Blog – RxDataScience Inc. (3)

Top Use Cases for Machine Learning in Pharma

machine learning, pharma machine learning, artificial intelligence, pharma, patient journey, market research, clinical studies, healthcare, pharma ai, pharmaceuticals, commercial research

Top Use Cases for Machine Learning in Pharma

Real-World Use Cases for AI & ML in Pharma

For decades, Pharmaceutical data analytics has been a largely manual and tedious task conducted by the commercial research, health outcomes, R&D and Clinical Study groups at Pharma companies both small and large. With the emergence of machine learning, artificial intelligence and other disruptive innovations, Pharma, like other industries has also started its slow but sure transition to a more agile, data-driven model – one where in-house research is supplemented by intelligence gathered by applying algorithms across terabytes of Physician Rx, Patient Claims and other related datasets.

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Big Pharma; Big Data: how a third party company can revolutionize your data for a better tomorrow

pharma, Big Data, Real World Data, Data Analytics, Real World Evidence, Data Optimization, Data Insights, biotech, analytics

Big Pharma; Big Data: how a third party company can revolutionize your data for a better tomorrow

As each industry becomes more technologically savvy, the pharmaceutical industry has the chance to emerge into the 21^stcentury and reform how they treat patients while tackling different medical epidemics that affect the world today.

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Small Companies are key to RTP's continued success

Small Companies, Research, RTP, Start Up, Innovation

Small Companies are key to RTP's continued success

Larry Pickett Jr., CEO of RxDataScience Inc., had a problem common to startups: running out of space. His company, which crunches data for health care providers, employed three workers on the third floor of the 800 Building at the Frontier campus, a cluster of ’80s-era buildings in Research Triangle Park first used by IBM but now converted into an entrepreneurial coworking hub.

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PM360: Four Key Questions About Data Analytics

Big Data, Data Analytics

PM360: Four Key Questions About Data Analytics

PM360 asked experts in data analytics about how the process behind collecting and analyzing data is changing, including these four key questions:

How is the advancement of artificial intelligence, natural language processing, machine learning, and deep learning impacting the data analytics landscape?
How has the rise of concern for data privacy and the implementation of the EU’s General Data Protection Regulation (GDPR) affected pharma’s ability to collect or use data?
What can organizations do to help make their employees more data literate? Ultimately, how do you make everyone comfortable using data analytics?
What is the future of data analytics? How else is data collection, analyzation, visualization, implementation, etc., likely to change in 2019 and beyond?

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How Healthcare Can Prep for Artificial Intelligence, Machine Learning

Recently, Health IT Analytics published a blog on how the healthcare industry needs to prepare for advances in artificial intelligence and machine learning.

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Why Your Pharma CMO and Pharma CIO Need To Collaborate

In 2015, a survey by Accenture found that two-thirds of chief marketing officers (CMOs) in the pharmaceutical industry did not consider collaboration with their chief information officers (CIOs) as an important strategy. In the past, CMO/CIO collaboration was not a central focus as these two roles hardly ever coincided – CMOs generally focused on marketing technologies while CIOs focused on IT.

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Projected Pharmaceutical Data Analytics Trends 2018

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Projected Pharmaceutical Data Analytics Trends 2018

Advanced analytics necessitate the use of complex statistics and mathematical systems to improve the business operations of a company. Evidence shows that companies that use advanced analytics have repeatedly reduced variability in product quality and simultaneously lowered costs and increased sales.

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How the 21st Century Cures Act and Real World Evidence Impacts the Drug Approval Process

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How the 21st Century Cures Act and Real World Evidence Impacts the Drug Approval Process

The 21st Century Cures Act

In late December 2016 and with only three days remaining in session for the year, the U.S. Congress passed the 21st Century Cures Act, now commonly referred to as the Cures Act. This act laid out goals to “accelerate the discovery, development, and delivery of 21st century cures.” The law authorized $6.3 billion in funding, mostly for the National Institutes of Health. The Cures Act was first introduced nearly two years prior by seven bipartisan cosponsors, many of whom resided on the Science, Space, and Technology Committee. The legislation was supported by pharmaceutical manufacturers, as it had several important measures that would allow the healthcare and pharma industry to make more informed decisions to ultimately improve the patient journey. President Obama said the Cures Act will “modernize research and accelerate discovery” using data so that “treatment and healthcare can be tailored to individual patients.” It is a highly significant piece of legislation that will impact every pharmaceutical company and the way in which they manage, analyze, and leverage their real world data.

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Data-Driven Decision Making in Healthcare with RxDataScience

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Data-Driven Decision Making in Healthcare with RxDataScience

Providing data-driven healthcare solutions for better patient outcomes

Earlier in the year, our CEO Larry A. Pickett, Jr. gave a presentation at the CED Tech Venture Conference on RxDataScience’s solutions. There, he discussed RxDataScience’s ultimate goal of providing data-driven decision making in healthcare for better patient outcomes and lower costs of care. To achieve that goal, we’re helping companies unlock the value from their data.

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Pharma Big Data Use Case: A Mid-Market Pharma Success Story

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Pharma Big Data Use Case: A Mid-Market Pharma Success Story

Data-driven from the beginning

RxDataScience began as a small team at a mid-market pharmaceutical manufacturer, led by Larry Pickett as CIO.

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RxDataScience Blog

Top Use Cases for Machine Learning in Pharma

Top Use Cases for Machine Learning in Pharma

Real-World Use Cases for AI & ML in Pharma

Big Pharma; Big Data: how a third party company can revolutionize your data for a better tomorrow

Big Pharma; Big Data: how a third party company can revolutionize your data for a better tomorrow

Small Companies are key to RTP's continued success

Small Companies are key to RTP's continued success

PM360: Four Key Questions About Data Analytics

PM360: Four Key Questions About Data Analytics

How Healthcare Can Prep for Artificial Intelligence, Machine Learning

How Healthcare Can Prep for Artificial Intelligence, Machine Learning

Why Your Pharma CMO and Pharma CIO Need To Collaborate

Why Your Pharma CMO and Pharma CIO Need To Collaborate

Projected Pharmaceutical Data Analytics Trends 2018

Projected Pharmaceutical Data Analytics Trends 2018

How the 21st Century Cures Act and Real World Evidence Impacts the Drug Approval Process

How the 21st Century Cures Act and Real World Evidence Impacts the Drug Approval Process

The 21st Century Cures Act

Data-Driven Decision Making in Healthcare with RxDataScience

Data-Driven Decision Making in Healthcare with RxDataScience

Providing data-driven healthcare solutions for better patient outcomes

Pharma Big Data Use Case: A Mid-Market Pharma Success Story

Pharma Big Data Use Case: A Mid-Market Pharma Success Story

Data-driven from the beginning

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