16 – 18 March 2026
TRAINING TIMES
Learn how ICH guidelines and regulatory agencies expect statistical methods — and how they help ensure safe, effective products that meet patient needs.
See how statistical thinking improves product and process understanding, reduces risk, and drives better decisions.
Use data to define specifications, optimize processes, and meet validation and stability requirements with confidence.
Align process knowledge, statistical evidence, and patient-focused specifications to accelerate approvals and avoid rejections.
Three half-days of expert-led Zoom sessions packed with case discussions, Q&As, and real-world scenarios
All slides, tools, and supporting materials available in one place - before, during, and after the course.
Receive a digital certificate (also LinkedIn-ready) that verifies your skills in strategic trial planning.
Use statistics to define sampling and acceptance criteria, even when standard models don’t apply.
Learn to justify limits and decisions using DoE, control charts, and statistical intervals.
Use trends, real-world evidence, and stability data to make better regulatory and business decisions.
Turn risk analysis and process performance data into a sound ongoing verification plan.
Identify patient, product, and process risks and apply data-driven tools to manage them effectively.
Designed for professionals who want to enhance their expertise and advance their careers
SynoloStats, USA, Principal
Tara Scherder has over 20 years’ experience in the pharmaceutical and biopharmaceutical industries as a statistician, engineer, and master black belt. Her passion is the powerful combination of science and statistics to increase knowledge, optimize both manufacturing and business processes, and reduce risk. She combines statistical expertise with extensive knowledge of manufacturing platforms/analytical sciences and CMC requirements, always within business and regulatory context to achieve goals. She frequently speaks at industry forums and publishes on the practical incorporation of statistical methods for Lifecycle Process Validation. Tara earned a BS degree in Chemical Engineering from the University of Pittsburgh and a MS degree in Statistics from Carnegie Mellon University.
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