JMP data analysis software empowers some of the world's largest and most innovative pharmaceutical and biotech 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.
Some of the typical challenges facing the pharmaceutical industry include:
- The need to drive faster, better-informed decisions from the existing data to solve problems.
- 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.
- They must ensure quality and regulatory compliance while managing trade-offs in speed and being able to reduce cost.
- Scientists collect and assess data from laboratory methods, they need to quickly collect that data and assess data quality to determine if any curation of the data is needed before further analysis takes place.
- Another challenge is being able to effectively communicate across functions when the data indicates an issue with a product or process.[1]
How JMP can help
JMP helps users in the pharmaceutical industry solve problems using a data-driven approach in a friendly point-and-click interface. JMP allows scientists and engineers to focus on their areas of expertise to solve problems without having to code or earn an additional degree in statistics. Some of the common JMP tools in the pharmaceutical industry include:
- Exploratory data analysis to visualize, explore and find relationships between variables. JMP’s graph builder and distribution platforms have an intuitive click & drag interface that allows scientists and engineers interactively visualize and work with existing data to explore relationships and identify areas of the data that warrant further investigation.
- Design of Experiments (DOE) to identify process inputs that can be manipulated to obtain the desired process outcome. In addition to a complete library of tried and tested classical DOE designs, JMP also offers an innovative custom design capability that tailors the design to answer specific questions without wasting precious resources. Once the data has been collected, JMP streamlines the analysis and model building so scientists can easily see the pattern of response, identify active factors, and optimize responses.
- Control charts to ensure processes are in statistical control and capability analysis to ensure products are capable of meeting customer requirements. With the emergence of digital transformation and more manufacturing data being automatically recorded by sensors, the machine-learning tools in JMP, like predictor screening, can be easily leveraged for a data-driven approach to root-cause analysis. The tools in JMP help users identify emerging issues, determine their root causes, and contain and resolve them before they become customer problems.
- Stability analysis for determining expiration date for products in accordance with ICH guidelines. JMP offers built-in capabilities for analyzing the stability of drug batches over time, making complex statistics simple, and presenting the results in a straight-forward way, so scientists and engineers have confidence in their decisions and the accuracy of the reported numbers.
Customer Success Stories
Read on to learn how current users in the pharmaceutical industry are maximizing the value they get from JMP statistical discovery software every day.
Adocia, Daewoong Pharmaceutical, De Montfort University
- Define and implement the most cost-effective new data collection method and statistical analysis plan.
- Make statistics more approachable for non-statisticians.
- Improve efficiency across teams by quickly sharing discoveries.
Meanwhile Celltrion Coloplast, Colorado Department of Public Health and Environment, were able to :
- Maximize their 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 and manual tasks.
Mario Negri Institute for Pharmacological Research, Almirall, Beijing Children's Hospital, Bionano Genomics, CEA Grenoble,
- 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.
For more information please check https://www.jmp.com/es_cl/industries/data-analysis-software-for-the-pharmaceutical-and-biotechnology-industries.html
