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

Mobile Data For Clinical Trial-2

Posted by Phil on Sep 15, 2017 4:22:53 PM

A new research report, published in the Journal of Medical Internet Research reveals that the mobile device (Mobile Technology) can effectively support a slew of things within the clinical research such as project management, data management, and telemonitoring, according to a mhealthintelligence.com report.

Read More

Topics: Clinical Research

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.

Read More

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.

Read More

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.

Read More

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.

Read More

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:

Read More

Topics: Data Science

The Importance Of Patient Centricity In Clinical Trials

Posted by Phil on Aug 18, 2017 12:52:56 PM

On a run to adopt new technologies and implement effective ways which could bring out possible changes in the healthcare industry a lot of innovative techniques have been introduced into the market.

Read More

Topics: Clinical Research

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.

Read More

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.

Read More

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.

Read More

Topics: Clinical Research