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Data Analysis Software for the Pharmaceutical Industry

How JMP® Empowers the Pharmaceutical Industry

JMP data analysis software empowers some of the world's largest and most innovative pharmaceutical companies to explore process and lab data, understand sources of process variation, learn more from root-cause investigations and optimize processes and experimental design – all without learning to code. 

For research and development

New products and processes don't have the benefit of relevant historical data that can be used as a guide. Researchers therefore need to supplement their subject matter knowledge with data analytics to drive faster, better-informed decisions from the existing data and to solve problems correctly the first time. 

With JMP, you can:
  • Define and implement the most cost-effective new data collection method and statistical analysis plan. 
  • Make statistics more approachable for non-statisticians. Guided analysis eases anxiety about getting it right the first time. 
  • Achieve better outcomes by finding robust solutions to problems faster and meeting project milestones more quickly. 
  • Improve efficiency across teams by quickly sharing discoveries.

For process and product development

JMP provides the ability to manage project dependencies and timelines. Missed milestones add to work and stress levels and may lead to late product launches and high product costs (or low margins) once on the market.

With JMP, you can:
  • Maximize your product's efficacy and safety profile by developing robust processes that scale.
  • Achieve more development milestones predictably to increase R&D output and improve speed to market.
  • Increase speed and quality of analysis by automating routine, manual tasks.

For manufacturing

Scientists investigate manufacturing processes with an emphasis on quality and regulatory compliance while managing trade-offs in speed and cost.

With JMP, you can:
  • More effectively monitor processes to ensure consistent quality and identify and troubleshoot possible batch failures more proactively.
  • Continually improve processes and products to capture more value and reduce waste.
  • Develop effective analysis plans to drive out high-failure or high-cost aspects of a process.
  • Save time by easily accessing and pre-processing production data in one self-service platform.

For bench scientists and researchers

All along the R&D and process development path, there are measurements to determine product quality and yield along with process capability. Scientists collect and assess data from laboratory methods, including highly sophisticated instruments that output large amounts of data.

With JMP, you can:
  • Quickly collect data and assess data quality to determine if any curation of the data is needed before further analysis takes place.
  • Save time by having the complete analytic workflow in one self-service platform.
  • Effectively communicate across functions when the data indicates an issue with a product or process.

Results achieved by JMP customers


increase in yield



savings in R&D time and resources

Johnson Matthey


more efficient


JMP Capabilities for the Pharmaceutical Industries

  • Design of Experiments

    Actively manipulate factors according to a pre-specified design to quickly and easily gain useful new understanding.

  • Statistical Process Control

    Separate common and special causes to assist process analysis efforts, including problem investigations, out-of-control conditions and ongoing monitoring for stability.

  • Stability and Shelf Life Analysis

    Assess batch poolability, establish expiration dating and easily calculate confidence limits and crossing times – all in adherence to ICH Q1 guidelines.

  • Quality by Design

    Identify and evaluate all sources of variability with respect to a finished product's quality parameters. 

  • Dose Response

    Analyze precision, accuracy, linearity, bias and reproducibility. Fit curves and compare models for a wide range of sigmoidal responses (4p, 5p). Efficiently assess parallelism for relative potency and apply streamlined methods for cut point determination.

  • Robust Process Optimization

    Find the sweet spot in a design where performance is minimally sensitive to variation for all critical quality attribute (CQA) goals in your process, following ICH Q11 guidelines.