Drug Safety Evaluation Research Articles

Ventricular voltage-gated ion channels: Detection, characteristics, mechanisms, and drug safety evaluation.

Cardiac voltage‐gated ion channels (VGICs) play critical roles in mediating cardiac electrophysiological signals, such as action potentials, to maintain normal heart excitability and contraction. Inherited or acquired alterations in the structure, expression, or function of VGICs, as well as VGIC‐related side effects of pharmaceutical drug delivery can result in abnormal cellular electrophysiological processes that induce life‐threatening cardiac arrhythmias or even sudden cardiac death. Hence, to reduce possible heart‐related risks, VGICs must be acknowledged as important targets in drug discovery and safety studies related to cardiac disease. In this review, we first summarize the development and application of electrophysiological techniques that are employed in cardiac VGIC studies alone or in combination with other techniques such as cryoelectron microscopy, optical imaging and optogenetics. Subsequently, we describe the characteristics, structure, mechanisms, and functions of various well‐studied VGICs in ventricular myocytes and analyze their roles in and contributions to both physiological cardiac excitability and inherited cardiac diseases. Finally, we address the implications of the structure and function of ventricular VGICs for drug safety evaluation. In summary, multidisciplinary studies on VGICs help researchers discover potential targets of VGICs and novel VGICs in heart, enrich their knowledge of the properties and functions, determine the operation mechanisms of pathological VGICs, and introduce groundbreaking trends in drug therapy strategies, and drug safety evaluation.

Combining human-based in silico and in vitro models of inherited cardiac diseases for drug safety and efficacy evaluation

Combining human-based in silico and in vitro models of inherited cardiac diseases for drug safety and efficacy evaluation

웨어러블 기기를 위한 광혈류 데이터 기반 혈압 측정 하이브리드 딥러닝 시스템의 구축

In this work, we developed a PPG-based blood pressure estimation hybrid deep learning model built into wearable devices and used by hypertension patients to monitor blood pressure in real-time in their daily lives. The model is a deep-learning model that combines data preprocessing, Autoencoder deep learning model for feature extraction, and RAN regression model developed by this research team. We conducted experiments to compare the blood pressure prediction performance of the proposed model with other deep learning models and find out how the objective blood pressure prediction performance is. We conducted experiments on an open dataset with the vital signs of 32 subjects. After models trained on 24 subjects’ data and are tested on eight other people’s data, we could see that using deep-learning regression models combined with an Autoencoder (hybrid deep-learning) performs better than using a deep learning model alone, and RAN accurately predicts blood pressure than the comparable deep-learning models. The study found that the average error for actual and predicted blood pressure in the proposed hybrid deep-learning models was 4.67 mmHg, and the standard deviation of error was 6.37 mmHg. It satisfies the accuracy criteria presented by the Korean National Institute of Food and Drug Safety Evaluation.

Incidence of completed suicide and suicide attempts in a global prospective study of Huntington's disease.

Risk of death from suicide in Huntington's disease is notably elevated relative to that in the general population, although the incidence within HD populations has not been precisely defined. Robust incidence estimates of suicidal behavior can serve as references for HD therapeutic research and post-marketing surveillance to help evaluate the suicidality risk of novel therapeutics. To estimate the incidence rate of completed suicide and suicide attempt in the global, prospective HD cohort study Enroll-HD that records these events per protocol. A total of 20 912 participants were available for analysis (HD gene-expansion carriers (HDGECs) n = 15 924; non-HDGECs n = 4988) representing a collective observation period of 53 390 participant-years. Each observed event was subject to clinical review and evaluation. We generated incidence rates (events per 100 000 person-years) for suicides and suicide attempts using all available data, as well as by year of study and geographical region. Proportionate mortality statistics for suicide and respective 95% confidence intervals were also generated. The overall incidence rate of suicide in HDGECs was 72 per 100 000 person-years, and 8 per 100 000 person-years in non-HDGECs. Proportionate mortality attributable to suicide in HDGECs was 4.6%. For suicide attempts, the global overall incidence rate observed in HDGECs was 306-375 per 100 000 person-years, and 23-38 per 100 000 person-years in non-HDGECs. The incidence estimates calculated here can be used as a reference to help evaluate drug safety and may also be useful in assessing progress in clinical care for HDGECs once therapeutic interventions become widely available.

Detection algorithms and attentive points of safety signal using spontaneous reporting systems as a clinical data source.

Continuous evaluation of drug safety is needed following approval to determine adverse events (AEs) in patient populations with diverse backgrounds. Spontaneous reporting systems are an important source of information for the detection of AEs not identified in clinical trials and for safety assessments that reflect the real-world use of drugs in specific populations and clinical settings. The use of spontaneous reporting systems is expected to detect drug-related AEs early after the launch of a new drug. Spontaneous reporting systems do not contain data on the total number of patients that use a drug; therefore, signal detection by disproportionality analysis, focusing on differences in the ratio of AE reports, is frequently used. In recent years, new analyses have been devised, including signal detection methods focused on the difference in the time to onset of an AE, methods that consider the patient background and those that identify drug-drug interactions. However, unlike commonly used statistics, the results of these analyses are open to misinterpretation if the method and the characteristics of the spontaneous reporting system cannot be evaluated properly. Therefore, this review describes signal detection using data mining, considering traditional methods and the latest knowledge, and their limitations.

Sex Differences in Drug-Induced Arrhythmogenesis.

The electrical activity in the heart varies significantly between men and women and results in a sex-specific response to drugs. Recent evidence suggests that women are more than twice as likely as men to develop drug-induced arrhythmia with potentially fatal consequences. Yet, the sex-specific differences in drug-induced arrhythmogenesis remain poorly understood. Here we integrate multiscale modeling and machine learning to gain mechanistic insight into the sex-specific origin of drug-induced cardiac arrhythmia at differing drug concentrations. To quantify critical drug concentrations in male and female hearts, we identify the most important ion channels that trigger male and female arrhythmogenesis, and create and train a sex-specific multi-fidelity arrhythmogenic risk classifier. Our study reveals that sex differences in ion channel activity, tissue conductivity, and heart dimensions trigger longer QT-intervals in women than in men. We quantify the critical drug concentration for dofetilide, a high risk drug, to be seven times lower for women than for men. Our results emphasize the importance of including sex as an independent biological variable in risk assessment during drug development. Acknowledging and understanding sex differences in drug safety evaluation is critical when developing novel therapeutic treatments on a personalized basis. The general trends of this study have significant implications on the development of safe and efficacious new drugs and the prescription of existing drugs in combination with other drugs.

27880 Differences in pediatric vs adult clinical trial designs for atopic dermatitis

Despite an increasing burden of atopic dermatitis (AD) in all ages, the distribution of participant age and trial characteristics remains unelucidated. The aim of this study was to compare trial characteristics between pediatric and adult AD trials. We collected data from ClinicalTrials.gov on AD therapeutic trials completed between 2003-2019 and further stratified trials by pediatrics (mean or median age <18 years of the experimental group participants) or adults. Trials without results on ClinicalTrials.gov were searched on PubMed. Exclusion criteria include non-pharmacologic trials or those without published data on ClinicalTrials.gov or PubMed as of April 30, 2020. Of 210 trials, 50 (24%) were pediatric trials [mean age: 8.2 ± 4.3 years (SD)] and 160 (76%) were adult trials [mean age 35.2 ± 5.7 years (SD)]. Pediatric and adult trials were equally likely randomized controlled trials; however, pediatric trials were more likely open label trials (P ˂ .001) and have no comparator (P ˂ .001). Adult trials were more likely industry funded (95% vs 80%, P = .001). Any evaluation of drug safety was more likely present in adult trials (83% vs 60%, P = .001). In trials examining AD severity as an outcome, Eczema Area and Severity Index (EASI) predominated in adult trials (51% vs 29%, P ˂ .05) and SCORing Atopic Dermatitis (SCORAD) in pediatric trials (25% vs 10%, P ˂ .05). The results suggest differences in trial design between pediatric and adult AD trials and also show the lack of trial standardization in trial design.

Comparison of intrinsic exercise capacity and response to acute exercise in ICR (Institute of Cancer Research) mice derived from three different lineages

BackgroundAs a laboratory animal resource, the ICR mouse is commonly used in a variety of research fields. However, information on differences in exercise-related characteristics in ICR mice derived from different lineages and the underlying mechanisms remains to be elucidated. In this study, we investigated the intrinsic exercise capacity and a magnitude of response to acute exercise, and sought to identify mechanisms contributing to difference in Korl:ICR (a novel ICR lineage recently established by the National Institute of Food and Drug Safety Evaluation, Korea) and two commercialized ICR lineages derived from different origins (viz., A:ICR mouse from Orient Bio Com, the United States, and B:ICR mouse from Japan SLC Inc., Japan).ResultsResults showed that despite no significant difference in body weight and weight-proportioned tissue mass of heart and skeletal muscles among groups, the relatively low intrinsic exercise capacity and exaggerated response to acute exercise were identified in B:ICR comparted with Korl:ICR and A:ICR, as reflected by total work and lactate threshold (LT). Also, the mitochondrial efficiency expressed as the complex 1 and complex 1 + 2 respiratory control ratio (RCR) values for cardiac mitochondrial O2 consumption in B:ICR was significantly lower than that in Korl:ICR with higher level of state 2 respiration by glutamate/malate and UCP3 expression in cardiac muscle.ConclusionsTaken together, these results indicate that the intrinsic exercise capacity of ICR mouse varies according to lineages, suggesting the role of cardiac mitochondrial coupling efficiency as a possible mechanism that might contribute to differences in the intrinsic exercise capacity and magnitude of response to exercise.

Sensitive assay design for detection of anti-drug antibodies to biotherapeutics that lack an immunoglobulin Fc domain

Today the evaluation of unwanted immunogenicity is a key component in the clinical safety evaluation of new biotherapeutic drugs and macromolecular delivery strategies. However, the evolving structural complexity in contemporary biotherapeutics creates a need for on-going innovation in assay designs for reliable detection of anti-drug antibodies, especially for biotherapeutics that may not be well-suited for testing by a bridging assay. We, therefore, initiated systematic optimization of the direct binding assay to adapt it for routine use in regulatory-compliant assays of serum anti-drug antibodies. Accordingly, we first prepared a SULFO-TAG labeled conjugate of recombinant Protein-A/G to create a sensitive electrochemiluminescent secondary detection reagent with broad reactivity to antibodies across many species. Secondly, we evaluated candidate blocker-diluents to identify ones producing the highest signal-to-noise response ratios. Lastly, we introduced use of the ratio of signal responses in biotherapeutic-coated and uncoated wells as a data transformation strategy to identify biological outliers. This alternative data normalization approach improved normality, reduced skewness, and facilitated application of a parametric screening cut point. We believe the optimized direct binding assay design employing SULFO-TAG labeled Protein-A/G represents a useful analytical design for detecting serum ADA to biotherapeutics that lack an immunoglobulin Fc domain.

Kidney Organoid and Microphysiological Kidney Chip Models to Accelerate Drug Development and Reduce Animal Testing.

Kidneys are critical for the elimination of many drugs and metabolites via the urine, filtering waste and maintaining proper fluid and electrolyte balance. Emerging technologies incorporating engineered three-dimensional (3D) in vitro cell culture models, such as organoids and microphysiological systems (MPS) culture platforms, have been developed to replicate nephron function, leading to enhanced efficacy, safety, and toxicity evaluation of new drugs and environmental exposures. Organoids are tiny, self-organized three-dimensional tissue cultures derived from stem cells that can include dozens of cell types to replicate the complexity of an organ. In contrast, MPS are highly controlled fluidic culture systems consisting of isolated cell type(s) that can be used to deconvolute mechanism and pathophysiology. Both systems, having their own unique benefits and disadvantages, have exciting applications in the field of kidney disease modeling and therapeutic discovery and toxicology. In this review, we discuss current uses of both hPSC-derived organoids and MPS as pre-clinical models for studying kidney diseases and drug induced nephrotoxicity. Examples such as the use of organoids to model autosomal dominant polycystic kidney disease, and the use of MPS to predict renal clearance and nephrotoxic concentrations of novel drugs are briefly discussed. Taken together, these novel platforms allow investigators to elaborate critical scientific questions. While much work needs to be done, utility of these 3D cell culture technologies has an optimistic outlook and the potential to accelerate drug development while reducing the use of animal testing.

Application Scope of Real-World Data in Post-Marketing Drug Safety Monitoring and Evaluation for Drug Safety

Application Scope of Real-World Data in Post-Marketing Drug Safety Monitoring and Evaluation for Drug Safety

Liver-Heart on chip models for drug safety.

Current pre-clinical models to evaluate drug safety during the drug development process (DDP) mainly rely on traditional two-dimensional cell cultures, considered too simplistic and often ineffective, or animal experimentations, which are costly, time-consuming, and not truly representative of human responses. Their clinical translation thus remains limited, eventually causing attrition and leading to high rates of failure during clinical trials. These drawbacks can be overcome by the recently developed Organs-on-Chip (OoC) technology. OoC are sophisticated in vitro systems capable of recapitulating pivotal architecture and functionalities of human organs. OoC are receiving increasing attention from the stakeholders of the DDP, particularly concerning drug screening and safety applications. When a drug is administered in the human body, it is metabolized by the liver and the resulting compound may cause unpredicted toxicity on off-target organs such as the heart. In this sense, several liver and heart models have been widely adopted to assess the toxicity of new or recalled drugs. Recent advances in OoC technology are making available platforms encompassing multiple organs fluidically connected to efficiently assess and predict the systemic effects of compounds. Such Multi-Organs-on-Chip (MOoC) platforms represent a disruptive solution to study drug-related effects, which results particularly useful to predict liver metabolism on off-target organs to ultimately improve drug safety testing in the pre-clinical phases of the DDP. In this review, we focus on recently developed liver and heart on chip systems for drug toxicity testing. In addition, MOoC platforms encompassing connected liver and heart tissues have been further reviewed and discussed.

Key Characteristics of Human Hepatotoxicants as a Basis for Identification and Characterization of the Causes of Liver Toxicity.

Hazard identification regarding adverse effects on the liver is a critical step in safety evaluations of drugs and other chemicals. Current testing paradigms for hepatotoxicity rely heavily on preclinical studies in animals and human data (epidemiology and clinical trials). Mechanistic understanding of the molecular and cellular pathways that may cause or exacerbate hepatotoxicity is well advanced and holds promise for identification of hepatotoxicants. One of the challenges in translating mechanistic evidence into robust decisions about potential hepatotoxicity is the lack of a systematic approach to integrate these data to help identify liver toxicity hazards. Recently, marked improvements were achieved in the practice of hazard identification of carcinogens, female and male reproductive toxicants, and endocrine disrupting chemicals using the key characteristics approach. Here, we describe the methods by which key characteristics of human hepatotoxicants were identified and provide examples for how they could be used to systematically identify, organize, and use mechanistic data when identifying hepatotoxicants.

Differences in pediatric versus adult clinical trial characteristics for atopic dermatitis.

Atopic dermatitis (AD) is a growing burden in all ages. The aim of this study was to compare trial characteristics between pediatric and adult AD trials. Data were collected from ClinicalTrials.gov on AD therapeutic trials completed between 2003 and 2019. The trials were classified as pediatrics (mean or median age <18years of the experimental group participants) or adults. The trials with and without results on ClinicalTrials.gov were searched on PubMed for further data collection. Of 210 trials, 50 (24%) were pediatric trials [mean age: 8.2±4.3years (SD)] and 160 (76%) were adult trials [mean age 35.2±5.7years (SD)]. Pediatric and adult trials were equally likely to be randomized controlled trials; however, pediatric trials were more likely to be open-label trials (P<.001) and have no comparator (P<.001). Adult trials were more likely to be industry-funded (95% vs. 80%, P=.001). Any evaluation of drug safety was more likely present in adult trials (83% vs. 60%, P=.001). In trials examining AD severity as an outcome, the Eczema Area and Severity Index (EASI) predominated in adult trials (51% vs. 29%, P<.05) and Scoring Atopic Dermatitis (SCORAD) in pediatric trials (25% vs. 10%, P<.05). The results highlight differences in trial design between pediatric and adult AD trials and show a lack of standardization in trial design.

Study design criteria for regulatory-based drug control action: Drug discrimination

This “methods paper” focusses on one specific and limited aspect of drug safety evaluations required for all new drug entities that affect the central nervous system – the drug discrimination (DD) assay. We focus on three critical factors involved in experimental design and protocol development for the conduct of DD studies for abuse liability risk assessment that comply with the Good Laboratory Practice Guidelines (GLPs). The selection of 1) the reference drug(s) choice, 2) training dose selection, and 3) the selected route-of-administration will determine the applicability of the data to meet the regulatory expectations of the 8-factors determinative of schedule control recommendations. The study conduct and resulting data submission to the FDA are intended for drug scheduling review by the Controlled Substances Staff in the Center for Drug Evaluation and Research (CDER) at the US Food & Drug Administration (FDA). These animal studies are required to meet the statutory requirements of the Controlled Substances Act of 1970. The abuse liability study is conducted during Phase II and III of human clinical trials. Procedural or method-based errors this late in drug development can result in a significant economic and business threat to the program.

A drug safety evaluation of enzalutamide to treat advanced prostate cancer

ABSTRACT Introduction Prostate cancer (PC) is the most common cancer in North American men. Advanced PC is incurable. The androgen receptor antagonist enzalutamide is used to manage advanced PC, often over a period of months or years; it is therefore important to evaluate the safety profile of enzalutamide. Areas covered This literature review presents safety data from pivotal trials and real-world data studies of enzalutamide in patients with advanced PC, including metastatic hormone-sensitive prostate cancer (mHSPC), nonmetastatic castration-resistant prostate cancer (nmCRPC), and metastatic castration-resistant prostate cancer (mCRPC). A large body of evidence supports the maintenance or improvement in the health-related quality of life (HRQoL) afforded by enzalutamide treatment in patients with mHSPC, nmCRPC, or chemotherapy-naïve mCRPC, as well as improvement in the HRQoL in patients with later-stage symptomatic mCRPC. Efficacy data from clinical trials are also briefly discussed. Expert opinion We aim to provide clinicians with a better understanding of how to properly interpret enzalutamide clinical trial safety data. This knowledge may help clinicians guide their patients with PC to achieve optimal clinical benefit from enzalutamide therapy, and to properly manage their patients to mitigate any potential risk.

Human Pluripotent Stem-Cell-Derived Models as a Missing Link in Drug Discovery and Development.

Human pluripotent stem cells (hPSCs), including human embryonic stem cells (hESCs) and human-induced pluripotent stem cells (hiPSCs), have the potential to accelerate the drug discovery and development process. In this review, by analyzing each stage of the drug discovery and development process, we identified the active role of hPSC-derived in vitro models in phenotypic screening, target-based screening, target validation, toxicology evaluation, precision medicine, clinical trial in a dish, and post-clinical studies. Patient-derived or genome-edited PSCs can generate valid in vitro models for dissecting disease mechanisms, discovering novel drug targets, screening drug candidates, and preclinically and post-clinically evaluating drug safety and efficacy. With the advances in modern biotechnologies and developmental biology, hPSC-derived in vitro models will hopefully improve the cost-effectiveness and the success rate of drug discovery and development.

Visual analysis of research progress of Sophorae Tonkinensis Radix et Rhizoma based on CiteSpace

To analyze the study advance of Sophorae Tonkinensis Radix et Rhizoma, this study utilized CiteSpace 5.6.R5 software to conduct bibliometrics analysis on the Chinese literatures of Sophorae Tonkinensis Radix et Rhizoma from 1990 to 2020 included in the CNKI database retrieval platform. The analysis contents involved the number of published papers, co-authors, cooperative institutions, emergence, co-occurrence and clustering of keywords. A total of 808 Chinese literatures were included in the study, of which 17 were published by SUN Rong, the author with the most published papers, and formed a research team centered on SUN Rong; the analysis of the cooperation of publishing institutions showed that the Drug Safety Evaluation Research Center, Shanghai University of Traditional Chinese Medicine was the organization with the largest number of publications, with a total of 29 articles. It also formed a scientific research coorperation institution with Shandong Academy of Traditional Chinese Medicine as the core, and formed a relatively close cooperative network relationship. The analysis of literature keywords showed that the research direction was concentrated on the traditional Chinese medicine of Sophorae Tonkinensis Radix et Rhizoma, pharmacological mechanism, and side effects, active ingredients, etc. Among them, the research on the efficacy and toxicity of the active ingredients of Sophorae Tonkinensis Radix et Rhizoma has become a hot trend.

A survey for Management of Drug Safety Evaluation System for Investigational Product

A survey for Management of Drug Safety Evaluation System for Investigational Product

A nanosensor for precise discrimination of nephrotoxic drug mechanisms via dynamic fluorescence fingerprint strategy

Drug-induced kidney injury causes structural or functional abnormalities of kidney, seriously affecting clinical practice and drug discovery. However, rapid and effective identification of nephrotoxic drug mechanisms is yet a challenging task arising from the complexity and diversity of various nephrotoxic mechanisms. Herein, we have constructed a polydopamine-polyethyleneimine/quantum dots sensor to instantaneously read out the nephrotoxic drugs mechanisms based on the disparate cell surface phenotypes. Cell surface components induced by multiple nephrotoxic drugs can change the fluorescence emission of multicolor quantum dots, generating their corresponding fluorescent fingerprints. The fluorescence response signatures induced by different nephrotoxic agents are gained with 84% accuracy via linear discriminant analysis. Furthermore, taking the time-toxicity relationship into consideration, dynamic fluorescent fingerprint is obtained through continuous monitoring the progress of renal cell damage, achieving 100% precise classification for nephrotoxic mechanisms of four types of antibiotics. Notably, the fluorescent fingerprint-based high-throughput sensor has been demonstrated by successfully distinguishing nephrotoxic drugs in seconds, employing a promising protocol to discriminate the specific mechanism of nephrotoxic drugs, as well as drug safety evaluation.