Bioprocess Data Analytics and Machine Learning

Organizations on the leading edge of bioprocess data analytics have already seen dramatic improvements in pharmaceutical batch optimization, manufacturing scalability, and regulatory efficiency.

To help you take advantage of these revolutionary developments—and drive breakthroughs of your own—MIT Professional Education is pleased to introduce Bioprocess Data Analytics and Machine Learning. In this intensive, three-day course, you’ll gain:

• A greater understanding of how bioprocess data analytics can be applied to develop and improve biotherapeutic manufacturing
• Insight into important advances in data analytics, machine learning methods, and software that provide new ways to build models, diagnose problems, and make informed decisions
• An introduction to new sensor technologies, including spectral imaging and real-time color video, and the major classes of data analytics and machine learning methods used in bioprocess operations
• Tools to systematically interrogate the data to ascertain specific characteristics needed to select among the best-in-class data analytics methods

With the guidance of academic and industry experts, you’ll discover transformative ways to apply data analytics—and avoid the most common pitfalls that arise when analyzing bioprocess data. By the end of the course, you’ll have an understanding of the best practices needed to translate biopharmaceutical manufacturing data into reliable models and better decisions. Simply put, you’ll be able to select the right methods, improve accuracy and effectiveness, and save time and money. 

Certificate of Completion from MIT Professional Education

• Apply new sensor technologies relevant to biopharmaceutical manufacturing processes, such as spectral imaging and real-time color video
• Understand major classes of data analytics and machine learning methods relevant to bioprocess operations
• Systematically interrogate bioprocess data to ascertain characteristics (such as nonlinearity, multicollinearity, and dynamics)
• Select among the best-in-class data analytics methods based on the objective and data characteristics
• Summarize ways to combine data-driven models with mechanistic understanding
• Avoid common pitfalls when analyzing bioprocess data

Program Outline

Classes will run on the following schedule:

• Day One: 9:00am – 6:00pm
• Day Two: 9:00am – 6:30pm
• Day Three: 9:00am – 5:30pm

Bioprocess Data Analytics and Machine Learning is designed for scientists and engineers in the biopharma industry who want to take their skills—and their careers—to the next level. In particular, this course is well suited to individuals with job titles such as Data Scientist, Senior Research Scientist, and Bioprocess Engineer. Additionally, course participants should have some experience with analyzing experimental data.

Requirements

Participants should have some experience in data analytics and bioprocesses. In addition, participants must be professionals with experience working in the pharmaceutical or biopharmaceutical industry.