John L. Werth

Clinical importance of changes in chronic pain intensity measured on an 11-point numerical pain rating scale

&NA; Pain intensity is frequently measured on an 11‐point pain intensity numerical rating scale (PI‐NRS), where 0=no pain and 10=worst possible pain. However, it is difficult to interpret the clinical importance of changes from baseline on this scale (such as a 1‐ or 2‐point change). To date, there are no data driven estimates for clinically important differences in pain intensity scales used for chronic pain studies. We have estimated a clinically important difference on this scale by relating it to global assessments of change in multiple studies of chronic pain. Data on 2724 subjects from 10 recently completed placebo‐controlled clinical trials of pregabalin in diabetic neuropathy, postherpetic neuralgia, chronic low back pain, fibromyalgia, and osteoarthritis were used. The studies had similar designs and measurement instruments, including the PI‐NRS, collected in a daily diary, and the standard seven‐point patient global impression of change (PGIC), collected at the endpoint. The changes in the PI‐NRS from baseline to the endpoint were compared to the PGIC for each subject. Categories of ‘much improved’ and ‘very much improved’ were used as determinants of a clinically important difference and the relationship to the PI‐NRS was explored using graphs, box plots, and sensitivity/specificity analyses. A consistent relationship between the change in PI‐NRS and the PGIC was demonstrated regardless of study, disease type, age, sex, study result, or treatment group. On average, a reduction of approximately two points or a reduction of approximately 30% in the PI‐NRS represented a clinically important difference. The relationship between percent change and the PGIC was also consistent regardless of baseline pain, while higher baseline scores required larger raw changes to represent a clinically important difference. The application of these results to future studies may provide a standard definition of clinically important improvement in clinical trials of chronic pain therapies. Use of a standard outcome across chronic pain studies would greatly enhance the comparability, validity, and clinical applicability of these studies.

Efficacy of the Novel Anxiolytic Pregabalin in Social Anxiety Disorder: A Placebo-Controlled, Multicenter Study

Abstract: Pregabalin is a novel compound in the development for the treatment of anxiety disorders. The safety and efficacy of pregabalin for the treatment of social anxiety disorder was evaluated in a double-blind, multicenter clinical trial in which 135 patients were randomized to 10 weeks of double-blind treatment with either pregabalin 150 mg/d, pregabalin 600 mg/d, or placebo. The primary efficacy parameter was change from baseline to end point in the Liebowitz Social Anxiety Scale (LSAS) total score. Safety was assessed through clinical and laboratory monitoring, and recording spontaneously reported adverse events. Ninety-four patients (70%) completed the 11-week double-blind treatment phase. LSAS total score was significantly decreased by pregabalin 600 mg/d treatment compared with placebo (P = 0.024, analysis of covariance). Significant differences (P ≤ 0.05) between pregabalin 600 mg/d and placebo were seen on several secondary measures including the LSAS subscales of total fear, total avoidance, social fear, and social avoidance, and the Brief Social Phobia Scale fear subscale. Pregabalin 150 mg/d was not significantly better than placebo on any measures. Somnolence and dizziness were the most frequently occurring adverse events among patients receiving pregabalin 600 mg/d. In conclusion, pregabalin 600 mg/d was an effective and well-tolerated treatment of social anxiety disorder.

How Modeling and Simulation Have Enhanced Decision Making in New Drug Development

The idea of model-based drug development championed by Lewis Sheiner, in which pharmacostatistical models of drug efficacy and safety are developed from preclinical and available clinical data, offers a quantitative approach to improving drug development and development decision-making. Examples are presented that support this paradigm. The first example describes a preclinical model of behavioral activity to predict potency and time-course of response in humans and assess the potential for differentiation between compounds. This example illustrates how modeling procedures expounded by Lewis Sheiner provided the means to differentiate potency and the lag time between drug exposure and response and allow for rapid decision making and dose selection. The second example involves planning a Phase 2a dose-ranging and proof of concept trial in Alzheimer’s disease (AD). The issue was how to proceed with the study and what criteria to use for a go/no go decision. The combined knowledge of AD disease progression, and preclinical and clinical information about the drug were used to simulate various clinical trial scenarios to identify an efficient and effective Phase 2 study. A design was selected and carried out resulting in a number of important learning experiences as well as extensive financial savings. The motivation for this case in point was the “Learn-Confirm” paradigm described by Lewis Sheiner. The final example describes the use of Pharmacokinetic and Pharmacodynamic (PK/PD) modeling and simulation to confirm efficacy across doses. In the New Drug Application for gabapentin, data from two adequate and well-controlled clinical trials was submitted to the Food and Drug Administration (FDA) in support of the approval of the indication for the treatment of post-herpetic neuralgia. The clinical trial data was not replicated for each of the sought dose levels in the drug application presenting a regulatory dilemma. Exposure response analysis submitted in the New Drug Application was applied to confirm the evidence of efficacy across these dose levels. Modeling and simulation analyses showed that the two studies corroborate each other with respect to the pain relief profiles. The use of PK/PD information confirmed evidence of efficacy across the three studied doses, eliminating the need for additional clinical trials and thus supporting the approval of the product. It can be speculated that the work by Lewis Sheiner reflected in the FDA document titled “Innovation or Stagnation: Challenge and Opportunity on the Critical Path to New Medical Products” made this scientific approach to the drug approval process possible.

A statistical approach for classifying change in cognitive function in individuals following pharmacologic challenge: an example with alprazolam

IntroductionThe effects of any drug treatment on cognitive function are typically studied in groups of subjects. Observations made about the behavior of the drug, in the study sample, are then generalized to the population from which the sample was drawn. However, the magnitude and pharmacodynamic qualities of the response to many central nervous system-active drugs are known to vary in the population. Therefore, it is useful to consider statistical models for the detection of cognitive change in response to a drug treatment in individual subjects.Materials and methodsIn this report, we first outline the statistical assumptions and requirements for the reliable estimation of clinically relevant individual change in cognition. We then used the sedative benzodiazepine, alprazolam, as a pharmacologic challenge in healthy volunteer subjects to test our statistical model, using a parallel groups placebo-controlled study design. After treatment, the nature and severity of alprazolam-induced cognitive change was determined for each individual.ResultsOur proposed method and analysis showed an excellent sensitivity and specificity for alprazolam-related cognitive deterioration in individuals.Discussion and conclusions These findings, although preliminary, suggest that statistically reliable decisions about the effects of sedative drugs on cognition can be made for individuals.

The Use of a Clinical Utility Index to Compare Insomnia Compounds: A Quantitative Basis for Benefit–Risk Assessment

The use of a clinical utility index (CUI) was proposed in order to compare two calcium channel α2δ ligands that were in development for the treatment of insomnia. The important attributes included in the CUI were two measures of residual sedation and five measures of efficacy (wake after sleep onset, sleep quality, sleep latency, and sleep stages (stage 1 and stages 3–4)). Dose–response analyses were conducted on each end point, and a sensitivity analysis was conducted to determine a clinically meaningful difference in CUI. Nonparametric bootstrap parameters were used to build confidence intervals (CIs). Peak CUI (80% CI) was 0.345 (0.25–0.43), observed at a dose of ~30 mg with the lead compound and 0.436 (0.35–0.52) observed at >600‐mg dose for the backup. Although CUI was slightly greater for the backup, peak CUI values were observed at doses that were not considered viable, and therefore development of the ligand was discontinued. The use of the CUI allowed an efficient, quantitative, and transparent decision.

Effect of renal impairment on the pharmacokinetics of PD 0200390, a novel ligand for the voltage-gated calcium channel alpha-2-delta subunit.

AIMS To investigate the pharmacokinetics and safety of PD 0200390 in healthy subjects and subjects with renal impairment (RI) and to examine the relationship between oral and renal PD 0200390 clearance and estimated creatinine clearance (CLcr). METHODS In this open-label study, 26 subjects were categorized into four groups based on renal function: no RI (CLcr >80 ml min(-1); n= 6); mild RI (CLcr 51 to < or =80 ml min(-1); n= 6); moderate RI (CLcr >30 to 50 ml min(-1); n= 6); and severe RI (CLcr < or =30 ml min(-1); n= 8). Subjects received a single, oral dose of PD 0200390 25 mg. Noncompartmental pharmacokinetic parameters were determined from plasma and urine concentration-time data. RESULTS PD 0200390 was rapidly absorbed; mean time to maximum plasma concentration was 1.66-3.24 h. Mean half-life in subjects with normal renal function was 5.36 h, and increased with worsening RI. Oral (CL/F) and renal (CL(R)) clearance rates decreased with deteriorating renal function, whereas area under the concentration-time curve (AUC(0-infinity)) values increased by 56, 117 and 436% in subjects with mild, moderate and severe RI, respectively, indicating increased PD 0200390 exposure. Regression analysis demonstrated that CL/F and CL(R) correlated with CLcr (r= 0.953 and 0.961, respectively). PD 0200390 was well tolerated in subjects with mild, moderate or no RI. The most common adverse events were somnolence, dizziness and headache; these occurred with greatest intensity in the severe RI group. CONCLUSIONS PD 0200390 pharmacokinetic parameters (CL/F, CL(R) and AUC(0-infinity)) vary predictably with decreases in renal function; therefore dose adjustment may be required in individuals with RI.

Pooled biomarker analyses of phase 2 studies of vanutide cridificar vaccine (ACC-001) in mild-to-moderate and early Alzheimer’s disease

-23%, and -60%). For the combination drug treatment arms, we observed a significant broad dose response in the presence of high dose antibody and varying dose levels of BACE inhibitor (from -33% through -84%). The combination drug treatments of a high dose BACE inhibitor in the presence of varying dose levels of Ab antibody revealed a significant, yet steeper dose response (from -60% through -84%). Several of the of drug combination treatments resulted in significant synergistic lowering of deposited Ab. The longitudinal study demonstrated significant time dependent effects on plaque removal that was detected as early as 4weeks and the combination therapy showed a continual significant reduction over time that resulted in a dramatic reduction of deposited Ab as compared to the time zero cohort. Conclusions: The combination therapy studies demonstrated significant dose-response and longitudinal relationships for the plaque specific antibody and BACE inhibitor that further support/enable the rationale for utilizing combinational anti-amyloid therapies in the clinic.

Depression in patients screened for Alzheimer's disease clinical trials

Background: Depression is a common comorbidity in patients with AD. In two recent clinical trials for treatment of mild to moderate AD, patients with a medical history of depression were permitted to participate except those with current major depressive disorder. The prevalence of depression and clinical characteristics of these patients were investigated. Methods: A total of 2490 patients with AD who reported their medical history at a screening visit of two trials between December 2007 and October 2011 were included (ClinicalTrials.gov identifiers NCT00667810 and NCT00676143). The prevalence of a past medical history of depression was described for the overall patient sample and for patient subgroups defined by race, gender, and age at AD diagnosis. Onset of depression in relation to date of AD diagnosis was described. A statistical-modeling approach was used to identify the AD patient subgroup with the highest prevalence of depression. Results:Approximately 27% of patients reported a past medical history of depression at screening. Prevalence of depression was 33% in subjects with a diagnosis of AD at or before age 65 and 24% in those with a diagnosis of AD after age 65, with 31% in women, 22% in men, 33% in whites, and 15% in other races. The prevalence did not vary with ApoE e4 carrier status or MMSE scores (<21 vs 21). The statistical model estimated that white women with a diagnosis of AD would have the highest estimated prevalence of depression (45%). Approximately 89% of patients who had medical history of depression reported concurrent depression at screening. In comparing the time of concurrent depressive onset and diagnosis of AD in these patients, we found that depression occurred prior to AD diagnosis in approximately 44% of these patients. The percentage of women (49%) whose depressive onset preceded the diagnosis of AD was higher than that for men (34%). Conclusions: Depression was common among AD patients who were screened for these two clinical trials. Prevalence of depression was found to be highest among patients with diagnosis of AD at or before age 65, women, and whites in our AD patient sample.

OII-A-2The use of a clinical utility index in decision making to select an insomnia compound

Based on the results of the Phase 2 trials in insomnia patients, one out of 2 compounds was to be selected for further development. A CUI was developed based on data from Compound 1. The CUI is an integrated measure of clinical benefit/risk over the dose‐range and was proposed as a tool to compare compounds.