About Sollers

Sollers is a graduate school located in New Jersey, specializing in clinical research, drug safety and pharmacovigilance training.

Our graduate certificate and masters programs cover a wide range of subjects tailored to this fast growing industry, and our graduates go on to highly successful careers in the pharmaceuticals industry and healthcare industries.

  • HOURS
  • Monday - Thursday | 10 AM - 7 PM
  • Friday | 12 PM - Midnight
  • Saturday | 12 PM - Midnight
  • Sunday | Closed
  • OPEN 24/7 - sollers.edu
    • PHONE
    • (848) 299-5900
    • Location
    • 100 Menlo Park, Suite 550
      Edison New Jersey 08837 -2488

Location

Call Us Now: 848 299-5900

Sollers Blog

Phil

Recent Posts

Semantic Indexing Along With Deep Learning

Posted by Phil on Aug 16, 2017 11:14:05 AM

One of the main areas that are trending in the research sectors of Machine Learning and Pattern Recognition is Deep Learning (DL). DL focuses on Machine Learning tools and techniques and applies them in resolving complications which lack human or artificial thoughts and could be achieved in data science. DL is achieved by learning over a cascade of many layers. DL handles many real world complications, such as Machine Translation, Object Recognition, and Localization, Speech Recognition, Image caption generation, Distributed representation for text, Natural Language Processing, Image Classification, etc., with its data-driven representation learning. The traditional computing is facing challenges in dealing with high-dimensional and streaming data, semantic indexing, and scalability of models.

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Topics: Data Science

Methods of Big data Preprocessing

Posted by Phil on Aug 11, 2017 1:11:36 PM

The presence of data preprocessing methods for data mining has been reviewed over the past few years with a lot of high volumes, velocity, and a variety of data that require a new high-performance processing. A large computational infrastructure in big data along with a challenging and time-demanding task is involved to ensure successful data processing and analysis. Approaches in big data comprise of definition, characteristics, and categorization of data preprocessing. There is a huge connection between big data and data preprocessing throughout all families of methods and big data technologies and everything will be examined including developments on different big data framework, such as Hadoop, Spark and Flink and the encouragement in devoting substantial research efforts in some families of data preprocessing methods and applications on new big data learning paradigms.

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Topics: Data Science

Protocol Procedure Complexity In Clinical Trial

Posted by Phil on Aug 7, 2017 11:37:37 AM

Over the past few years, an increasing protocol complexity has garnered a lot of attention among clinical trial experts. It has lead to various important studies beginning from meditating insights metrics warehouse which reveal that clinical studies have reached to a significant level of complexity in the recent times. In spite of a larger increase in metrics in the first half of the past decade and continued warnings from experts, the complexity continues to be on an upward surge through admittedly less steep and trends. A quantifiable or reputable measure of effort is necessary to conduct a study on the protocol complexity value which was supposedly a new addition to Medidata Insights metrics warehouse. There is a factor called Relative Value Unit (RVU) and it will be multiplied by the quantity of each trial procedure and clinical research activity conducted per completed patient. The result of this calculation will be used for the association of burden on sited and to conduct relevant studies.

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Topics: Clinical Research

List of Data Analysis Tools!

Posted by Phil on Aug 1, 2017 3:33:43 PM

Data analyses tools for different purposes are classified into various categories to facilitate finalization and visualization of data including social networks and to perform optimization. The tools also help to search efficient and relevant information besides solving numerous data analysis issues. Here are some of such potential data analyses tools.

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Topics: Data Science

Risk Based Monitoring

Posted by Phil on Jul 27, 2017 2:19:34 PM

Join the Program on Risk Based Monitoring (RBM)  

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Topics: Clinical Research

Tips for Chemical Inventory Management

Posted by Phil on Jul 26, 2017 1:23:01 PM

Having an organized inventory is the key for your overall chemical management initiatives and adherence to GHS compliance. You should have periodic inventories on what chemicals you have on the site, besides documenting where these chemicals are located, while making sure that accurate and up to date safety data (SDS) is in place.

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Topics: Drug Safety

Five Habits Of Successful Analysts

Posted by Phil on Jul 20, 2017 12:00:03 PM

Five habits of successful analysts are keeping a high bar on project delivery by walking that extra mile and delivering your best, the segment you can; triangulate numbers and think what do they mean for business, testing out your hypothesis even if you think they make complete business sense and learning something about analytics every day. Now let us see elaborately, what these five habits are.

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Topics: Data Science

Economic Impact on Drug Safety and Pharmacovigilance

Posted by Phil on Jul 12, 2017 3:46:28 PM

Drugs can enter the market only when these are found safe for use. Pharmacovigilance and safety of any drug is crucial to any clinical research.  It includes many aspects of well-being of the patient, trust, and confidence in the pharmaceutical industry and the field of medicine. Another important facet is the economic impact of drugs and drug safety issues.

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Topics: Drug Safety

Data Integrity Risk and How to mitigate it

Posted by Phil on Jul 5, 2017 2:44:03 PM

FDA defines Data Integrity as data, which is complete, consistent and accurate. It further defines data integrity as data, which is -

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Topics: Data Science

Technical Aspect of Data Mining

Posted by Phil on Jun 23, 2017 12:54:49 PM

Data Mining is a science of unearthing hidden patterns and relationships within your data to help you take better business decisions. It can help you in spotting sale trends, developing marketing campaigns or predicting customer churn. It has several applications in today’s business, which is required to deal with a large amount of data. Data mining requires a Data Warehouse as a source of data. Principles of data mining have been around for a while, but they have gained prominence with the advent of Big Data and Data Analytics.

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Topics: Data Science