Journal of pharmacological and toxicological methods最新文献

Introduction

In preclinical cardiovascular safety pharmacology studies, statistical analysis of the rate corrected QT interval (QTc) is the focus for predicting QTc interval changes in the clinic. Modeling of a concentration/QTc relationship, common clinically, is limited due to minimal pharmacokinetic (PK) data in nonclinical testing. It is possible, however, to relate the average drug plasma concentration from sparse PK samples over specific times to the mean corrected QTc. We hypothesize that averaging drug plasma concentration and the QTc-rate relationship over time provides a simple, accurate concentration-QTc relationship bridging statistical and concentration/QTc modeling.

Methods

Cardiovascular telemetry studies were conducted in non-human primates (NHP; n = 48) and canines (n = 8). Pharmacokinetic samples were collected on separate study days in both species. Average plasma concentrations for specific intervals (CAverage_0-X) were calculated for moxifloxacin in canines and NHP using times corresponding to super-intervals for the QTc data statistical analysis. The QTc effect was calculated for each super-interval using a linear regression correction incorporating QT and HR data from the whole super-interval. The concentration QTc effects were then modeled.

Results

In NHP, a 10.9 ± 0.06 ms (mean ± 95% CI) change in QTc was detected at approximately 1.5× the moxifloxacin plasma concentration that causes a 10 ms QTc change in humans, based on a 0-24 h super-interval. When simulating a drug without QT effects, mock, no effect on QTc was detected at up to 3× the clinical concentration. Similarly, in canines, a 16.6 ± 0.1 ms change was detected at 1.7× critical clinical moxifloxacin concentration, and a 0.04 ± 0.1 ms change was seen for mock.

Conclusions

While simultaneous PK and QTc data points are preferred, practical constraints and the need for QTc averaging did not prevent concentration-QTc analyses. Utilizing a 0-24 h super-interval method illustrates a simple and effective method to address cardiovascular questions when preclinical drug exposures exceed clinical concentrations.

Introduction

Nonclinical evaluation of the cardiovascular effects of novel chemical or biological entities (NCE, NBEs) is crucial for supporting first-in-human clinical trials. One important aspect of these evaluations is the assessment of potential QT/QTc prolongation risk, as drug-induced QT prolongation can have catastrophic effects. The recent publication of E14/S7B Q&As allows for the situational incorporation of nonclinical QTc data as part of an integrated risk assessment for a Thorough QT (TQT) waiver application provided certain best practice criteria are met. Recent publications provided detailed characterization of nonclinical QTc telemetry data collected from the commonly used Latin square study design.

Methods

To understand whether data from alternate telemetry study designs were sufficient to serve as part of the E14/S7B integrated risk assessment, we report the performance and translational sensitivity to identify clinical risk of QTc prolongation risk for an ascending dose telemetry design.

Results

The data demonstrated low variability in QTci interval within animals from day to day, indicating a well-controlled study environment and limited concern for uncontrolled effects across dosing days. Historical study variances of the ascending dose design with n = 4 subjects, measured by least significant difference (LSD) and root mean square error (RMSE) values, were low enough to detect a + 10 ms QTci interval change, and the median minimum detectable difference (MDD) for QTci interval changes was <10 ms. Furthermore, concentration-QTci (C-QTci) assessments to determine +10 ms QTci increases for known hERG inhibitors were comparable to clinical CC values listed in the E14/S7B training materials, supporting the use of the ascending dose design in an E14/S7B integrated risk assessment.

Discussion

These findings suggest that the ascending dose design can be a valuable tool in nonclinical evaluation of QT/QTc prolongation risk and the support of TQT waiver applications.

Allergic conjunctival disease is an immune-mediated inflammatory disease of the conjunctiva. To develop clinically useful drugs, it is necessary to develop quantitative evaluation methods that reflect the clinical symptoms in experimental animal models. Allergic conjunctivitis model mice were systemically sensitised with ovalbumin (OVA) administered intraperitoneally and locally sensitised with OVA eye drops between day 14–28. Next, conjunctivitis induced by ocular administration of OVA solution to sensitised mice was evaluated based on tear volume. Additionally, we evaluated increase in tear volume induced by direct ocular instillation of histamine, compound 48/80, and carrageenan. An increase in antigen-induced tear volume was observed in the mice model. Additionally, direct instillation of histamine, compound 48/80, and carrageenan increased tear volume. Furthermore, levocabastine inhibited the increase in tear volume in antigen-induced allergic conjunctivitis and histamine- and compound 48/80-induced conjunctivitis models. In contrast, betamethasone suppressed carrageenan-induced tear volume but not histamine- or compound 48/80-induced tear volume. Histamine may be involved in increased tear volume in allergic conjunctivitis. Betamethasone is not directly involved in the action of histamine and is thought to suppress increase in tear volume. Evaluation of tear volume in a conjunctivitis mice model is highly quantitative; therefore, it is possible to evaluate drug efficacy. This is considered a useful index compared with conventional methods.

Cardiovascular safety pharmacology and toxicology studies include vehicle control animals in most studies. Electrocardiogram data on common vehicles is accumulated relatively quickly. In the interests of the 3Rs principles it may be useful to use this historical information to reduce the use of animals or to refine the sensitivity of studies.

We used implanted telemetry data from a large nonhuman primate (NHP) cardiovascular study (n = 48) evaluating the effect of moxifloxacin. We extracted 24 animals to conduct a n = 3/sex/group analysis. The remaining 24 animals were used to generate 1000 unique combinations of 3 male and 3 female NHP to act as control groups for the three treated groups in the n = 3/sex/group analysis. The distribution of treatment effects, median minimum detectable difference (MDD) values were gathered from the 1000 studies. These represent contemporary controls.

Data were available from 42 NHP from 3 other studies in the same laboratory using the same technology. These were used to generate 1000 unique combinations of 6, 12, 18, 24 and 36 NHP to act as historical control animals for the 18 animals in the treated groups of the moxifloxacin study. Data from an additional laboratory were also available for 20 NHP.

The QT, RR and QT-RR data from the three sources were comparable. However, differences in the time course of QTc effect in the vehicle data from the two laboratories meant that it was not possible to use cross-lab controls. In the case of historical controls from the same laboratory, these could be used in place of the contemporary controls in determining a treatment's effect. There appeared to be an advantage in using larger (≥18) group sizes for historical controls. These data support the opportunity of using historical controls to reduce the number of animals used in new cardiovascular studies.

Thymoquinone (TH) has been one of the major phytochemical used in the treatment of cancers since long time, especially in the management of glioblastoma multiforme (GBM). The formulation of lipo-polymeric nanoshells (LPNs) and their nasal delivery are fascinating approaches for overcoming the drawbacks of low solubility and poor bioavailability of TH. Hence targeting LPNs to the brain requires a validated bioanalytical method for the assessment of TH concentration in Cerebrospinal fluid (CSF) and brain tissue homogenates (BTH). Therefore, the current work focuses on the development and validation of high-performance liquid chromatography (HPLC) method in CSF by employing nasal simulated fluid (NSF) as one of the major components of the mobile phase. The developed method was checked for linearity in the range of 0.05 to 1.6 μg/mL, having an r² value of 0.999 with mean % recovery >95% and % RSD values below <2.0%. The developed method gave a clear separation of TH at 6.021 ± 0.17 min with an internal standard at 4.102 ± 0.09 min and a CSF spike at 2.170 ± 0.12 min. The developed method assisted in determining the in-vitro and in-vivo drug release study of LPNs, pharmacokinetic profiling, qualitative in-vivo brain uptake study, in-vitro cellular uptake, and generating stability data of formulated LPNs proposed for intranasal administration in rats.

Determining the causality of Adverse Drug Reactions (ADRs) is essential for management and prevention of future occurrences. The WHO-Uppsala Monitoring Centre (UMC) system is recommended under the Pharmacovigilance Program of India whereas Naranjo's algorithm is commonly utilized by clinicians, but their agreement remains a subject of investigation. This study aims to compare the inter-rater agreement between these two scales for causality assessment of ADRs. In this cross-sectional study, two groups of pharmacovigilance experts were given a set of total 399 anonymized individual case safety reports, collected over six months. The raters were blinded to each other's assessments and applied the WHO-UMC system and Naranjo algorithm to each case independently. Inter-rater agreement was then evaluated utilizing Cohen's kappa. The suspected ADRs were also comprehensively analysed on parameters like age, sex, route of administration, speciality, organ system affected, most common drug categories and individual drugs, outcome of ADRs. Analysis of 399 suspected ADRs revealed that mean age of patients was 36.8 ± 18.0 years, females were more frequently affected, highest proportion of reports were from psychiatry inpatients, seen with antipsychotic drugs, involved the central nervous system, with oral administration, and 91% resolved. On causality assessment by the WHO-UMC system, 53.3% were “Certain” whereas Naranjo's algorithm categorized 96.74% of ADRs as “Probable”. Cohen's kappa showed a “Minimal” agreement (0.22) between WHO-UMC and Naranjo system of causality assessment. The considerable lack of agreement between the two commonly employed systems of causality assessment of ADRs warrants further investigation into specific factors influencing the disagreement to improve the accuracy of causality assessments.

The Health and Environmental Sciences Institute (HESI) Cardiac Safety Committee designed and created a publicly accessible database with an initial set of 128 pharmacologically defined pharmaceutical agents, many with known cardiotoxic properties. The database includes specific information about each compound that could be useful in evaluating hypotheses around mechanisms of drug-induced cardiac toxicity or for development of novel cardiovascular safety assays. Data on each of the compounds was obtained from published literature and online sources (e.g., DrugBank.ca and International Union of Basic and Clinical Pharmacology (IUPHAR) / British Pharmacological Society (BPS) Guide to PHARMACOLOGY) and was curated by 10 subject matter experts. The database includes information such as compound name, pharmacological mode of action, characterized cardiac mode of action, type of cardiac toxicity, known clinical cardiac toxicity profile, animal models used to evaluate the cardiotoxicity profile, routes of administration, and toxicokinetic parameters (i.e., Cmax). Data from both nonclinical and clinical studies are included for each compound. The user-friendly web interface allows for multiple approaches to search the database and is also intended to provide a means for the submission of new data/compounds from relevant users. This will ensure that the database is constantly updated and remains current. Such a data repository will not only aid the HESI working groups in defining drugs for use in any future studies, but safety scientists can also use the database as a vehicle of support for broader cardiovascular safety studies or exploring mechanisms of toxicity associated with certain pharmacological modes of action.

The Health and Environmental Sciences Institute (HESI) is a nonprofit organization dedicated to resolving global health challenges through collaborative scientific efforts across academia, regulatory authorities and the private sector. Collaborative science across non-clinical disciplines offers an important keystone to accelerate the development of safer and more effective medicines. HESI works to address complex challenges by leveraging diverse subject-matter expertise across sectors offering access to resources, data and shared knowledge. In 2008, the HESI Cardiac Safety Committee (CSC) was established to improve public health by reducing unanticipated cardiovascular (CV)-related adverse effects from pharmaceuticals or chemicals. The committee continues to significantly impact the field of CV safety by bringing together experts from across sectors to address challenges of detecting and predicting adverse cardiac outcomes. Committee members have collaborated on the organization, management and publication of prospective studies, retrospective analyses, workshops, and symposia resulting in 38 peer reviewed manuscripts. Without this collaboration these manuscripts would not have been published. Through their work, the CSC is actively addressing challenges and opportunities in detecting potential cardiac failure modes using in vivo, in vitro and in silico models, with the aim of facilitating drug development and improving study design. By examining past successes and future prospects of the CSC, this manuscript sheds light on how the consortium's multifaceted approach not only addresses current challenges in detecting potential cardiac failure modes but also paves the way for enhanced drug development and study design methodologies. Further, exploring future opportunities and challenges will focus on improving the translational predictability of nonclinical evaluations and reducing reliance on animal research in CV safety assessments.

The principle of proportionality of the systolic area of the central aortic pressure to stroke volume (SV) has been long known. The aim of the present work was to evaluate an in silico solution derived from this principle for modelling SV (iSV model) in cardiovascular safety pharmacology studies by telemetry. Blood pressure was measured in the abdominal aorta in accordance with standard practice. Central aortic pressure was modelled from the abdominal aortic pressure waveform using the N-point moving average (NPMA) method for beat-to-beat estimation of SV. First, the iSV was compared to the SV measured by ultrasonic flowmetry in the ascending aorta (uSV) after various pharmacological challenges in beagle dogs anaesthetised with etomidate/fentanyl. The iSV showed minimal bias (0.2 mL i.e. 2%) and excellent agreement with uSV. Then, previous telemetry studies including reference vasoactive and inotropic compounds were retrospectively reanalysed to model drug effects on stroke volume (iSV), cardiac output (iCO) and systemic vascular resistance (iSVR). Among them, the examples of nicardipine and isoprenaline highlight risks of erroneous or biased estimation of drug effects from the abdominal aortic pressure due to pulse pressure amplification. Furthermore, the examples of verapamil, quinidine and moxifloxacin show that iSV, iCO and iSVR are earlier biomarkers than blood pressure itself for predicting drug effect on blood pressure. This in silico modelling approach included in vivo telemetry safety pharmacology studies can be considered as a New Approach Methodology (NAM) that provides valuable additional information and contribute to improving non-clinical translational research to the clinic.