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

Data Capture Methods- eCOA and ePRO!

Posted by Phil on Sep 11, 2017 10:35:56 AM

Over the recent years, the data capture technology has influenced a large sector of business organizations in terms of novel approaches and seamless execution. Electronic clinical outcome assessments and Electronic patient report assessments follow methodologies that are appropriate for effective data capture mechanisms. Both of these technology-enabled methods project a comprehensive space into user's everyday lives for using their device-inclusive approach i.e. the data captured can be accessed from any internet connected device such as mobile phones, laptops, tablets, medical devices, and PCs.

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Topics: Data Science

Importance of Tableau in Data Analytics

Posted by Phil on Sep 1, 2017 2:32:06 PM

Tableau enables businesses to make decisions using the data visualization features available to business users of any background and Industry. It empowers businesses to keep up with the continuously evolving technology and outperform its competition through an innovative means of visualizing their data. There is not a single data source that Tableau fails to connect with. Let it be Data Warehouse, MS Excel or any web data, it establishes a connection with all of them. Basically, in any type of data analytics, Tableau provides an end to end insight by transforming data into visually engaging, interactive views in dashboards. With easy to use drag-and-drop interface one can come up with insights in few moments rather than months or years.

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Topics: Data Science

Recent trends in Neuromorphic Engineering

Posted by Phil on Aug 30, 2017 3:14:35 PM

Technology is changing the world at an unimaginable speed. It has been the greatest transformation tool in the modern world. From the age of Industrial revolution, the world has changed completely. Today, we cannot imagine our life without technology.

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Topics: Data Science

How Artificial Intelligence Is Helping The Pharmaceutical Industries?

Posted by Phil on Aug 23, 2017 3:53:09 PM

The current drug discovery process needs to shift dramatically in order to meet the needs of both the society and patients in the 21st Century. Artificial Intelligence and machine learning, in particular, present the pharmaceutical industry with a real opportunity to do R&D differently, so that it can operate more efficiently and substantially improve success at the early stages of drug development. There needs to be a fundamental shift in drug discovery and Artificial Intelligence holds the key to bringing the pharmaceutical industry into the 21st Century.

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Topics: Data Science

Data Integrity Risk and Mitigation!

Posted by Phil on Aug 22, 2017 12:46:00 PM

The United States Federal Drug Administration (USFDA) 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

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

What is SAS Enterprise Guide?

Posted by Doctor Erick on Aug 3, 2017 12:39:28 PM

SAS Enterprise Guide is a point-and-click, menu and wizard-driven tool, which provides fast-track learning for quick data analysis, generates code for productivity and speeds your ability to deploy analyses and forecasts in real time.

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Topics: Data Science

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

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