Preclinical evaluation of drugs in animals helps researchers to select potentially informative clinical laboratory markers for human trials. To assess the utility of animal thrombin generation (TG) assay, we studied the sensitivity of animal plasmas to triggers of TG, human Tissue Factor (TF), and Activated Factor XI (FXIa). Pooled human, mouse, rat, guinea pig, rabbit, bovine, sheep, and goat plasmas were used in this study. TF- or FXIa-triggered TG and clotting were measured via fluorescence and optical density, respectively. Thrombin peak height (TPH) and time (TPT), clot time (CT), and fibrin clot density (FCD) were all analyzed. The trigger low and high sensitivity borders (LSB and HSB) for each assay parameter were defined as TF and FXIa concentrations, providing 20 and 80% of the maximal parameter value, unless the baseline (no trigger) value exceeded 20% of the maximal, in which case, LSB was derived from 120% of baseline value. Normal human samples demonstrated lower TPH HSB than most of the animal samples for both TF and FXIa. Animal samples, except mice, demonstrated lower TPT LSB for FXIa versus humans. Most rodent and rabbit samples produced baseline TG in the absence of TG triggers that were consistent with the pre-activation of blood coagulation. FCD was not sensitive to both TF and FXIa in either of the plasmas. Animal plasmas have widely variable sensitivities to human TF and FXIa, which suggests that optimization of trigger concentration is required prior to test use, and this complicates the extrapolation of animal model results to humans.

Necessity for finding improved intervention in many legacy therapeutic areas are of high priority. This has the potential to decrease the expense of medical care and poor outcomes for many patients. Typically, clinical efficacy is the primary evaluating criteria to measure any beneficial effect of a treatment. Albeit, there could be situations when several other factors (e.g. side-effects, cost-burden, less debilitating, less intensive, etc.) which can permit some slightly less efficacious treatment options favorable to a subgroup of patients. This often leads to non-inferiority (NI) testing. NI trials may or may not include a placebo arm due to ethical reasons. However, when included, the resulting three-arm trial is more prudent since it requires less stringent assumptions compared to a two-arm placebo-free trial. In this article, we consider both Frequentist and Bayesian procedures for testing NI in the three-arm trial with binary outcomes when the functional of interest is risk difference. An improved Frequentist approach is proposed first, which is then followed by a Bayesian counterpart. Bayesian methods have a natural advantage in many active-control trials, including NI trial, as it can seamlessly integrate substantial prior information. In addition, we discuss sample size calculation and draw an interesting connection between the two paradigms.

Variability in pain-related outcomes can hamper assay sensitivity of chronic pain clinical trials. Expectations of outcome in such trials may account for some of this variability, and thereby impede development of novel pain treatments. Measurement of participants\' expectations prior to initiating study treatment (active or placebo) is infrequent, variable, and often unvalidated. Efforts to optimize and standardize measurement, analysis, and management of expectations are needed. In this Focus Article, we provide an overview of research findings on the relationship between baseline expectations and pain-related outcomes in clinical trials of pharmacological and nonpharmacological pain treatments. We highlight the potential benefit of adjusting for participants\' expectations in clinical trial analyses and draw on findings from patient interviews to discuss critical issues related to measurement of expectations. We conclude with suggestions regarding future studies focused on better understanding the utility of incorporating these measures into clinical trial analyses. PERSPECTIVE: This focus article provides an overview of the relationship between participants\' baseline expectations and pain-related outcomes in the setting of clinical trials of chronic pain treatments. Systematic research focused on the measurement of expectations and the impact of adjusting for expectations in clinical trial analyses may improve assay sensitivity.

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Randomized controlled trials (RCTs) of a new investigational drug often include active as well as placebo control arms. The active arm, comprising an approved treatment for the indication under study, along with the placebo arm, are together required to establish assay sensitivity; if the active treatment outperforms placebo, as expected, the results of the RCT can be further interpreted, but if the active treatment is no better than placebo (such as because of ceiling or floor effects), the RCT is a failed trial. The concepts involved are explained from scientific and ethical perspectives.

Proteins are one of the main constituents of living cells. Studying the quantities of proteins under physiological and pathological conditions can give valuable insights into health status, since proteins are the functional molecules of life. To be able to detect and quantify low-abundance proteins in biofluids for applications such as early disease diagnostics, sensitive analytical techniques are desired. An example of this application is using proteins as biomarkers for detecting cancer or neurological diseases, which can provide early, lifesaving diagnoses. However, conventional methods for protein detection such as ELISA, mass spectrometry, and western blotting cannot offer enough sensitivity for certain applications. Recent advances in optical-based micro- and nano-biosensors have demonstrated promising results to detect proteins at low quantities down to the single-molecule level, shining lights on their capacities for ultrasensitive disease diagnosis and rare protein detection. However, to date, there is a lack of review articles synthesizing and comparing various optical micro- and nano-sensing methods of enhancing the limits of detections of the antibody-based protein assays. The purpose of this article is to critically review different strategies of improving assay sensitivity using miniaturized biosensors, such as assay miniaturization, improving antibody binding capacity, sample purification, and signal amplification. The pros and cons of different methods are compared, and the future perspectives of this research field are discussed.

There is a public health need for improved suicide risk assessment tools. This pilot methodology study compared the assay sensitivity of computerized adaptive tests (CAT) of depression and suicidal ideation vs. traditional ratings in a randomized trial subgroup. The last 20 persons to enroll in a published ketamine trial in suicidal depression were studied. This subgroup received traditional and CAT ratings at baseline, 24 h post-infusion and follow-up week 2, 4, and 6: Hamilton Depression Rating Scale, Beck Depression Inventory, and Beck Scale for Suicidal Ideation vs. the CAT-Depression Inventory and CAT-Suicide Scale. Results showed larger effect sizes (ES) for CAT compared with traditional clinician-rated and self-report scales. Coefficients of variation for baseline measurements were lower for CAT compared with traditional scales. This is the first study to show that CAT may have greater assay sensitivity for treatment effects, particularly for suicidal ideation, compared with traditional clinician-rated and non-adaptive self-rated scales in a randomized trial. The findings suggest CAT can enable quick long-term follow-up assessments via cellphone, tablet, or computer while minimizing response bias due to repeated measurement of the same symptom items. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT01700829.

Determination of the presence in the blood of antibodies specific to the causative agent of a particular disease (serodiagnosis) is an effective approach in medical analytical chemistry. Serodiagnostics performed in the lateral flow immunoassay format (immunochromatography) meet the modern requirements for point-of-care testing and are supported by existing technologies of large-scale diagnostic tests production, thus increasing the amount of attention in a tense epidemiological situation. For traditional lateral flow serodiagnostics formats, a large number of nonspecific immunoglobulins in the sample significantly reduces the degree of detectable binding. To overcome these limitations, an assay based on the formation of immobilized antigen-specific antibody-labeled antigen complexes detection was proposed. However, the requirements for its implementation, providing maximum sensitivity, have not been established. This article describes the mathematical model for the above assay. The influence of the ratio of reagent concentrations on the analysis results is considered. It is noted that the formation of specific antibody complexes with several labeled antigens is the main limiting factor in reducing the detection limit, and methods are proposed to minimize this factor. Recommendations for the choice of the assay conditions, following from the analysis of the model, are confirmed experimentally.

To compare assay sensitivity of the Visual Analogue Scale (VAS) for global osteoarthritis pain and the Western Ontario and McMaster University (WOMAC) pain subscale, and the associated between-trial heterogeneity in effect sizes (ES).
We included trials with placebo, sham or non-intervention control that included at least 100 patients with hip or knee osteoarthritis per arm, reporting both VAS and WOMAC pain scores. ES were calculated as between-group difference in means divided by the pooled standard deviation and compared using a paired t-test. ES and τ2 as a measure of between-trial heterogeneity were combined using random-effects meta-regression with robust variance estimation to account for the correlation of data within trials and meta-analyses.
Twenty-eight trials with 44 randomized comparisons were included. In 28 comparisons (64%), ES from VAS favoured the intervention more than those from WOMAC pain (P = 0.003). Twenty-six p-values (59%) were smaller according to VAS (P = 0.008). The 44 comparisons contributed to 12 meta-analyses. Eleven meta-analyses (92%) showed larger benefits of interventions according to VAS, with a combined overall difference in ES of -0.08 (95% CI -0.14 to -0.02). τ2 was similar for VAS and WOMAC pain (difference in τ2, -0.003, 95% CI -0.009 to 0.004).
The VAS for global pain had slightly higher assay sensitivity at trial and meta-analysis levels than the WOMAC pain subscale without relevant increase in between-trial heterogeneity.

To evaluate the association between the degree of response to placebo in migraine studies and the observed difference between drug and placebo across studies of preventative treatments for migraine.
A systematic review was performed using MEDLINE and the Cochrane Central Register of Controlled Clinical Trials from January 1988 to June 2019. Randomized, double-blind, parallel-group, placebo-controlled trials on oral or injection preventative treatments for migraine were included. Single- and multi-variable linear regression analyses were performed on the placebo-subtracted response rate (i.e. placebo responders subtracted from active responders), and the proportion of placebo responders. Fisher\'s exact tests were performed on the level of placebo response and the success in meeting the study\'s primary endpoint.
After adjusting for route of administration and number of randomized subjects, there was a statistically significant association between the proportion of patients who were placebo responders and the placebo-subtracted response rate (b = -0.27, p = 0.02). There was a statistically significant difference in trial success rate (60%) between studies with ≤20% placebo responders and studies with > 30% placebo responders (p = 0.03).
Considering the detrimental impact that high placebo response can have on clinical trials, it is imperative to find effective solutions to decrease the placebo response and increase assay sensitivity.