Urinary MicroRNA Biomarkers of Nephrotoxicity in Macaca fascicularis.

Drug-induced kidney injury (DIKI) refers to kidney damage resulting from the administration of medications. The aim of this project was to identify reliable urinary microRNA (miRNAs) biomarkers that can be used as potential predictors of DIKI before disease diagnosis. This study quantified a panel of six miRNAs (miRs-210-3p, 423-5p, 143-3p, 130b-3p, 486-5p, 193a-3p) across multiple time points using urinary samples from a previous investigation evaluating effects of a nephrotoxicant in cynomolgus monkeys. Exosome-associated miRNA exhibited distinctive trends when compared to miRNAs quantified in whole urine, which may reflect a different urinary excretion mechanism of miRNAs than those released passively into the urine. Although further research and mechanistic studies are required to elucidate how these miRNAs regulate signaling in disease pathways, we present, for the first time, data that several miRNAs displayed strong correlations with histopathology scores, thus indicating their potential use as biomarkers to predict the development of DIKI in preclinical studies and clinical trials. Also, these findings can potentially be translated into other non-clinical species or human for the detection of DIKI.

Challenging the status quo: a framework for mechanistic and human-relevant cardiovascular safety screening.

Traditional approaches to preclinical drug safety assessment have generally protected human patients from unintended adverse effects. However, these assessments typically occur too late to make changes in the formulation or in phase 1 and beyond, are highly dependent on animal studies and have the potential to lead to the termination of useful drugs due to liabilities in animals that are not applicable in patients. Collectively, these elements come at great detriment to both patients and the drug development sector. This phenomenon is particularly problematic in the area of cardiovascular safety assessment where preclinical attrition is high. We believe that a more efficient and translational approach can be defined. A multi-tiered assessment that leverages our understanding of human cardiovascular biology, applies human cell-based in vitro characterizations of cardiovascular responses to insult, and incorporates computational models of pharmacokinetic relationships would enable earlier and more translational identification of human-relevant liabilities. While this will take time to develop, the ultimate goal would be to implement such assays both in the lead selection phase as well as through regulatory phases.

A (not) new Rx: Quality Improvement for NAM.

New Approach Methodologies (NAMs) are a rapidly growing set of tools/methods for use food, drug, consumer product, or chemical safety assessment paradigms. The massive growth in NAMs tech development, publication, and legislation has been paralleled by a growing sense of frustration. The challenge of realizing the systems-level changes needed to catalyze the broad-scale adoption and use of NAMs is substantial. This Commentary asserts that these challenges may be less unique than perceived to date, and points to specific opportunities to learn from decades of experience (both positive and negative) from the Quality Improvement (QI) movement in the public health and healthcare arenas. Specific recommendations to inform and guide NAMs development are offered.

Potential pharmacokinetic interactions with concurrent use of herbal medicines and a ritonavir-boosted COVID-19 protease inhibitor in low and middle-income countries.

The COVID-19 pandemic sparked the development of novel anti-viral drugs that have shown to be effective in reducing both fatality and hospitalization rates in patients with elevated risk for COVID-19 related morbidity or mortality. Currently, nirmatrelvir/ritonavir (Paxlovid™) fixed-dose combination is recommended by the World Health Organization for treatment of COVID-19. The ritonavir component is an inhibitor of cytochrome P450 (CYP) 3A, which is used in this combination to achieve needed therapeutic concentrations of nirmatrelvir. Because of the critical pharmacokinetic effect of this mechanism of action for Paxlovid™, co-administration with needed medications that inhibit or induce CYP3A is contraindicated, reflecting concern for interactions with the potential to alter the efficacy or safety of co-administered drugs that are also metabolized by CYP3A. Some herbal medicines are known to interact with drug metabolizing enzymes and transporters, including but not limited to inhibition or induction of CYP3A and P-glycoprotein. As access to these COVID-19 medications has increased in low- and middle-income countries (LMICs), understanding the potential for herb-drug interactions within these regions is important. Many studies have evaluated the utility of herbal medicines for COVID-19 treatments, yet information on potential herb-drug interactions involving Paxlovid™, specifically with herbal medicines commonly used in LMICs, is lacking. This review presents data on regionally-relevant herbal medicine use (particularly those promoted as treatments for COVID-19) and mechanism of action data on herbal medicines to highlight the potential for herbal medicine interaction Herb-drug interaction mediated by ritonavir-boosted antiviral protease inhibitors This work highlights potential areas for future experimental studies and data collection, identifies herbal medicines for inclusion in future listings of regionally diverse potential HDIs and underscores areas for LMIC-focused provider-patient communication. This overview is presented to support governments and health protection entities as they prepare for an increase of availability and use of Paxlovid™.

Integrated Genotoxicity Testing of three anti-infective drugs using the TGx-DDI transcriptomic biomarker and high-throughput CometChip® assay in TK6 cells.

Genotoxicity testing relies on the detection of gene mutations and chromosome damage and has been used in the genetic safety assessment of drugs and chemicals for decades. However, the results of standard genotoxicity tests are often difficult to interpret due to lack of mode of action information. The TGx-DDI transcriptomic biomarker provides mechanistic information on the DNA damage-inducing (DDI) capability of chemicals to aid in the interpretation of positive in vitro genotoxicity data. The CometChip® assay was developed to assess DNA strand breaks in a higher-throughput format. We paired the TGx-DDI biomarker with the CometChip® assay in TK6 cells to evaluate three model agents: nitrofurantoin (NIT), metronidazole (MTZ), and novobiocin (NOV). TGx-DDI was analyzed by two independent labs and technologies (nCounter® and TempO-Seq®). Although these anti-infective drugs are, or have been, used in human and/or veterinary medicine, the standard genotoxicity testing battery showed significant genetic safety findings. Specifically, NIT is a mutagen and causes chromosome damage, and MTZ and NOV cause chromosome damage in conventional in vitro tests. Herein, the TGx-DDI biomarker classified NIT and MTZ as non-DDI at all concentrations tested, suggesting that NIT's mutagenic activity is bacterial specific and that the observed chromosome damage by MTZ might be a consequence of in vitro test conditions. In contrast, NOV was classified as DDI at the second highest concentration tested, which is in line with the fact that NOV is a bacterial DNA-gyrase inhibitor that also affects topoisomerase II at high concentrations. The lack of DNA damage for NIT and MTZ was confirmed by the CometChip® results, which were negative for all three drugs except at overtly cytotoxic concentrations. This case study demonstrates the utility of combining the TGx-DDI biomarker and CometChip® to resolve conflicting genotoxicity data and provides further validation to support the reproducibility of the biomarker.

A Transformative Vision for an Omics-Based Regulatory Chemical Testing Paradigm.

Use of molecular data in human and ecological health risk assessments of industrial chemicals and agrochemicals has been anticipated by the scientific community for many years; however, these data are rarely used for risk assessment. Here, a logic framework is proposed to explore the feasibility and future development of transcriptomic methods to refine and replace the current apical endpoint-based regulatory toxicity testing paradigm. Four foundational principles are outlined and discussed that would need to be accepted by stakeholders prior to this transformative vision being realized. Well-supported by current knowledge, the first principle is that transcriptomics is a reliable tool for detecting alterations in gene expression that result from endogenous or exogenous influences on the test organism. The second principle states that alterations in gene expression are indicators of adverse or adaptive biological responses to stressors in an organism. Principle 3 is that transcriptomics can be employed to establish a benchmark dose-based point of departure (POD) from short-term, in vivo studies at a dose level below which a concerted molecular change (CMC) is not expected. Finally, Principle 4 states that the use of a transcriptomic POD (set at the CMC dose level) will support a human health-protective risk assessment. If all four principles are substantiated, this vision is expected to transform aspects of the industrial chemical and agrochemical risk assessment process that are focused on establishing safe exposure levels for mammals across numerous toxicological contexts resulting in a significant reduction in animal use while providing equal or greater protection of human health. Importantly, these principles and approaches are also generally applicable for ecological safety assessment.

A Collaborative Initiative to Establish Genomic Biomarkers for Assessing Tumorigenic Potential to Reduce Reliance on Conventional Rodent Carcinogenicity Studies.

There is growing recognition across broad sectors of the scientific community that use of genomic biomarkers has the potential to reduce the need for conventional rodent carcinogenicity studies of industrial chemicals, agrochemicals, and pharmaceuticals through a weight-of-evidence approach. These biomarkers fall into 2 major categories: (1) sets of gene transcripts that can identify distinct tumorigenic mechanisms of action; and (2) cancer driver gene mutations indicative of rapidly expanding growth-advantaged clonal cell populations. This call-to-action article describes a collaborative approach launched to develop and qualify biomarker gene expression panels that measure widely accepted molecular pathways linked to tumorigenesis and their activation levels to predict tumorigenic doses of chemicals from short-term exposures. Growing evidence suggests that application of such biomarker panels in short-term exposure rodent studies can identify both tumorigenic hazard and tumorigenic activation levels for chemical-induced carcinogenicity. In the future, this approach will be expanded to include methodologies examining mutations in key cancer driver gene mutation hotspots as biomarkers of both genotoxic and nongenotoxic chemical tumor risk. Analytical, technical, and biological validation studies of these complementary genomic tools are being undertaken by multisector and multidisciplinary collaborative teams within the Health and Environmental Sciences Institute. Success from these efforts will facilitate the transition from current heavy reliance on conventional 2-year rodent carcinogenicity studies to more rapid animal- and resource-sparing approaches for mechanism-based carcinogenicity evaluation supporting internal and regulatory decision-making.

An international, interlaboratory ring trial confirms the feasibility of an extraction-less "direct" RT-qPCR method for reliable detection of SARS-CoV-2 RNA in clinical samples.

Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is used worldwide to test and trace the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). "Extraction-less" or "direct" real time-reverse transcription polymerase chain reaction (RT-PCR) is a transparent and accessible qualitative method for SARS-CoV-2 detection from nasopharyngeal or oral pharyngeal samples with the potential to generate actionable data more quickly, at a lower cost, and with fewer experimental resources than full RT-qPCR. This study engaged 10 global testing sites, including laboratories currently experiencing testing limitations due to reagent or equipment shortages, in an international interlaboratory ring trial. Participating laboratories were provided a common protocol, common reagents, aliquots of identical pooled clinical samples, and purified nucleic acids and used their existing in-house equipment. We observed 100% concordance across laboratories in the correct identification of all positive and negative samples, with highly similar cycle threshold values. The test also performed well when applied to locally collected patient nasopharyngeal samples, provided the viral transport media did not contain charcoal or guanidine, both of which appeared to potently inhibit the RT-PCR reaction. Our results suggest that direct RT-PCR assay methods can be clearly translated across sites utilizing readily available equipment and expertise and are thus a feasible option for more efficient COVID-19 coronavirus disease testing as demanded by the continuing pandemic.

An international, interlaboratory ring trial confirms the feasibility of an open-source, extraction-less "direct" RT-qPCR method for reliable detection of SARS-CoV-2 RNA in clinical samples.

Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is used worldwide to test and trace the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). "Extraction-less" or "direct" real time-reverse transcription polymerase chain reaction (RT-PCR) is an open-access qualitative method for SARS-CoV-2 detection from nasopharyngeal or oral pharyngeal samples with the potential to generate actionable data more quickly, at a lower cost, and with fewer experimental resources than full RT-qPCR. This study engaged 10 global testing sites, including laboratories currently experiencing testing limitations due to reagent or equipment shortages, in an international interlaboratory ring trial. Participating laboratories were provided a common protocol, common reagents, aliquots of identical pooled clinical samples, and purified nucleic acids and used their existing in-house equipment. We observed 100% concordance across laboratories in the correct identification of all positive and negative samples, with highly similar cycle threshold values. The test also performed well when applied to locally collected patient nasopharyngeal samples, provided the viral transport media did not contain charcoal or guanidine, both of which appeared to potently inhibit the RT-PCR reaction. Our results suggest that open-access, direct RT-PCR assays are a feasible option for more efficient COVID-19 coronavirus disease testing as demanded by the continuing pandemic.

The COMPARE Database: A Public Resource for Allergen Identification, Adapted for Continuous Improvement.

Motivation: The availability of databases identifying allergenic proteins via a transparent and consensus-based scientific approach is of prime importance to support the safety review of genetically-modified foods and feeds, and public safety in general. Over recent years, screening for potential new allergens sequences has become more complex due to the exponential increase of genomic sequence information. To address these challenges, an international collaborative scientific group coordinated by the Health and Environmental Sciences Institute (HESI), was tasked to develop a contemporary, adaptable, high-throughput process to build the COMprehensive Protein Allergen REsource (COMPARE) database, a publicly accessible allergen sequence data resource along with bioinformatics analytical tools following guidelines of FAO/WHO and CODEX Alimentarius Commission. Results: The COMPARE process is novel in that it involves the identification of candidate sequences via automated keyword-based sorting algorithm and manual curation of the annotated sequence entries retrieved from public protein sequence databases on a yearly basis; its process is meant for continuous improvement, with updates being transparently documented with each version; as a complementary approach, a yearly key-word based search of literature databases is added to identify new allergen sequences that were not (yet) submitted to protein databases; in addition, comments from the independent peer-review panel are posted on the website to increase transparency of decision making; finally, sequence comparison capabilities associated with the COMPARE database was developed to evaluate the potential allergenicity of proteins, based on internationally recognized guidelines, FAO/WHO and CODEX Alimentarius Commission.

'All In': a pragmatic framework for COVID-19 testing and action on a global scale.

Current demand for SARS-CoV-2 testing is straining material resource and labor capacity around the globe. As a result, the public health and clinical community are hindered in their ability to monitor and contain the spread of COVID-19. Despite broad consensus that more testing is needed, pragmatic guidance toward realizing this objective has been limited. This paper addresses this limitation by proposing a novel and geographically agnostic framework (the 4Ps framework) to guide multidisciplinary, scalable, resource-efficient, and achievable efforts toward enhanced testing capacity. The 4Ps (Prioritize, Propagate, Partition, and Provide) are described in terms of specific opportunities to enhance the volume, diversity, characterization, and implementation of SARS-CoV-2 testing to benefit public health. Coordinated deployment of the strategic and tactical recommendations described in this framework has the potential to rapidly expand available testing capacity, improve public health decision-making in response to the COVID-19 pandemic, and/or to be applied in future emergent disease outbreaks.

A cross-sector call to improve carcinogenicity risk assessment through use of genomic methodologies.

Robust genomic approaches are now available to realize improvements in efficiencies and translational relevance of cancer risk assessments for drugs and chemicals. Mechanistic and pathway data generated via genomics provide opportunities to advance beyond historical reliance on apical endpoints of uncertain human relevance. Published research and regulatory evaluations include many examples for which genomic data have been applied to address cancer risk assessment as a health protection endpoint. The alignment of mature, robust, reproducible, and affordable technologies with increasing demands for reduced animal testing sets the stage for this important transition. We present our shared vision for change from leading scientists from academic, government, nonprofit, and industrial sectors and chemical and pharmaceutical safety applications. This call to action builds upon a 2017 workshop on "Advances and Roadblocks for Use of Genomics in Cancer Risk Assessment." The authors propose a path for implementation of innovative cancer risk assessment including incorporating genomic signatures to assess mechanistic relevance of carcinogenicity and enhanced use of genomics in benchmark dose and point of departure evaluations. Novel opportunities for the chemical and pharmaceutical sectors to combine expertise, resources, and objectives to achieve a common goal of improved human health protection are identified.

Stakeholder perspectives on addressing adverse events from adjuvant cancer therapy: A qualitative study.

BACKGROUND: With increasing survival rates, a growing population of patients with cancer have received or will receive adjuvant therapy to prevent cancer recurrences. Patients and caregivers will confront the complexities of balancing the preventative benefits of adjuvant therapy with possible near-term or long-term adverse events (AEs). Adjuvant treatment-related AEs (from minimal to severe) can impact therapeutic adherence, quality of life, emotional and physical health, and survival. However, to the authors' knowledge, limited information is available regarding how stakeholders use or desire to use adjuvant-related AE information to inform the care of patients with cancer. METHODS: A qualitative, purposeful sampling approach was used to elicit stakeholder feedback via semistructured interviews (24 interviews). Drug development, drug regulatory, clinical, payer, and patient/patient advocacy stakeholders were questioned about the generation, dissemination, and use of adjuvant treatment-related AE information to inform the care of patients with cancer. Transcripts were coded independently by 2 senior health care researchers and reconciled to identify key themes. RESULTS: All stakeholder groups in the current study identified needed improvements in each of the following 4 areas: 1) improving the accessibility and relevance of AE-related information; 2) better integrating and implementing available information regarding AEs for decisions; 3) connecting contemporary cultural and economic value systems to the generation and use of information regarding adjuvant treatment-related AEs; and 4) addressing a lack of alignment and ownership of stakeholder efforts to improve the use of AE information in the adjuvant setting. CONCLUSIONS: Despite commonalities in the overall needs identified by the diverse stakeholders in the current study, broad systemic change has been stymied. The current study identified the lack of alignment and the absence of a central "owner" of these diffuse efforts as a previously unrecognized hurdle to realizing the desired systemic improvements. Future initiatives aimed at improving quality of life and outcomes for patients receiving adjuvant therapy through the improved use of AE information must address this challenge through innovative collectives and novel leadership strategies.

Improving attribution of adverse events in oncology clinical trials.

Attribution of adverse events (AEs) is critical to oncology drug development and the regulatory process. However, processes for determining the causality of AEs are often sub-optimal, unreliable, and inefficient. Thus, we conducted a toxicity-attribution workshop in Silver Springs MD to develop guidance for improving attribution of AEs in oncology clinical trials. Attribution stakeholder experts from regulatory agencies, sponsors and contract research organizations, clinical trial principal investigators, pre-clinical translational scientists, and research staff involved in capturing attribution information participated. We also included patients treated in oncology clinical trials and academic researchers with expertise in attribution. We identified numerous challenges with AE attribution, including the non-informative nature of and burdens associated with the 5-tier system of attribution, increased complexity of trial logistics, costs and time associated with AE attribution data collection, lack of training in attribution for early-career investigators, insufficient baseline assessments, and lack of consistency in the reporting of treatment-related and treatment-emergent AEs in publications and clinical scientific reports. We developed recommendations to improve attribution: we propose transitioning from the present 5-tier system to a 2-3 tier system for attribution, more complete baseline information on patients' clinical status at trial entry, and mechanisms for more rapid sharing of AE information during trials. Oncology societies should develop recommendations and training in attribution of toxicities. We call for further harmonization and synchronization of recommendations regarding causality safety reporting between FDA, EMA and other regulatory agencies. Finally, we suggest that journals maintain or develop standardized requirements for reporting attribution in oncology clinical trials.

TGx-DDI, a Transcriptomic Biomarker for Genotoxicity Hazard Assessment of Pharmaceuticals and Environmental Chemicals.

Genotoxicity testing is an essential component of the safety assessment paradigm required by regulatory agencies world-wide for analysis of drug candidates, and environmental and industrial chemicals. Current genotoxicity testing batteries feature a high incidence of irrelevant positive findings-particularly for in vitro chromosomal damage (CD) assays. The risk management of compounds with positive in vitro findings is a major challenge and requires complex, time consuming, and costly follow-up strategies including animal testing. Thus, regulators are urgently in need of new testing approaches to meet legislated mandates. Using machine learning, we identified a set of transcripts that responds predictably to DNA-damage in human cells that we refer to as the TGx-DDI biomarker, which was originally referred to as TGx-28.65. We proposed to use this biomarker in conjunction with current genotoxicity testing batteries to differentiate compounds with irrelevant "false" positive findings in the in vitro CD assays from true DNA damaging agents (i.e., for de-risking agents that are clastogenic in vitro but not in vivo). We validated the performance of the TGx-DDI biomarker to identify true DNA damaging agents, assessed intra- and inter- laboratory reproducibility, and cross-platform performance. Recently, to augment the application of this biomarker, we developed a high-throughput cell-based genotoxicity testing system using the NanoString nCounter® technology. Here, we review the status of TGx-DDI development, its integration in the genotoxicity testing paradigm, and progress to date in its qualification at the US Food and Drug Administration (FDA) as a drug development tool. If successfully validated and implemented, the TGx-DDI biomarker assay is expected to significantly augment the current strategy for the assessment of genotoxic hazards for drugs and chemicals.

Can non-clinical repolarization assays predict the results of clinical thorough QT studies? Results from a research consortium.

BACKGROUND AND PURPOSE: Translation of non-clinical markers of delayed ventricular repolarization to clinical prolongation of the QT interval corrected for heart rate (QTc) (a biomarker for torsades de pointes proarrhythmia) remains an issue in drug discovery and regulatory evaluations. We retrospectively analysed 150 drug applications in a US Food and Drug Administration database to determine the utility of established non-clinical in vitro IKr current human ether-à-go-go-related gene (hERG), action potential duration (APD) and in vivo (QTc) repolarization assays to detect and predict clinical QTc prolongation. EXPERIMENTAL APPROACH: The predictive performance of three non-clinical assays was compared with clinical thorough QT study outcomes based on free clinical plasma drug concentrations using sensitivity and specificity, receiver operating characteristic (ROC) curves, positive (PPVs) and negative predictive values (NPVs) and likelihood ratios (LRs). KEY RESULTS: Non-clinical assays demonstrated robust specificity (high true negative rate) but poor sensitivity (low true positive rate) for clinical QTc prolongation at low-intermediate (1×-30×) clinical exposure multiples. The QTc assay provided the most robust PPVs and NPVs (ability to predict clinical QTc prolongation). ROC curves (overall test accuracy) and LRs (ability to influence post-test probabilities) demonstrated overall marginal performance for hERG and QTc assays (best at 30× exposures), while the APD assay demonstrated minimal value. CONCLUSIONS AND IMPLICATIONS: The predictive value of hERG, APD and QTc assays varies, with drug concentrations strongly affecting translational performance. While useful in guiding preclinical candidates without clinical QT prolongation, hERG and QTc repolarization assays provide greater value compared with the APD assay.

Do current approaches to assessing therapy related adverse events align with the needs of long-term cancer patients and survivors?

The increasing efficacy of cancer therapeutics means that the timespan of cancer therapy administration is undergoing a transition to increasingly long-term settings. Unfortunately, chronic therapy-related adverse health events are an unintended, but not infrequent, outcome of these life-saving therapies. Historically, the cardio-oncology field has evolved as retrospective effort to understand the scope, mechanisms, and impact of treatment-related toxicities that were already impacting patients. This review explores whether current systemic approaches to detecting, reporting, tracking, and communicating AEs are better positioned to provide more proactive or concurrent information to mitigate the impact of AE's on patient health and quality of life. Because the existing tools and frameworks for capturing these effects are not specific to cardiology, this study looks broadly at the landscape of approaches and assumptions. This review finds evidence of increasing focus on the provision of actionable information to support long-term health and quality of life for survivors and those on chronic therapy. However, the current means to assess and support the impact of this burden on patients and the healthcare system are often of limited relevance for an increasingly long-lived survivor and patient population.

Enhancing quality of life as a goal for anticancer therapeutics.

Translational cancer research requires a quality-of-life-driven agenda.