events coordinated between cell types? How does disease and drug effect this coordination? To address these questions, we analyzed single-nucleus-RNAseq (sn-RNAseq) data from the human anterior cingulate cortex-a region involved in many psychiatric disorders. Density index, a metric for quantifying similarities and dissimilarities across functional profiles, was employed to identify common or salient functional themes across cell types. Cell-specific signatures were integrated with existing disease and drug-specific signatures to determine cell-type-specific vulnerabilities, druggabilities, and responsiveness. Clustering of functional profiles revealed cell types jointly participating in these events. SST and VIP interneurons were found to be most vulnerable, whereas pyramidal neurons were least. Overall, the disease state is superficial layer-centric, influences cell-specific salient themes, strongly impacts disinhibitory neurons, and influences astrocyte interaction with a subset of deep-layer pyramidal neurons. In absence of disease, drugs profiles largely recapitulate disease profiles, offering a possible explanation for drug side effects. However, in presence of disease, drug activities, are deep layer-centric and involve activating a distinct subset of deep-layer pyramidal neurons to circumvent the disease state's disinhibitory circuit malfunction. These findings demonstrate a novel application of sn-RNAseq data to explain drug and disease action at a systems level.

toxCSM: comprehensive prediction of small molecule toxicity profiles

Drug discovery is a lengthy, costly and high-risk endeavour that is further convoluted by high attrition rates in later development stages. Toxicity has been one of the main causes of failure during clinical trials, increasing drug development time and costs. To facilitate early identification and optimisation of toxicity profiles, several computational tools emerged aiming at improving success rates by timely pre-screening drug candidates. Despite these efforts, there is an increasing demand for platforms capable of assessing both environmental as well as human-based toxicity properties at large scale. Here, we present toxCSM, a comprehensive computational platform for the study and optimisation of toxicity profiles of small molecules. toxCSM leverages on the well-established concepts of graph-based signatures, molecular descriptors and similarity scores to develop 36 models for predicting a range of toxicity properties, which can assist in developing safer drugs and agrochemicals. toxCSM achieved an Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) of up to 0.99 and Pearson's correlation coefficients of up to 0.94 on 10-fold cross-validation, with comparable performance on blind test sets, outperforming all alternative methods. toxCSM is freely available as a user-friendly web server and API at http://biosig.lab.uq.edu.au/toxcsm.

Ethanol extract of Pharbitis nil ameliorates liver fibrosis through regulation of the TGFβ1-SMAD2/3 pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Pharbitis nil (L.) Choisy is a medicinal herb, and herbal remedies based on its seeds have been used to treat of obesity and liver diseases, including fatty liver and liver cirrhosis in East Asia.

AIM OF THE STUDY

Liver fibrosis is a major cause of morbidity and mortality in patients with chronic liver inflammation such as that caused by non-alcoholic steatohepatitis. However, no effective pharmaceutical treatment for liver fibrosis has been approved. In this study, we aimed to investigate that ethanol extract of pharbitis nil (PNE) alleviates the liver fibrosis.

MATERIALS AND METHODS

We studied the effects of PNE on two preclinical models. Six-week-old male C57BL/6 mice were intraperitoneally injected with CCl₄ twice weekly for 6 weeks and then treated with 5 or 10 mg/kg PNE daily from week 3 for weeks. Secondly, mice were fed HFD for 41 weeks and at 35 weeks treated with 5 mg/kg PNE daily for the remaining 6 weeks. In addition, we examined the antifibrotic effects of PNE in primary mouse hepatic stellate cells and LX-2 cells.

RESULTS

PNE treatment ameliorated hepatocyte necrosis, inflammation, and liver fibrosis in CCl₄-treated mice and inhibited the progression of liver fibrosis in mice with HFD-induced fibrosis. PNE reduced the expressions of fibrosis markers and SMAD2/3 activations in mouse livers and in TGFβ1-treated primary mouse hepatic stellate and LX-2 cells CONCLUSIONS: This study demonstrates that PNE attenuates liver fibrosis by downregulating TGFβ1-induced SMAD2/3 activation.

Investigation of memory-enhancing effects of Streptococcus thermophilus EG007 in mice and elucidating molecular and metagenomic characteristics using nanopore sequencing

Over the past decades, accumulating evidences have highlighted the gut microbiota as a key player in the brain functioning via microbiota–gut–brain axis, and accordingly, the beneficial role of several probiotic strains in cognitive ability also have been actively investigated. However, the majority of the research have demonstrated the effects against age-related cognitive decline or neurological disease. To this end, we aimed to investigate lactic acid bacteria strains having beneficial effects on the cognitive function of healthy young mice and elucidate underlying characteristics by carrying out nanopore sequencing-based genomics and metagenomics analysis. 8-week consumption of Streptococcus thermophilus EG007 demonstrated marked enhancements in behavior tests assessing short-term spatial and non-spatial learning and memory. It was revealed that EG007 possessed genes encoding various metabolites beneficial for a health condition in many aspects, including gamma-aminobutyric acid producing system, a neurotransmitter associated with mood and stress response. Also, by utilizing 16S–23S rRNA operon as a taxonomic marker, we identified more accurate species-level compositional changes in gut microbiota, which was increase of certain species, previously reported to have associations with mental health or down-regulation of inflammation or infection-related species. Moreover, correlation analysis revealed that the EG007-mediated altered microbiota had a significant correlation with the memory traits.

Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system

CNS disorders are indications with a very high unmet medical needs, relatively smaller number of available drugs, and a subpar satisfaction level among patients and caregiver. Discovery of CNS drugs is extremely expensive affair with its own unique challenges leading to extremely high attrition rates and low efficiency. With explosion of data in information age, there is hardly any aspect of life that has not been touched by data driven technologies such as artificial intelligence (AI) and machine learning (ML). Drug discovery is no exception, emergence of big data via genomic, proteomic, biological, and chemical technologies has driven pharmaceutical giants to collaborate with AI oriented companies to revolutionise drug discovery, with the goal of increasing the efficiency of the process. In recent years many examples of innovative applications of AI and ML techniques in CNS drug discovery has been reported. Research on therapeutics for diseases such as schizophrenia, Alzheimer's and Parkinsonism has been provided with a new direction and thrust from these developments. AI and ML has been applied to both ligand-based and structure-based drug discovery and design of CNS therapeutics. In this review, we have summarised the general aspects of AI and ML from the perspective of drug discovery followed by a comprehensive coverage of the recent developments in the applications of AI/ML techniques in CNS drug discovery.

Increased/Targeted Brain (Pro)Drug Delivery via Utilization of Solute Carriers (SLCs)

Membrane transporters have a crucial role in compounds’ brain drug delivery. They allow not only the penetration of a wide variety of different compounds to cross the endothelial cells of the blood–brain barrier (BBB), but also the accumulation of them into the brain parenchymal cells. Solute carriers (SLCs), with nearly 500 family members, are the largest group of membrane transporters. Unfortunately, not all SLCs are fully characterized and used in rational drug design. However, if the structural features for transporter interactions (binding and translocation) are known, a prodrug approach can be utilized to temporarily change the pharmacokinetics and brain delivery properties of almost any compound. In this review, main transporter subtypes that are participating in brain drug disposition or have been used to improve brain drug delivery across the BBB via the prodrug approach, are introduced. Moreover, the ability of selected transporters to be utilized in intrabrain drug delivery is discussed. Thus, this comprehensive review will give insights into the methods, such as computational drug design, that should be utilized more effectively to understand the detailed transport mechanisms. Moreover, factors, such as transporter expression modulation pathways in diseases that should be taken into account in rational (pro)drug development, are considered to achieve successful clinical applications in the future.

Nanotherapeutics and the Brain

Brain disease remains a significant health, social, and economic burden with a high failure rate of translation of therapeutics to the clinic. Nanotherapeutics have represented a promising area of technology investment to improve drug bioavailability and delivery to the brain, with several successes for nanotherapeutic use for central nervous system disease that are currently in the clinic. However, renewed and continued research on the treatment of neurological disorders is critically needed. We explore the challenges of drug delivery to the brain and the ways in which nanotherapeutics can overcome these challenges. We provide a summary and overview of general design principles that can be applied to nanotherapeutics for uptake and penetration in the brain. We next highlight remaining questions that limit the translational potential of nanotherapeutics for application in the clinic. Lastly, we provide recommendations for ongoing preclinical research to improve the overall success of nanotherapeutics against neurological disease.

Targeting NMDA receptors in neuropsychiatric disorders by drug screening on human neurons derived from pluripotent stem cells

NMDA receptors (NMDARs), a prominent subtype of glutamatergic receptors, are implicated in the pathogenesis and development of neuropsychiatric disorders such as epilepsy, intellectual disability, autism spectrum disorder, and schizophrenia, and are therefore a potential therapeutic target in treating these disorders. Neurons derived from induced pluripotent stem cells (iPSCs) have provided the opportunity to investigate human NMDARs in their native environment. In this review, we describe the expression, function, and regulation of NMDARs in human iPSC-derived neurons and discuss approaches for utilizing human neurons for identifying potential drugs that target NMDARs in the treatment of neuropsychiatric disorders. A challenge in studying NMDARs in human iPSC-derived neurons is a predominance of those receptors containing the GluN2B subunit and low synaptic expression, suggesting a relatively immature phenotype of these neurons and delayed development of functional NMDARs. We outline potential approaches for improving neuronal maturation of human iPSC-derived neurons and accelerating the functional expression of NMDARs. Acceleration of functional expression of NMDARs in human iPSC-derived neurons will improve the modeling of neuropsychiatric disorders and facilitate the discovery and development of novel therapeutics targeting NMDARs for the treatment of these disorders.

Cholinergic models of memory impairment in animals and man: scopolamine vs. biperiden

Scopolamine has been used as a pharmacologic model for cognitive impairments in dementia and Alzheimer's disease. The validity of this model seems to be limited because findings in animals do not readily translate to novel treatments in humans. Biperiden is also a cholinergic deficit model for cognitive impairments but specifically blocks muscarinic M1 receptors. The effects of scopolamine and biperiden (and pirenzepine) are compared in animal studies and related to findings in humans. It is concluded that the effects on cognitive functions are different for scopolamine and biperiden, and they should be considered as different cognitive deficit models. Scopolamine may model more advanced stages of Alzheimer's disease whereas biperiden may model the early deficits in declarative memory in aging and mild cognitive impairment.

Brain somatic mutations as RNA therapeutic targets in neurological disorders

Research into the genetic etiology of a neurological disorder can provide directions for genetic diagnosis and targeted therapy. In the past, germline mutations, which are transmitted from parents or newly arise from parental germ cells, were considered as major genetic causes of neurological disorders. However, recent evidence has shown that somatic mutations in the brain, which can arise from neural stem cells during development or over aging, account for a significant number of brain disorders, ranging from neurodevelopmental, neurodegenerative, and neuropsychiatric to neoplastic disease. Moreover, the identification of disease-causing somatic mutations or mutated genes has provided new insights into molecular pathogenesis and unveiled potential therapeutic targets for treating neurological disorders that have few, or no, therapeutic options. RNA therapeutics, including antisense oligonucleotide (ASO) and small interfering RNA (siRNA), are emerging as promising therapeutic tools for treating genetic neurological disorders. As the number of approved and investigational ASO and siRNA drugs for neurological disorders associated with germline mutations increases, they may also prove to be attractive modalities for treating neurologic disorders resulting from somatic mutations. In this perspective, we highlight several neurological diseases caused by brain somatic mutations and discuss the potential role of RNA therapeutics in these conditions.

The druggable schizophrenia genome: from repurposing opportunities to unexplored drug targets

There have been no new drugs for the treatment of schizophrenia in several decades and treatment resistance represents a major unmet clinical need. The drugs that exist are based on serendipitous clinical observations rather than an evidence-based understanding of disease pathophysiology. In the present review, we address these bottlenecks by integrating common, rare, and expression-related schizophrenia risk genes with knowledge of the druggability of the human genome as a whole. We highlight novel drug repurposing opportunities, clinical trial candidates which are supported by genetic evidence, and unexplored therapeutic opportunities in the lesser-known regions of the schizophrenia genome. By identifying translational gaps and opportunities across the schizophrenia disease space, we discuss a framework for translating increasingly well-powered genetic association studies into personalized treatments for schizophrenia and initiating the vital task of characterizing clinically relevant drug targets in underexplored regions of the human genome.

Reconsidering animal models used to study autism spectrum disorder: Current state and optimizing future

Neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD) and intellectual disability (ID), are pervasive, often lifelong disorders, lacking evidence-based interventions for core symptoms. With no established biological markers, diagnoses are defined by behavioral criteria. Thus, preclinical in vivo animal models of NDDs must be optimally utilized. For this reason, experts in the field of behavioral neuroscience convened a workshop with the goals of reviewing current behavioral studies, reports, and assessments in rodent models. Goals included: (a) identifying the maximal utility and limitations of behavior in animal models with construct validity; (b) providing recommendations for phenotyping animal models; and (c) guidelines on how in vivo models should be used and reported reliably and rigorously while acknowledging their limitations. We concluded by recommending minimal criteria for reporting in manuscripts going forward. The workshop elucidated a consensus of potential solutions to several problems, including revisiting claims made about animal model links to ASD (and related conditions). Specific conclusions included: mice (or other rodent or preclinical models) are models of the neurodevelopmental insult, not specifically any disorder (e.g., ASD); a model that perfectly recapitulates a disorder such as ASD is untenable; and greater attention needs be given to validation of behavioral testing methods, data analysis, and critical interpretation.

Pharmacoproteomics of Brain Barrier Transporters and Substrate Design for the Brain Targeted Drug Delivery

One of the major reasons why central nervous system (CNS)-drug development has been challenging in the past, is the barriers that prevent substances entering from the blood circulation into the brain. These barriers include the blood-brain barrier (BBB), blood-spinal cord barrier (BSCB), blood-cerebrospinal fluid barrier (BCSFB), and blood-arachnoid barrier (BAB), and they differ from each other in their transporter protein expression and function as well as among the species. The quantitative expression profiles of the transporters in the CNS-barriers have been recently revealed, and in this review, it is described how they affect the pharmacokinetics of compounds and how these expression differences can be taken into account in the prediction of brain drug disposition in humans, an approach called pharmacoproteomics. In recent years, also structural biology and computational resources have progressed remarkably, enabling a detailed understanding of the dynamic processes of transporters. Molecular dynamics simulations (MDS) are currently used commonly to reveal the conformational changes of the transporters and to find the interactions between the substrates and the protein during the binding, translocation in the transporter cavity, and release of the substrate on the other side of the membrane. The computational advancements have also aided in the rational design of transporter-utilizing compounds, including prodrugs that can be actively transported without losing potency towards the pharmacological target. In this review, the state-of-art of these approaches will be also discussed to give insights into the transporter-mediated drug delivery to the CNS.

Access to Innovative Neurological Drugs in Europe: Alignment of Health Technology Assessments Among Three European Countries

Even for products centrally approved, each European country is responsible for national market access after European Medicines Agency (EMA) approval. This step can result in inequalities in terms of access, due to different opinions about the therapeutic value assessed by Health Technology Assessment (HTA) bodies. This study aims to provide a comparative analysis of HTA recommendations issued by EU countries (France, Germany, and Italy) for new neurological drugs following EMA approval. In the reference period, we identified 11 innovative medicines authorized in Europe for five neurological diseases (cerebral adrenoleukodystrophy, spinal muscular atrophy, metachromatic leukodystrophy, migraine, and polyneuropathy in patients with hereditary transthyretin amyloidosis), including eight drugs for genetic rare diseases. We found no agreement on the therapeutic value (in particular the “added value” compared to the standard of care) of the selected drugs. Despite the differences in terms of assessment, the access has been usually guaranteed even if with various types of limitations. The heterogeneity of the HTA assessment of clinical data among countries is probably related to the uncertainties about clinical value at the time of EMA approval and the lack of long-term data and of direct comparison with available alternatives. Given the importance of new medicines especially for rare diseases, it is crucial to understand and act on the causes of inconsistency among the HTA assessments, in order to ensure rapid and uniform access to innovation for patients who can benefit.

Organ on a Chip: A Novel in vitro Biomimetic Strategy in Amyotrophic Lateral Sclerosis (ALS) Modeling

Amyotrophic lateral sclerosis is a pernicious neurodegenerative disorder that is associated with the progressive degeneration of motor neurons, the disruption of impulse transmission from motor neurons to muscle cells, and the development of mobility impairments. Clinically, muscle paralysis can spread to other parts of the body. Hence it may have adverse effects on swallowing, speaking, and even breathing, which serves as major problems facing these patients. According to the available evidence, no definite treatment has been found for amyotrophic lateral sclerosis (ALS) that results in a significant outcome, although some pharmacological and non-pharmacological treatments are currently applied that are accompanied by some positive effects. In other words, available therapies are only used to relieve symptoms without any significant treatment effects that highlight the importance of seeking more novel therapies. Unfortunately, the process of discovering new drugs with high therapeutic potential for ALS treatment is fraught with challenges. The lack of a broad view of the disease process from early to late-stage and insufficiency of preclinical studies for providing validated results prior to conducting clinical trials are other reasons for the ALS drug discovery failure. However, increasing the combined application of different fields of regenerative medicine, especially tissue engineering and stem cell therapy can be considered as a step forward to develop more novel technologies. For instance, organ on a chip is one of these technologies that can provide a platform to promote a comprehensive understanding of neuromuscular junction biology and screen candidate drugs for ALS in combination with pluripotent stem cells (PSCs). The structure of this technology is based on the use of essential components such as iPSC- derived motor neurons and iPSC-derived skeletal muscle cells on a single miniaturized chip for ALS modeling. Accordingly, an organ on a chip not only can mimic ALS complexities but also can be considered as a more cost-effective and time-saving disease modeling platform in comparison with others. Hence, it can be concluded that lab on a chip can make a major contribution as a biomimetic micro-physiological system in the treatment of neurodegenerative disorders such as ALS.

Atomistic Model of Solute Transport across the Blood-Brain Barrier

The blood-brain barrier remains a major roadblock to the delivery of drugs to the brain. While in vitro and in vivo measurements of permeability are widely used to predict brain penetration, very little is known about the mechanisms of passive transport. Detailed insight into interactions between solutes and cell membranes could provide new insight into drug design and screening. Here, we perform unbiased atomistic MD simulations to visualize translocation of a library of 24 solutes across a lipid bilayer representative of brain microvascular endothelial cells. A temperature bias is used to achieve steady state of all solutes, including those with low permeability. Based on free-energy surface profiles, we show that the solutes can be classified into three groups that describe distinct mechanisms of transport across the bilayer. Simulations down to 310 K for solutes with fast permeability were used to justify the extrapolation of values at 310 K from higher temperatures. Comparison of permeabilities at 310 K to experimental values obtained from in vitro transwell measurements and in situ brain perfusion revealed that permeabilities obtained from simulations vary from close to the experimental values to more than 3 orders of magnitude faster. The magnitude of the difference was dependent on the group defined by free-energy surface profiles. Overall, these results show that MD simulations can provide new insight into the mechanistic details of brain penetration and provide a new approach for drug discovery.

High-content analysis and Kinetic Image Cytometry identify toxicity and epigenetic effects of HIV antiretrovirals on human iPSC-neurons and primary neural precursor cells

INTRODUCTION

Despite viral suppression due to combination antiretroviral therapy (cART), HIV-associated neurocognitive disorders (HAND) continue to affect half of people with HIV, suggesting that certain antiretrovirals (ARVs) may contribute to HAND.

METHODS

We examined the effects of nucleoside/nucleotide reverse transcriptase inhibitors tenofovir disoproxil fumarate (TDF) and emtricitabine (FTC) and the integrase inhibitors dolutegravir (DTG) and elvitegravir (EVG) on viability, structure, and function of glutamatergic neurons (a subtype of CNS neuron involved in cognition) derived from human induced pluripotent stem cells (hiPSC-neurons), and primary human neural precursor cells (hNPCs), which are responsible for neurogenesis.

RESULTS

Using automated digital microscopy and image analysis (high content analysis, HCA), we found that DTG, EVG, and TDF decreased hiPSC-neuron viability, neurites, and synapses after 7 days of treatment. Analysis of hiPSC-neuron calcium activity using Kinetic Image Cytometry (KIC) demonstrated that DTG and EVG also decreased the frequency and magnitude of intracellular calcium transients. Longer ARV exposures and simultaneous exposure to multiple ARVs increased the magnitude of these neurotoxic effects. Using the Microscopic Imaging of Epigenetic Landscapes (MIEL) assay, we found that TDF decreased hNPC viability and changed the distribution of histone modifications that regulate chromatin packing, suggesting that TDF may reduce neuroprogenitor pools important for CNS development and maintenance of cognition in adults.

CONCLUSION

This study establishes human preclinical assays that can screen potential ARVs for CNS toxicity to develop safer cART regimens and HAND therapeutics.

Existing Drug Repurposing for Glioblastoma to Discover Candidate Drugs as a New a Approach

Aims:

Repurposing of drugs has been hypothesized as a means of identifying novel treatment methods for certain diseases.

Background:

Glioblastoma (GB) is an aggressive type of human cancer; the most effective treatment for glioblastoma is chemotherapy, whereas, when repurposing drugs, a lot of time and money can be saved.

Objective:

Repurposing of the existing drug may be used to discover candidate drugs for individualized treatments of GB.

Method:

We used the bioinformatics method to obtain the candidate drugs. In addition, the drugs were verified by MTT assay, Transwell® assays, TUNEL staining, and in vivo tumor formation experiments, as well as statistical analysis.

Result:

We obtained 4 candidate drugs suitable for the treatment of glioma, camptothecin, doxorubicin, daunorubicin and mitoxantrone, by the expression spectrum data IPAS algorithm analysis and drug-pathway connectivity analysis. These validation experiments showed that camptothecin was more effective in treating the GB, such as MTT assay, Transwell® assays, TUNEL staining, and in vivo tumor formation.

Conclusion:

With regard to personalized treatment, this present study may be used to guide the research of new drugs via verification experiments and tumor formation. The present study also provides a guide to systematic, individualized drug discovery for complex diseases and may contribute to the future application of individualized treatments.

Helpful Lessons and Cautionary Tales: How Should COVID-19 Drug Development and Access Inform Approaches to Non-Pandemic Diseases?

After witnessing extraordinary scientific and regulatory efforts to speed development of and access to new COVID-19 interventions, patients facing other serious diseases have begun to ask "where's our Operation Warp Speed?" and "why isn't Emergency Use Authorization an option for our health crises?" Although this pandemic bears a number of unique features, the response to COVID-19 offers translatable lessons, in both its successes and failures, for non-pandemic diseases. These include the importance of collaborating across sectors, supporting the highest-priority research efforts, adopting rigorous and innovative trial designs, and sharing reliable information quickly. In addition, the regulatory response to the pandemic demonstrates that lowering standards for marketing authorization can result in increased safety concerns, missed opportunities for research and treatment, and delays in determining what works. Accordingly, policymakers and patient advocates seeking to build on the COVID-19 experience for non-pandemic diseases with unmet treatment needs should focus their efforts on promoting robust and efficient research designs, improving access to clinical trials, and facilitating use of the Food and Drug Administration's existing Expanded Access pathway.

CRISPR-Cas9-Mediated Gene Therapy in Neurological Disorders

Neurological disorders are primarily diseases with sophisticated etiology that are always refractory and recrudescent. The major obstruction to effective therapies for neurological disorders is the poor understanding of their pathogenic mechanisms. CRISPR-Cas9 technology, which allows precise and effective gene editing in almost any cell type and organism, is accelerating the pace of basic biological research. An increasing number of groups are focusing on uncovering the molecular mechanisms of neurological disorders and developing novel therapies using the CRISPR-Cas9 system. This review highlights the application of CRISPR-Cas9 technology in the treatment of neurological disorders, including Alzheimer's disease, amyotrophic lateral sclerosis and/or frontotemporal dementia, Duchenne muscular dystrophy, Dravet syndrome, epilepsy, Huntington's disease, and Parkinson's disease. Hopefully, it will improve our understanding of neurological disorders and give insights into future treatments for neurological disorders.

Modelling the central nervous system: tissue engineering of the cellular microenvironment

With the increasing prevalence of neurodegenerative diseases, improved models of the central nervous system (CNS) will improve our understanding of neurophysiology and pathogenesis, whilst enabling exploration of novel therapeutics. Studies of brain physiology have largely been carried out using in vivo models, ex vivo brain slices or primary cell culture from rodents. Whilst these models have provided great insight into complex interactions between brain cell types, key differences remain between human and rodent brains, such as degree of cortical complexity. Unfortunately, comparative models of human brain tissue are lacking. The development of induced Pluripotent Stem Cells (iPSCs) has accelerated advancement within the field of in vitro tissue modelling. However, despite generating accurate cellular representations of cortical development and disease, two-dimensional (2D) iPSC-derived cultures lack an entire dimension of environmental information on structure, migration, polarity, neuronal circuitry and spatiotemporal organisation of cells. As such, researchers look to tissue engineering in order to develop advanced biomaterials and culture systems capable of providing necessary cues for guiding cell fates, to construct in vitro model systems with increased biological relevance. This review highlights experimental methods for engineering of in vitro culture systems to recapitulate the complexity of the CNS with consideration given to previously unexploited biophysical cues within the cellular microenvironment.

Electrophysiological- and Neuropharmacological-Based Benchmarking of Human Induced Pluripotent Stem Cell-Derived and Primary Rodent Neurons

Human induced pluripotent stem cell (iPSC)-derived neurons are of interest for studying neurological disease mechanisms, developing potential therapies and deepening our understanding of the human nervous system. However, compared to an extensive history of practice with primary rodent neuron cultures, human iPSC-neurons still require more robust characterization of expression of neuronal receptors and ion channels and functional and predictive pharmacological responses. In this study, we differentiated human amniotic fluid-derived iPSCs into a mixed population of neurons (AF-iNs). Functional assessments were performed by evaluating electrophysiological (patch-clamp) properties and the effect of a panel of neuropharmacological agents on spontaneous activity (multi-electrode arrays; MEAs). These electrophysiological data were benchmarked relative to commercially sourced human iPSC-derived neurons (CNS.4U from Ncardia), primary human neurons (ScienCell™) and primary rodent cortical/hippocampal neurons. Patch-clamp whole-cell recordings showed that mature AF-iNs generated repetitive firing of action potentials in response to depolarizations, similar to that of primary rodent cortical/hippocampal neurons, with nearly half of the neurons displaying spontaneous post-synaptic currents. Immunochemical and MEA-based analyses indicated that AF-iNs were composed of functional glutamatergic excitatory and inhibitory GABAergic neurons. Principal component analysis of MEA data indicated that human AF-iN and rat neurons exhibited distinct pharmacological and electrophysiological properties. Collectively, this study establishes a necessary prerequisite for AF-iNs as a human neuron culture model suitable for pharmacological studies.