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- Design of Experiments (DOE) for Pharmaceutical Sciences, Biotechnology, and Medical Electronics - Bridging Innovation and PrecisionLearn how DOE is revolutionizing pharma, biotech and medical electronics engineering, making health care safer, more efficient, and more effective for all.
- Why the making stuff mindset doesn't make senseDOE expert Phil Kay discusses how design of experiments, and a little planning, can help you run projects that are more efficient, predictable and deliver the data you need to make better decisions.
- CDISC Enables Efficient Streamlining of Clinical Trial Safety EvaluationIn this paper we discuss clinical trial summary information and follow the flow of FDA New Drug Application (NDA) submissions, Clinical Reviews (CR) and Biosimilar Multi-disciplinary Evaluation and Review (BMER) to reveal how the various domains of SDTM and ADaM are used to assess drug safety.
- You Don't Need Coding to be a ChemistDOE expert Phil Kay says the job of today's chemist is less about making samples and more about generating data
- Digitalisation is the future of science, just ask a bologistDOE expert Phil Kay discusses how digitalisation can help automate large and complex experiments, an idea chemists should borrow from their biologist friends.
- Unit TestsOver the past 20 years, software developers have become increasingly interested in automated unit testing and the phrase unit testing framework has come to refer to the mechanism used to facilitate automated unit testing. Learn how JMP uses unit testing in its software development.
- Machine learning applications for chemical and process industriesIn this article, we explain industrial data science fundamentals and link them with commonly-known examples in process engineering. Then, we review industrial applications using state-of-art machine learning techniques.
- Analyzing spectral data: Multivariate methods and advanced pre-processingJMP Senior Systems Engineers Bill Worley and Data Scientist Jeremy Ash demonstrate the utility of the multivariate platforms in JMP..
- Analyzing spectroscopic data: Pre-processingJMP Senior Systems Engineers Bill Worley and Data Scientist Jeremy Ash describe how you can import, visualize, clean, and analyze spectroscopic data with JMP software.
- Data Science is a Team SportProfessor Alyson Wilson discusses how, as data grows in volume, velocity, variety and veracity, solving complex problems can no longer be done in a silo.
- Forecasting in the IoT eraProfessor, researcher and author Galit Shmueli discusses how large collections of time series can lead to extremely useful forecasting in the Internet of Things Era.
- Empowering P&G employees to do text analysisScott Reese, from the Data & Modeling Science team at Procter & Gamble, explains how he uses text analytics to answer some of the company's most pressing data questions.
- What Is Experimental Design?Experiments are more than a demonstration of scientific principles. Bradley Jones describes a utopia where experimental design is a standard engineering procedure and where all products get to market more quickly with better quality and lower cost.