A Decade On: Systematic Review of ClinicalTrials.gov Infectious Disease Trials, 2007-2017.

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2019-06

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Abstract

Background:Registration of interventional trials of Food and Drug Administration-regulated drug and biological products and devices became a legal requirement in 2007; the vast majority of these trials are registered in ClinicalTrials.gov. An analysis of ClinicalTrials.gov offers an opportunity to define the clinical research landscape; here we analyze 10 years of infectious disease (ID) clinical trial research. Methods:Beginning with 166 415 interventional trials registered in ClinicalTrials.gov from 2007-2017, ID trials were selected by study conditions and interventions. Relevance to ID was confirmed through manual review, resulting in 13 707 ID trials and 152 708 non-ID trials. Results:ID-related trials represented 6.9%-9.9% of all trials with no significant trend over time. ID trials tended to be more focused on treatment and prevention, with a focus on testing drugs, biologics, and vaccines. ID trials tended to be large, randomized, and nonblinded with a greater degree of international enrollment. Industry was the primary funding source for 45.2% of ID trials. Compared with the global burden of disease, human immunodeficiency virus/AIDS and hepatitis C trials were overrepresented, and lower respiratory tract infection trials were underrepresented. Hepatitis C trials fluctuated, keeping with a wave of new drug development. Influenza vaccine trials peaked during the 2009 H1N1 swine influenza outbreak. Conclusions:This study presents the most comprehensive characterization of ID clinical trials over the past decade. These results help define how clinical research aligns with clinical need. Temporal trends reflect changes in disease epidemiology and the impact of scientific discovery and market forces. Periodic review of ID clinical trials can help identify gaps and serve as a mechanism to realign resources.

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10.1093/ofid/ofz189

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Jaffe, Ian S, Karen Chiswell and Ephraim L Tsalik (2019). A Decade On: Systematic Review of ClinicalTrials.gov Infectious Disease Trials, 2007-2017. Open forum infectious diseases, 6(6). p. ofz189. 10.1093/ofid/ofz189 Retrieved from https://hdl.handle.net/10161/19462.

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Scholars@Duke

Tsalik

Ephraim Tsalik

Adjunct Associate Professor in the Department of Medicine

My research at Duke has focused on understanding the dynamic between host and pathogen so as to discover and develop host-response markers that can diagnose and predict health and disease.  This new and evolving approach to diagnosing illness has the potential to significantly impact individual as well as public health considering the rise of antibiotic resistance.

With any potential infectious disease diagnosis, it is difficult, if not impossible, to determine at the time of presentation what the underlying cause of illness is.  For example, acute respiratory illness is among the most frequent reasons for patients to seek care. These symptoms, such as cough, sore throat, and fever may be due to a bacterial infection, viral infection, both, or a non-infectious condition such as asthma or allergies.  Given the difficulties in making the diagnosis, most patients are inappropriately given antibacterials.  However, each of these etiologies (bacteria, virus, or something else entirely) leaves a fingerprint embedded in the host’s response. We are very interested in finding those fingerprints and exploiting them to generate new approaches to understand, diagnose, and manage disease.

These principles also apply to sepsis, defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Just as with acute respiratory illness, it is often difficult to identify whether infection is responsible for a patient’s critical illness.  We have embarked on a number of research programs that aim to better identify sepsis; define sepsis subtypes that can be used to guide future clinical research; and to better predict sepsis outcomes.  These efforts have focused on many systems biology modalities including transcriptomics, miRNA, metabolomics, and proteomics.  Consequently, our Data Science team has utilized these highly complex data to develop new statistical methods, furthering both the clinical and statistical research communities.

These examples are just a small sampling of the breadth of research Dr. Tsalik and his colleagues have conducted.  

In April 2022, Dr. Tsalik has joined Danaher Diagnostics as the VP and Chief Scientific Officer for Infectious Disease, where he is applying this experience in biomarkers and diagnostics to shape the future of diagnostics in ID. 


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