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Mobile Health, Wireless Data and the Future of Clinical Trials

Mobile Health, Wireless Data and the Future of Clinical Trials | Clinical Trials | Scoop.it
When we talk to patients about the challenges they face while participating in clinical trials, they tell us that it can be difficult to integrate the study's requirements into their everyday lives...
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Access to clinical trial data: the Italian perspective - Lexology (registration)

Access to clinical trial data: the Italian perspective - Lexology (registration) | Clinical Trials | Scoop.it
Access to clinical trial data: the Italian perspective
Lexology (registration)
There is an increasing trend towards full publication of data resulting from clinical trials sponsored by the pharmaceutical industry.
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Quintiles Wins Society for Clinical Research Sites' 2013 Eagle Award - Wall Street Journal

Quintiles Wins Society for Clinical Research Sites' 2013 Eagle Award - Wall Street Journal | Clinical Trials | Scoop.it
Quintiles Wins Society for Clinical Research Sites' 2013 Eagle Award Wall Street Journal Quintiles today announced that the company has been awarded the Society for Clinical Research Sites' (SCRS) 2013 Clinical Research Organization (CRO) Eagle...
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Clinical Trials: What You Don't Know Can Hurt You - DrugWatch.com

Clinical Trials: What You Don't Know Can Hurt You - DrugWatch.com | Clinical Trials | Scoop.it
DrugWatch.com Clinical Trials: What You Don't Know Can Hurt You DrugWatch.com Since the mid-twentieth century, clinical trials employing human volunteers have drastically altered the landscape of modern medicine, improving our collective...
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Shutdown Prompts Fear, Confusion Among Cancer Patients

Shutdown Prompts Fear, Confusion Among Cancer Patients | Clinical Trials | Scoop.it
Patients and doctors fear the shutdown will hamper treatment, research.
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Quorum IRB Board Chair to Speak at South Korean Research Summit - PR Web (press release)

Quorum IRB Board Chair to Speak at South Korean Research Summit - PR Web (press release) | Clinical Trials | Scoop.it
Quorum IRB Board Chair to Speak at South Korean Research Summit PR Web (press release) It's an honor to be representing Quorum Review IRB in South Korea at this prestigious event, and I am looking forward to contributing to the international...
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Training the pharma sales rep for a digital age

Training the pharma sales rep for a digital age | Clinical Trials | Scoop.it
As every pharma company invests in digital technology to arm its sales force for more efficient prescriber engagement, MXM Health kicks off a three-part series exploring whether we are overlooking the potential of such techniques for internal...

Via Nikos Papaioannou, eMedToday
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Dan Baxter's curator insight, September 22, 2013 4:31 PM

Interesting  theory but doesn't mention the requirement for a better understanding of exactly which new channels customers are using to get their clinical information from...

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Indian firms get FDA approval for 110 generic drugs

Indian firms get FDA approval for 110 generic drugs | Clinical Trials | Scoop.it
Drugmakers from India, the biggest overseas source of medicines sold in the US, have got more than 100 generic drug approvals from the American health regulator FDA this year so far.

Via Amar Bhat
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Amar Bhat's curator insight, September 16, 2013 2:19 PM

Indian firms have 40% of U.S. generics market, foreign firms have 77% of Indian drug patents.  Its a battle of volume (India) vs. value (foreign).  Where is the future in this?

 

The future is in value.  India can and will get undercut on low labor costs, which is the competitive edge that India brings to the pharma game, while it virtually ignores the innovative market. In the meantime, a single innovator company can make more than the entire Indian pharma industry with one or two blockbusters.  Who is the winner there?

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Pharma fixed in online traffic patterns, despite distrust survey

Pharma fixed in online traffic patterns, despite distrust survey | Clinical Trials | Scoop.it
A good percentage of consumers are open to visiting a pharmaceutical company website, an online survey shows, despite a persistent undercurrent of distrust for industry.

Via Philippe Marchal, Lionel Reichardt / le Pharmageek
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Cancer and Clinical Trials: The Role of Big Data In Personalizing the Health Experience

Cancer and Clinical Trials: The Role of Big Data In Personalizing the Health Experience | Clinical Trials | Scoop.it
Cancer and Clinical Trials: The Role of Big Data In Personalizing the Health Experience (via Strata – Making Data Work)
This article was written with Ellen M. Martin and Tobi Skotnes. Dr.

Via Emmanuel Capitaine
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Clinical Trials and Social Networking | IVT - GCP

Clinical Trials and Social Networking | IVT - GCP | Clinical Trials | Scoop.it
The aim of this paper was to determine if this new social media innovation has been widely accepted by the pharmaceutical and CRO industry as a potential patient recruitment tool for clinical trials.
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ACRES Launches Global Clinical Research Network Technology Platform - San Francisco Chronicle (press release)

ACRES Launches Global Clinical Research Network Technology Platform - San Francisco Chronicle (press release) | Clinical Trials | Scoop.it
ACRES Launches Global Clinical Research Network Technology Platform San Francisco Chronicle (press release) The Alliance for Clinical Research Excellence and Safety (ACRES), together with two of its strategic technology allies, ViS Research (ViS)...
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Representation of Older People in Clinical Trials - PR Web (press release)

Representation of Older People in Clinical Trials - PR Web (press release) | Clinical Trials | Scoop.it
PR Web (press release) Representation of Older People in Clinical Trials PR Web (press release) Challenges which include co-morbidities, polypharmacy drug-drug interactions, adherence formulation challenges are just some of the difficulties faced...
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Garlic: A Simple Way to Protect Your Heart - ProHealth

Garlic: A Simple Way to Protect Your Heart - ProHealth | Clinical Trials | Scoop.it
ProHealth
Garlic: A Simple Way to Protect Your Heart
ProHealth
Clinical studies and overall reports about garlic have been very positive. In a recent overall analysis of 26 ...
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More than 100 clinical trials now underway in Nebraska

More than 100 clinical trials now underway in Nebraska | Clinical Trials | Scoop.it
There are more than one hundred clinical trials currently taking place in Nebraska. Jeff Trewhitt is the author of the report, “Pharmaceutical Clinical Trials in Nebraska” and says nearly everyone in the state benefits.
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Online Social Networking as an Alternative Information Source for Clinical Research

Online Social Networking as an Alternative Information Source for Clinical Research | Clinical Trials | Scoop.it

Background
Clinical trials and patient records have been the main information sources for clinical research. While well-designed clinical trials can produce high quality data, they are generally very expensive and time consuming. Further, patients enrolled in clinical trials are not necessarily representative of the intended patient population. Chart reviews avoid some of the drawbacks of the clinical trial approach. However, studies that use chart reviews are limited by the accuracy and completeness of the data in the patient records. In the past decade, online social networks have grown exponentially. We hypothesized that information from online social networks has the potential to serve a new and complementary information source for clinical research. To test this hypothesis, we conducted two separate studies. In the first study, we compared the prevalence of fatigue and depression for patients of amyotrophic lateral sclerosis (ALS), multiple sclerosis (MS) and Parkinson’s disease (PD), as reported on the online social network PatientsLikeMe and a large medical record data repository. In the second study, we compared clinicians’ and patients’ perspectives on the symptomatic treatment of ALS by comparing data from a traditional survey study of clinicians with data from a patient social network.

 

Methods
In the first study, multivariable logistic regression was performed on the probability of reporting fatigue or depression as predicted by age, gender, data source, type of neurological disease and the interaction of data source and type of neurological disease. We report on the effects of the interaction of data source and type of neurological disease on the probability of reporting fatigue or depression. Our analysis addresses whether the association of reporting fatigue and depression with disease type differs between the two data sources, and, equivalently, whether the association of reporting fatigue and depression with data source varies between disease types. These results are controlled for the effects of age and gender. In the second study, we first extracted the 14 symptoms and associated top four treatments and then selected twenty symptom-treatment pairs to compare the clinicians’ and patients’ perceptions of treatment prevalence and efficacy.

 

Results
In the first study, overall, both fatigue and depression were more likely to be reported if the data source was PatientsLikeMe regardless of disease. The odds for reporting fatigue and depression were greater from the PLM source across all diseases (i.e. PLM users are more likely to report fatigue and depression). The odds ratio for reporting fatigue was 33.9 for ALS, 36.3 for MS, and 18.7 for PD. The odds of reporting depression were 6.1 for ALS, 9.7 for MS, and 4.91 for PD. In the second study, similarities and discrepancies were found between clinicians’ and patients’ perceptions of treatment prevalence and efficacy. In 10 out of the 20 pairs, the symptom-treatment differences between the two groups were above 10%. In three pairs the differences were above 20%.

 

Conclusions
Online social network data, reflecting patients’ perspectives, do provide somewhat different information regarding symptoms and symptomatic treatment from the traditional research data sources like survey results and medical records.


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Jackie Carter's curator insight, August 21, 2014 1:20 AM

20. This article from the University of Utah shows a study where social media was used as an advantage to conduct research for clinical trials and patient records.
The results proved that social networking provided somewhat different information regarding symptoms and symptomatic treatment from the traditional research data sources like survey results and medical records.
I wanted to add this article in to my list as it links in a unique way with Online Social and Professional Networks and demonstrates the different ways social networking can be an advantage. The source is highly reliable as it is a scholarly resource. I have located this post at the bottom of my curated list; although it is interesting, there are other posts that prove to be more informative than this post.

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Big Data, Faster Clinical Trials -- InformationWeek

Big Data, Faster Clinical Trials -- InformationWeek | Clinical Trials | Scoop.it
Merck partnership with Israeli health system is another promising step toward using big data to speed up the process of finding qualified patients for clinical trials.
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How healthcare analytics can ensure delivery of high quality patient care

How healthcare analytics can ensure delivery of high quality patient care | Clinical Trials | Scoop.it

Healthcare vertical can leverage big data analytics to achieve better prognosis, effectively do remote patient monitoring and dig into combined clinical and genomics research data to suggest personalized treatments for patients

 

In a bid to deliver high quality healthcare care and improve patient satisfaction, public and private sector hospitals are today looking at streamlining workflow processes, integrating healthcare related data and securing information exchange. Like many developing nations, India too is exploring all ways and means in providing good, cost effective healthcare to its citizens. In doing so, healthcare organizations are increasingly realizing that IT solutions can actually help them meet this challenge by optimising resource allocation and plugging inefficiencies that cause delay in treatment. 

One of the technology solutions that can be leverage quite effectively by healthcare organizations is big data analytics which can go a long way in reducing the cost of healthcare care and improving patient outcomes which in turn could pave the way for a new age in healthcare. Let us look at some of the ways in which healthcare vertical could leverage big data and analytics for providing high quality of patient care both for inpatients and outpatients. 

Healthcare analytics

The healthcare industry is fast moving away from a paper based systems to Electronic Medical Record (EMR) systems. So far, much of this data was locked in a system designed to treat patients on an episodic fashion, and may not have contained the full longitudinal health record of the patient. But with the maturing of some solutions based on big data architectures, the ability to unlock and analyze this information is now possible. The Chief Medical Information Officer or Chief Research Officer  at many healthcare organizations are using these tools to derive scientific evidence that will help them validate the treatment being given to a patient as the most effective and efficient care at the best cost.

Remote patient monitoring 

In many countries, technology is enabling healthcare providers to closely monitor patients in their home on a real time basis. The care givers are monitoring home devices such as glucometers, weight scales, pedometers and others to understand how the patient is faring day to day. For example, if a patient is suffering from a chronic disease such as diabetes or congestive heart failure, the ability to monitor him for weight gain, blood sugar levels and exercise attempts will allow the care team to proactively contact the patient and provide help or recommend his report to an emergency room for immediate treatment if need be.

Another example where real time in-home devices can be used is, for independent living. Just because many countries are experiencing an ageing population, does not mean that the people will want to give up the ability to live alone. In such a situation having the ability to covertly monitor the person, with their permission, provides a level of safety to determine if someone has fallen, not gotten out of bed, or has been missing meals. 

The facilities to extend the healthcare system into the home of a person allows for a much better quality of life for the patient as well as to reduce operational cost for hospitals. However the volume and velocity of the data being collected, as well as the real time nature of the analysis and action require health care organisations to put in place a big data solution. 

Tapping into clinical and genomics research data for personalized treatments

Advances in medical technology have changed the way doctors monitor and treat patients. With the cost of DNA sequencing becoming affordable in many parts of the world, the emergence of personalized medicine is becoming a reality. There are many drug therapies that have been found to be effective for a certain group of patients with specific gene expressions. The ability to determine if a patient has the genetic gene expression before treatment begins allows for a better prognosis. 

Many research institutes, academic medical centres, drug makers and contract research organization are looking for technology solutions that will help them combine clinical and genomics research data in order to determine the effectiveness of personalized treatments.  In order to achieve this, many hospitals will be looking at adopting solutions such as big data analytics, over the next few years.

No-where is the transformative power of big data analytics more meaningful than in the health care sector. The need is to identify the potential that big data analytics holds in itself to transform the way healthcare vertical has been traditionally responding to the patients needs, so far.


Via Chatu Jayadewa
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Social Media Release Increases Dissemination of Original Articles in the Clinical Pain Sciences

Social Media Release Increases Dissemination of Original Articles in the Clinical Pain Sciences | Clinical Trials | Scoop.it

A barrier to dissemination of research is that it depends on the end-user searching for or ‘pulling’ relevant knowledge from the literature base. Social media instead ‘pushes’ relevant knowledge straight to the end-user, via blogs and sites such as Facebook and Twitter. That social media is very effective at improving dissemination seems well accepted, but, remarkably, there is no evidence to support this claim. We aimed to quantify the impact of social media release on views and downloads of articles in the clinical pain sciences.

 

Sixteen PLOS ONE articles were blogged and released via Facebook, Twitter, LinkedIn and ResearchBlogging.org on one of two randomly selected dates. The other date served as a control. The primary outcomes were the rate of HTML views and PDF downloads of the article, over a seven-day period. The critical result was an increase in both outcome variables in the week after the blog post and social media release. The mean ± SD rate of HTML views in the week after the social media release was 18±18 per day, whereas the rate during the other three weeks was no more than 6±3 per day. The mean ± SD rate of PDF downloads in the week after the social media release was 4±4 per day, whereas the rate during the other three weeks was less than 1±1 per day (p<0.05 for all comparisons).

 

However, none of the recognized measures of social media reach, engagement or virality related to either outcome variable, nor to citation count one year later (p>0.3 for all). We conclude that social media release of a research article in the clinical pain sciences increases the number of people who view or download that article, but conventional social media metrics are unrelated to the effect.


We hypothesised that social media release of an original research article in the clinical pain sciences increases viewing and downloads of the article. The results support our hypothesis. In the week after the social media release, there were about 12 extra views of the HTML of the research article per day, and 3 extra downloads of the article itself per day, that we can attribute to the social media release. The effects were variable between articles, showing that multiple factors mediate the effect of a social media release on our chosen outcome variables. Although the absolute magnitude of the effect might be considered small (about 0.01% of people we reached were sufficiently interested to download the PDF), the effect size of the intervention was large (Cohen’s d >0.9 for both outcomes). The effect of social media release was probably smaller for our site, which is small, young and specialised, than it would be for sites with greater gravitas, for example NEJM or BMJ or indeed, PLOS.

Relationship between Reach and Impact

The idea of social media reach is fairly straightforward - it can be considered as the number of people in a network, for example the number of Facebook friends or Twitter followers. A blog may have 2,000 Facebook ‘likes’, 700 Twitter followers and 300 subscribers - a reach of three thousand people. Impact is less straightforward. The various definitions of social media each reflects a substantially larger population than our most proximal measure of impact – HTML views and PDF downloads of the original article. One might suggest that impact should reflect some sense of engagement with the material, for example the number of people within a network who make a comment on a post. From a clinical pain sciences perspective, change in clinical practice or clinician knowledge would be clear signs of impact, but such metrics are very difficult to obtain. Perhaps this is part of the reason that researchers are using, we believe erroneously, social media reach as a measure of social media impact.

 

There are now several social media options that researchers integrate into their overall ‘impact strategy’, for example listing their research on open non-subscription sites such as Mendeley, and joining discussions about research on social media sites such as Twitter and on blogs. Certainly, current measures of dissemination, most notably citations of articles or the impact factor of the journals in which they are published, do not take into account the social media impact of the article. New measurements, such as altmetrics and article-level metrics such as those provided by PLOS, aim to take into account the views, citations, social network conversations, blog posts and media coverage in an attempt to analyse the influence of research across a global community. There is merit in this pursuit, but, although our study relates to clinical pain sciences research, our results strongly suggest that we need to be careful in equating such measures with impact or influence, or using them as a surrogate for dissemination. Indeed, not even virality, which estimates the propensity of an item to ‘go viral’, was related with HTML views or PDF downloads.

 

This is very important because our results actually suggest that we may be measuring the wrong thing when it comes to determining the social media impact of research. That is, we showed a very clear effect of the social media release on both HTML views and PDF downloads of the target article. However, we did not detect any relationship between either outcome and the social media metrics we used. The only variable that related to either outcome was the number of HTML views, of the original blog post, in the week after social media release. It seems clear then, that it is not the total number of people you tell about your study, nor the number of people they tell, nor the number of people who follow you or who re-tweet your tweets. In fact, it appears that we are missing more of how the release improves dissemination than we are capturing.

 

The final result, that citation count did not relate to any social media measures, casts doubt over the intuitively sensible idea that social media impact reflects future citation-related impact. We used the Scopus citation count, taken almost 9 months after the completion of the experimental period, and 1–2 years after the publication date of the target articles, as a conventional measure of impact. There was no relationship between citation count and our measures of social media reach or virality. One must be cautious when interpreting this result because citation count so soon (1–2 years) after publication might be unlikely to capture new research that was triggered by the original article – although, importantly, journal impact factors are calculated on the basis of citations in the two years after publication. Suffice here to observe that the apparent popularity of an article on social media does not necessarily predict its short-term citation count.

 

Although this is the first empirical evaluation of social media impact in the clinical pain sciences and we have employed a conservative and robust design, we acknowledge several limitations. Social media dissemination in the clinical sciences relies on clinicians having access to, and using, social media. It will have no effect for those who do not use the web and who rely on more traditional means of dissemination - ‘pulling’ the evidence. Although there was an increase in HTML views and PDF downloads as a result of social media dissemination, we do not know if people read the article or whether it changed their practice. We presumed that a portion of those who viewed the HTML version of the article would then go onto download it, however our data suggest that a different pattern of access is occurring. Unfortunately, our data do not allow us to determine whether the same people both viewed the HTML and downloaded the article PDF or whether different people viewed the HTML and downloaded the article PDF. Downloading a PDF version of a paper does not necessarily imply that they would later read it, but it does increase the probability of such.

 

Citations and impact factors measure the impact within the scientific community whereas views by social media will also include interested clinicians and laypeople and, as such, measure uptake by different audiences. Although we used a variety of different social media platforms to disseminate to as wide an audience as possible, we do not know who the audience is - we can only surmise that they are a mixture of researchers, clinicians, people in pain and interested laypeople. Further, each social media strategy comes with inherent limitations in regards to data collection of usage statistics related to a blog post. Gathering Facebook and Twitter statistics for each article is still cumbersome and is probably not always accurate. The risk in using search engines to gather data is that there is no way of knowing whether all the data have been identified. For Twitter there is no way to retrospectively calculate the number of re-tweets accurately over a longer period retrospectively for each post.

 

As a result, our Twitter data is a best estimate and my have underestimated the true values but, critically, we would expect this effect to be unrelated to our blog post and therefore not impact on our findings. Regarding Facebook, shares, likes and comments are grouped as one statistic but in reality only shares and comments show engagement with the post and indicate that people are more likely to have read it. Regarding LinkedIn, the only available data was the number of members of the BodyInMind group and as such, we have no way of knowing how many viewed the actual blog post.

 

The blog, BodyInMind.org, through which the original blog posts of PLoS ONE articles were released, experienced a technical interruption half-way through the experiment. In spite of an attempt by PLOS to retrieve the statistics, approximately five days of data were lost on several of the blog posts. This also meant that additional data on traffic, such as percentage of traffic for each blog post from external sources such as Facebook, Twitter, LinkedIn and ResearchBlogging could not be measured during this period. Critically and fortuitously, this period did not coincide with data collection weeks. PLOS indicated that this technical problem has now been fixed, but similar problems may arise in the future and present an ongoing risk to studies such as ours. Although disconcerting for those keenly following social media data, this problem would be very unlikely to have affected our primary outcomes because none of our dates fell within the period that was affected.

 

Social influence can produce an effect whereby something that is popular becomes more popular and something that is unpopular becomes even less popular. It seems possible that articles on BodyInMind.org were shared because the site is popular among a discrete community and not because the article itself merited circulation. This possibility does not confound our main result but it adds a possible argument to the common objective of making a blog more popular as a device to boost social media impact of individual posts. Finally, our study relied on the target articles being freely available to the public. Many journals are not open access, particularly those in the clinical pain sciences. Therefore, we must be cautious extrapolating our results to subscription only access journals.

 

In conclusion, our results clearly support the hypothesis that social media can increase the number of people who view or download an original research article in the clinical pain sciences. However, the size of the effect is not related to conventional social media metrics, such as reach, engagement and virality. Our results highlight the difference between social media reach and social media impact and suggest that the latter is not a simple function of the former.



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Can Patient Reported Outcome (PRO) measure scores predict patient retention in clinical trials?

Can Patient Reported Outcome (PRO) measure scores predict patient retention in clinical trials? | Clinical Trials | Scoop.it
Our latest submission to the DIA 2014 Annual General Meeting Maintaining high levels of patient recruitment, adherence and retention is essential for the successful completion of a clinical trial, ...

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New electronic pump may increase heart failure survival

New electronic pump may increase heart failure survival | Clinical Trials | Scoop.it

Scientists have created a novel "electronic smart pump" that they say will "revolutionize" the treatment of patients suffering from chronic heart failure.


Researchers from the Nottingham Trent University and Nottingham University Hospitals NHS Trust in the UK say the smart aortic graft would be implanted in the patient's body and is entirely self-contained, eliminating the need for the patient to be hospitalized and wired to machinery.

 

 


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Why We Overeat -The Toxic Food Environment and Obesity

Why We Overeat -The Toxic Food Environment and Obesity | Clinical Trials | Scoop.it
Based on the latest science, this Forum event will examine how Americans can shift their food environments from toxic to healthy.

Via Giuseppe Fattori
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Quorum Review's Mitchell Parrish Presents at Embracing Change: Clinical ... - PR Web (press release)

Quorum Review's Mitchell Parrish Presents at Embracing Change: Clinical ... - PR Web (press release) | Clinical Trials | Scoop.it
Quorum Review's Mitchell Parrish Presents at Embracing Change: Clinical ...
PR Web (press release)
Quorum Review IRB, the industry leader in central IRB services, announces Mitchell E.
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Copper build up in brain 'could explain Alzheimer's dementia' - Medical News Today

Copper build up in brain 'could explain Alzheimer's dementia' - Medical News Today | Clinical Trials | Scoop.it
Nature World News Copper build up in brain 'could explain Alzheimer's dementia' Medical News Today But now a study that used cells from both mice and humans, led by Rashid Deane, a research professor in the University of Rochester Medical Center...
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ACRP and ACRES Create Strategic Alliance to Improve Conduct of Clinical Research - Applied Clinical Trials

ACRP and ACRES Create Strategic Alliance to Improve Conduct of Clinical Research - Applied Clinical Trials | Clinical Trials | Scoop.it
The Association of Clinical Research Professionals (ACRP) and the Alliance for Clinical Research Excellence and Safety (ACRES) have joined forces to address critical challenges facing the clinical research enterprise globally and to improve medical...
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