scholarly journals Pharmacogenomics in clinical practice and drug development

2012 ◽  
Vol 30 (11) ◽  
pp. 1117-1124 ◽  
Author(s):  
Andrew R Harper ◽  
Eric J Topol
Keyword(s):  
Clinical Practice ◽  
Drug Development

scholarly journals Quantitative analysis of the placebo response in pharmacotherapy of insomnia and its application in clinical trials

SLEEP ◽  
2019 ◽  
Vol 43 (5) ◽  
Author(s):  
Xijun Zheng ◽  
Yingchun He ◽  
Ling Xu ◽  
Yunfei Li ◽  
Fang Yin ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Drug Development ◽  
Sleep Onset ◽  
Placebo Response ◽  
Sleep Diary ◽  
Cochrane Library ◽  
Design Decision ◽  
Response Models ◽  
Sleep Parameters ◽  
Baseline Levels

Abstract Study Objectives This study aimed to develop a robust placebo response model for the pharmacotherapy for insomnia to guide drug development and clinical practice. Methods PubMed, EMBASE, and Cochrane Library databases were systematically searched for randomized placebo-controlled trials of medications for insomnia dating from the inception dates of the databases to April 18, 2018. Three placebo response models were established to describe the time–course of sleep parameters measured by objective (polysomnography or actigraphy) or subjective methods (sleep diary or questionnaires). The established models were applied to simulate placebo response distribution under different conditions using Monte Carlo simulations. Results Fifty-four studies involving 6,416 subjects were included. Placebo response increased over time and reached a plateau at approximately 8 weeks from start of therapy. Established models described the observed data reasonably well based on various diagnostic plots. Baseline sleep parameters affected the placebo response. There were significant positive correlations with placebo response and the severity of sleep latency, wake after sleep onset, and total sleep time at baseline. In addition, placebo response, assessed by subjective and objective methods, was consistent after correcting the baseline levels. Conclusions The established placebo response models can serve as a tool to predict placebo response at different baseline levels, which can provide valuable reference for clinical trial design, decision-making in drug development, and clinical practice.

scholarly journals Unorthodox Parenteral β-Lactam and β-Lactamase Inhibitor Combinations: Flouting Antimicrobial Stewardship and Compromising Patient Care

2020 ◽  
Vol 64 (5) ◽  
Author(s):  
Snehal Palwe ◽  
Balaji Veeraraghavan ◽  
Hariharan Periasamy ◽  
Kshama Khobragade ◽  
Arun S. Kharat
Keyword(s):  
Clinical Practice ◽  
Drug Development ◽  
Patient Care ◽  
Clinical Outcomes ◽  
Antimicrobial Stewardship ◽  
Fixed Dose ◽  
Resistance Development ◽  
Safety And Efficacy ◽  
India And China ◽  
Lactamase Inhibitor

ABSTRACT In India and China, indigenous drug manufacturers market arbitrarily combined parenteral β-lactam and β-lactamase inhibitors (BL-BLIs). In these fixed-dose combinations, sulbactam or tazobactam is indiscriminately combined with parenteral cephalosporins, with BLI doses kept in ratios similar to those for the approved BL-BLIs. Such combinations have been introduced into clinical practice without mandatory drug development studies involving pharmacokinetic/pharmacodynamic, safety, and efficacy assessments being undertaken. Such unorthodox combinations compromise clinical outcomes and also potentially contribute to resistance development.

scholarly journals Scientific Challenges and Implementation Barriers to Translation of Pharmacogenomics in Clinical Practice

2013 ◽  
Vol 2013 ◽  
pp. 1-17 ◽  
Author(s):  
Y. W. Francis Lam
Keyword(s):  
Clinical Practice ◽  
Drug Therapy ◽  
Drug Development ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Field Work ◽  
Current Approach ◽  
Therapeutic Area ◽  
Implementation Barriers ◽  
Public Expectation

The mapping of the human genome and subsequent advancements in genetic technology had provided clinicians and scientists an understanding of the genetic basis of altered drug pharmacokinetics and pharmacodynamics, as well as some examples of applying genomic data in clinical practice. This has raised the public expectation that predicting patients’ responses to drug therapy is now possible in every therapeutic area, and personalized drug therapy would come sooner than later. However, debate continues among most stakeholders involved in drug development and clinical decision-making on whether pharmacogenomic biomarkers should be used in patient assessment, as well as when and in whom to use the biomarker-based diagnostic tests. Currently, most would agree that achieving the goal of personalized therapy remains years, if not decades, away. Realistic application of genomic findings and technologies in clinical practice and drug development require addressing multiple logistics and challenges that go beyond discovery of gene variants and/or completion of prospective controlled clinical trials. The goal of personalized medicine can only be achieved when all stakeholders in the field work together, with willingness to accept occasional paradigm change in their current approach.

scholarly journals Erratum: Corrigendum: Pharmacogenomics in clinical practice and drug development

2012 ◽  
Vol 30 (12) ◽  
pp. 1249-1249 ◽  
Author(s):  
Andrew R Harper ◽  
Eric J Topol
Keyword(s):  
Clinical Practice ◽  
Drug Development
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