scholarly journals Pharmaceutical R & D pipeline management under trial duration uncertainty

2020 ◽  
Vol 136 ◽  
pp. 106782 ◽  
Author(s):  
Elvan Gökalp ◽  
Juergen Branke
Keyword(s):  
Trial Duration ◽  
Pipeline Management ◽  
Duration Uncertainty

scholarly journals Detection of Alzheimer’s Disease-Related Cognitive Change With the Mobile Cognitive App Performance Platform

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 801-801
Author(s):  
Dawn Mechanic-Hamilton ◽  
Sean Lydon ◽  
Alexander Miller ◽  
Kimberly Halberstadter ◽  
Jacqueline Lane ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Memory Load ◽  
Memory Task ◽  
Structural Mri ◽  
Cognitive Change ◽  
Difficulty Level ◽  
Trial Duration ◽  
Parahippocampal Cortex ◽  
Relationship Of

Abstract This study investigates the psychometric properties of the mobile cognitive app performance platform (mCAPP), designed to detect memory changes associated with preclinical Alzheimer’s Disease (AD). The mCAPP memory task includes learning and matching hidden card pairs and incorporates increasing memory load, pattern separation features, and spatial memory. Participants included 30 older adults with normal cognition. They completed the mCAPP, paper and pencil neuropsychological tests and a subset completed a high-resolution structural MRI. The majority of participants found the difficulty level of the mCAPP game to be “just right”. Accuracy on the mCAPP correlated with performance on memory and executive measures, while speed of performance on the mCAPP correlated with performance on attention and executive function measures. Longer trial duration correlated with measures of the parahippocampal cortex. The relationship of mCAPP variables with molecular biomarkers, at-home and burst testing, and development of additional cognitive measures will also be discussed.

scholarly journals Creation of a database to assess effects of omega-3, omega-6 and total polyunsaturated fats on health: methodology for a set of systematic reviews

BMJ Open ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. e029554 ◽  
Author(s):  
Lee Hooper ◽  
Asmaa Abdelhamid ◽  
Julii Brainard ◽  
Katherine H O Deane ◽  
Fujian Song
Keyword(s):  
Health Outcomes ◽  
Systematic Reviews ◽  
Sensitivity Analyses ◽  
Omega 3 ◽  
Alpha Linolenic Acid ◽  
Trial Duration ◽  
Omega 6 ◽  
3 Omega ◽  
Meta Analyses ◽  
Total Pufa

ObjectiveTo create a database of long-term randomised controlled trials (RCTs) comparing higher with lower omega-3, omega-6 or total polyunsaturated fatty acid (PUFA), regardless of reported outcomes, and to develop methods to assess effects of increasing omega-6, alpha-linolenic acid (ALA), long-chain omega-3 (LCn3) and total PUFA on health outcomes.DesignSystematic review search, methodology and meta-analyses.Data sourcesMedline, Embase, CENTRAL, WHO International Clinical Trials Registry Platform, Clinicaltrials.gov and trials in relevant systematic reviews.Eligibility criteriaRCTs of ≥24 weeks' duration assessing effects of increasing ALA, LCn3, omega-6 or total PUFAs, regardless of outcomes reported.Data synthesisMethods included random-effects meta-analyses and sensitivity analyses. Funnel plots were examined, and subgrouping assessed effects of intervention type, replacement, baseline diabetes risk and use of diabetic medications, trial duration and dose. Quality of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation (GRADE).ResultsElectronic searches generated 37 810 hits, de-duplicated to 19 772 titles and abstracts. We assessed 2155 full-text papers, conference abstracts and trials registry entries independently in duplicate. Included studies were grouped into 363 RCTs comparing higher with lower omega-3, omega-6 and/or total PUFA intake of at least 6 months’ duration—the Database.Of these 363 included RCTs, 216 RCTs were included in at least one of our reviews of health outcomes, data extracted and risk of bias assessed in duplicate. Ninety five RCTs were included in the Database but not included in our current reviews. Of these 311 completed trials, 27 altered ALA intake, 221 altered LCn3 intake and 16 trials altered omega-3 intake without specifying whether ALA or LCn3. Forty one trials altered omega-6 and 59 total PUFA.The remaining 52 trials are ongoing though 13 (25%) appear to be outstanding, or constitute missing data.ConclusionsThis extensive database of trials is available to allow assessment of further health outcomes.

Implementing a Deepwater Pipeline Management System

2013 ◽  
Author(s):  
Herve Gueveneux ◽  
Laufer Theo Manongtong Samosir ◽  
Alain Lechon ◽  
Dominique Popineau
Keyword(s):  
Management System ◽  
Pipeline Management

A unified approach to power and sample size determination for log-rank tests under proportional and nonproportional hazards

2021 ◽  
pp. 096228022098857
Author(s):  
Yongqiang Tang
Keyword(s):  
Sample Size ◽  
Proportional Hazards ◽  
Sample Size Calculation ◽  
Unified Approach ◽  
Rank Tests ◽  
Trial Duration ◽  
Nonproportional Hazards ◽  
Equivalence Trials ◽  
Superiority Trials ◽  
Log Rank Tests

Log-rank tests have been widely used to compare two survival curves in biomedical research. We describe a unified approach to power and sample size calculation for the unweighted and weighted log-rank tests in superiority, noninferiority and equivalence trials. It is suitable for both time-driven and event-driven trials. A numerical algorithm is suggested. It allows flexible specification of the patient accrual distribution, baseline hazards, and proportional or nonproportional hazards patterns, and enables efficient sample size calculation when there are a range of choices for the patient accrual pattern and trial duration. A confidence interval method is proposed for the trial duration of an event-driven trial. We point out potential issues with several popular sample size formulae. Under proportional hazards, the power of a survival trial is commonly believed to be determined by the number of observed events. The belief is roughly valid for noninferiority and equivalence trials with similar survival and censoring distributions between two groups, and for superiority trials with balanced group sizes. In unbalanced superiority trials, the power depends also on other factors such as data maturity. Surprisingly, the log-rank test usually yields slightly higher power than the Wald test from the Cox model under proportional hazards in simulations. We consider various nonproportional hazards patterns induced by delayed effects, cure fractions, and/or treatment switching. Explicit power formulae are derived for the combination test that takes the maximum of two or more weighted log-rank tests to handle uncertain nonproportional hazards patterns. Numerical examples are presented for illustration.

Abstract TP292: Effect of Improved Management Strategies on Study Retention Rates

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Michael Dela Cruz ◽  
Kinga Aitken ◽  
Ka-Ho Wong ◽  
Theodore Rock ◽  
Jennifer J Majersik
Keyword(s):  
Clinical Research ◽  
Research Team ◽  
Retention Rate ◽  
Management Strategies ◽  
Retention Rates ◽  
Stroke Patients ◽  
Trial Duration ◽  
Implementation Period ◽  
Stroke Center ◽  
Stroke Trial

Introduction: Average national dropout rates of participants enrolled in a research trial are reported to be 30%. Factors contributing to loss of stroke patient retention include the lack of understanding of study expectations, lack of relationship building between patient and clinical research team, and inefficient management processes. There has been little research into interventions to improve retention. Focusing on these 3 factors may increase the likelihood of stroke patients adhering to and completing participation in stroke trials. The University of Utah Stroke Center became a StrokeNet regional coordinating center in October 2013. As study trials increased, we recognized the need to implement new trial management strategies and did so in January 2016. Methods: Stroke trial metrics were compared between the pre-implementation period (7/1/2012 - 12/31/2015) and a post-implementation period (1/7/2016 - 7/1/2019). The size of clinical research team personnel remained the same across the two periods: 4 coordinators and 9 physicians. Standardization of enrollment processes in stroke trials occurred during the post-implementation period. Three key aspects addressed in the post-implementation period were building rapport, setting realistic expectations, and properly educating patient and family members. The clinical research team incorporated these factors when approaching patients regardless of type of stroke trial (acute, subacute, or observational). Results: During the pre-implementation period, the Stroke Center research team managed 8 stroke studies with 52 patients consented with average trial duration of 23 months (SD); in the post-implementation period, there were 15 studies with 99 patients consented, with average trial duration of 22 months (SD). Retention improved after the intervention from a mean (SD) retention rate of 79.5 (29.7) %. to 90.8 (17.2) %. Although this difference was not significant, it represented meaningful change to the research staff and helped us achieve StrokeNet retention goals. Conclusion: Implementation of effective management strategies leads to higher retention rates of stroke patients despite no change in the size of the clinical research team.

scholarly journals Penggunaan Daun Ubi Kayu (Manihot esculenta) dengan Pengolahan Berbeda terhadap Blood Urea Nitrogen Kambing Peranakan Etawa Jantan

2020 ◽  
Vol 4 (2) ◽  
pp. 23-29
Author(s):  
Okni Winda Artanti ◽  
◽  
Silvia Andriani
Keyword(s):  
Blood Urea Nitrogen ◽  
Crude Protein ◽  
Block Design ◽  
Protein Digestibility ◽  
Crude Fiber ◽  
Fiber Intake ◽  
Trial Duration ◽  
Urea Nitrogen ◽  
Cassava Leaves ◽  
Range Test

The objective of this experiment was to evaluate the effect of fresh, dried or silage cassava leaf to the blood urea nitrogen (BUN) of male Etawa Crossbreed (EC) goats. Twelve EC goats (grouping based on body weight with a weight range K1: 19-20 kg; K2: 20-21 kg; K3: 21-22 kg; K4: 22 kg) were allocated in housed individually throughout 90-day trial duration (14 days for animal's adaptation to the experimental diets and 7 days of faeces collection). Experimental design was randomized complete block design consisted of 3 treatments and 4 replications: concentrate + fresh cassava leaf (P0); concentrate + dried cassava leaf (P1); and concentrate + silage cassava leaf (P2). Concentrat was given at level of 50% (3% BW) and forage was given ad libitum respectively for each treatments. Variables observed were crude fiber intake, crude fiber digestibility, crude protein digestibility and blood urea nitrogen (BUN). Data were analyzed using analysis of variance (ANOVA), if there were significant effect of treatments were continued using duncan multiple range test. The results of this experiment showed that the processing of cassava leaves increased on crude fiber intake, crude fiber and crude protein digestibibility, but did not effect on blood urea nitrogen (BUN). In conclusion, processing of cassava leaves improved the consumption, digestibility but did not effect on blood urea nitrogen (BUN) of EC goats. Keywords: Blood Urea Nitrogen, Cassava Leaf, Male Etawa Crossbreed Goat

scholarly journals Modeling Clinical Trial Attrition Using Machine Intelligence: A driver analytics case study using 1,325 trials representing one million patients

2021 ◽  
Author(s):  
Emmette Hutchison ◽  
Sreenath Nampally ◽  
Imran Khan Neelufer ◽  
Youyi Zhang ◽  
Jim Weatherall ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Machine Intelligence ◽  
Duration Of Treatment ◽  
Trial Duration ◽  
Major Barrier ◽  
Clinical Phase ◽  
Successful Execution ◽  
Patient Attrition ◽  
Data Driven Approach

The amount of time and resources invested in bringing novel therapeutics to market has increased year over year with fewer successful treatments reaching patients. In the lifecycle of drug development, the clinical phase is a major contributor to this decreasing efficiency in the development of clinical trials. One major barrier to the successful execution of a randomized control trial (RCT) is the attrition of patients who no longer participate in a trial either following enrollment or randomization. To address this problem, we have assembled a unique dataset by integrating multiple public databases including ClinicalTrials.gov and Aggregate Analysis of ClincalTrials.gov (AACT) to assemble a trial sponsor-independent dataset. This data spans 20 years of clinical trials and over 1 million patients (3,175 cohorts consisting of 1,020,085 patients and 79 curated features) in the respiratory domain and enabled a data-driven approach to identify top features influencing patient attrition in a trial. Top Features included Duration of Trial, Duration of Treatment, Indication, and Number of Adverse Events. We evaluated multiple machine learning models and found the best performance on the Test Set with Random Forest (Test subset: n=637 cohorts; RMSE 6.64). We envisage that our work will enable clinical trial sponsors to optimize trial run time by better anticipating and correcting for potential patient attrition using patient-centric strategies to improve patient engagement, thus enabling new therapies to be delivered to patients more quickly.

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