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Pharmaceuticals

JMP statistical discovery software helps users visualize life sciences data, facilitating efficient and interactive exploration and analysis. When used from bench to bedside, JMP can optimize the research and development cycle, bringing safe, effective drugs to market in a quick and profitable manner, and analyze a product’s entire life cycle from pre- to post-marketing observations.

The drug discovery and development pathway is expensive, and is further complicated by great pressures to be the first to pinpoint medical needs and opportunities, all while complying with strict policies and regulations. Pharmaceutical companies are seeing patents expire, generics moving in on the market share and a dwindling pipeline.

JMP for Drug Discovery

JMP and JMP Genomics software offer interactive analysis for every stage of the drug discovery and development process

Discovery Research

Pre-Clinical Development

Clinical Development

Post-Marketing Programs

  • JMP
  • JMP & SAS Integration
  • JMP Genomics
  • JMP & the FDA
  • Compliance & Validation

Pharmaceutical companies that leverage technological resources will protect their financial well-being and improve the well-being of those who need their products. JMP software is a comprehensive statistical analysis tool that can be used at every stage of drug discovery and development. You can:

  • Access and load data from numerous databases and formats.
  • Modify and manipulate the data through an easy to use, point-and-click Graphical User Interface (GUI).
  • Explore and analyze data with a wide range of statistical and graphical techniques found in the menu-driven system – without having to write your own code.
  • Automate analyses to cut development time.
  • Visualize your data in dynamic and interactive graphs that clearly communicate your findings.
  • Copy and paste summary tables into reviews.

JMP is often deployed as a standalone desktop tool. But JMP seamlessly integrates with SAS as a scalable and cost-effective analytic alternative, allowing users to leverage robust SAS analytics and the rich graphics that JMP provides. JMP can be used as a fully-integrated interface to visually display data with any of the SAS Life Sciences products including:

  • SAS Clinical Data Integration
  • SAS Clinical Toolkit
  • SAS Drug Development
  • SAS Patient Safety

As translational medicine moves into the mainstream, pharmaceutical companies will need powerful software to bridge the gaps between discovery research, development and diagnosis. JMP Genomics provides heavy-duty processing of genomics data sets for statistical geneticists, biologists, bioinformatics experts and statisticians. By integrating with SAS, it is a powerful tool for research teams to apply molecular insights from the lab to the realities of a clinical setting. You can:

  • Understand data generated from genetics, expression, exon, copy-number and proteomics studies.
  • Use the menu-driven, point-and-click system to simplify workflow and eliminate the need for programming.
  • Explore data from every angle, then easily share finding with colleagues.

SAS is the FDA standard for electronic submissions and the choice of 100 percent of the Fortune 500 life sciences companies, and JMP is the most commonly used tool in the clinical review community, with 40 percent of the medical reviewers at the FDA making it their primary choice. JMP is compatible with FDA processes, and will continue to be well-suited to exchange standards as they evolve. JMP is an active participant in the Clinical Data Integration Standards Consortium (CDISC) and supports the standardization initiative with added scripts and features designed especially to meet CDISC standards.

JMP pledges an unwavering commitment to data quality and evidenced-based safety. JMP analytics are tested and backed by SAS, a trusted partner to the pharmaceutical industry for more than 25 years. Read our Quality Statement for detailed information on the JMP development process, numerical accuracy, operational qualification and installation validation.

 
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