All 20 of the world's largest pharmaceutical companies use JMP.
For research and development
- 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
- 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.
- 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
- 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.
increase in yield
savings in R&D time and resources
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.
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.
How JMP® Empowers the Pharmaceutical Industry
- Regeneron PharmaceuticalsIn this presentation, Diana Nadler, Manager of Continuous Improvement Statistics, discusses enterprise analytics at Regeneron Pharmaceuticals.
- Eli LillyChao Richard Li on data literacy and DOE.
- PerrigoPerrigo reduces product variability and other inefficiencies by growing the use of statistical analysis in experimentation and testing