Annual Product Quality Review Program Lead

Annual Product Quality Review (APQR) Program Lead

The Annual Product Quality Review (APQR) Program Lead supports and assists the Quality Assurance (QA) function by merging product data evaluation under FDA 21 CFR 211.180(e) with technical engineering controls to ensure commercial products consistently meet safety, identity, strength, quality and purity standards. The incumbent leads the statistical trending, data collection and aggregation and drafting of Annual Product Quality Reviews / Annual Product Reviews (APQRs/APRs) to monitor product/process stability and make data‑driven continuous improvement across various production processes in accordance with SOPs, current Good Manufacturing Practices (cGMPs), FDA standards and batch record specifications.

• Maintains all appropriate Quality related documentation, ensuring adherence to company quality policies, practices, SOPs and cGMPs.
• Leads the evaluation of annual product quality data to identify emerging quality risks, process variability, adverse trends and opportunities for continuous improvement using statistical methods and quality risk management principles.
• Collaborates with various departments, functions and SMEs to submit all sub‑reports in a timely, accurate and compliant manner.
• Hosts APR risk assessment meetings, tracks attendance and takes appropriate actions on team recommendations.
• Performs advanced trend analysis for intermediates, in‑process, finished product and stability batches, evaluating critical quality attributes (CQAs) and critical process parameters (CPPs) with statistical methods.
• Analyzes and interprets large datasets from Manufacturing, Packaging, Laboratory departments, complaints, deviations, CAPAs, change controls and stability programs to identify statistically significant trends, process shifts and emerging quality risks.
• Applies statistical methods including control charts, process capability analysis, regression analysis, Pareto analysis and trend modeling to evaluate process performance and product lifecycle health.
• Evaluates cumulative impact of deviations, CAPAs, change controls, complaints, stability trends, analytical changes and validation activities on product quality throughout product lifecycle.
• Recommends revalidation and determines the need for process revalidation or changes to registered specifications based on APQR/APR data and conclusions.
• Drives Root Cause Investigations by partnering with QA Investigations, Production, Laboratory and Technical Services teams using tools such as Fishbone, 5 Whys and FMEA.
• Monitors process capability and calculates and analyzes process indicators such as Process Capability Index (Cpk) and Process Capability Index (Ppk).
• Participates in inspections and supports Regulatory audits by acting as SME for APQRs, trending data and process statistics during FDA and foreign health authority inspections; assists in other QA areas as needed.
• Performs any other APR tasks assigned by Supervisor or Quality Senior Management.

Minimum education and experience:
Bachelor’s degree in Chemical Engineering, Pharmaceutical Sciences, Chemistry or a related scientific discipline and a minimum of 5 years in quality systems, process validation, product quality review or quality engineering within the pharmaceutical or biotechnology industry, or a combination of education and related experience in progressive technical roles.

• Deep understanding of FDA 21 CFR Part 210/211, ICH Q8, ICH Q9 and ICH Q10.
• Familiarity with laboratory testing equipment such as automated dissolution testers, HPLC, particle size analyzers and viscometers/rheometers.
• Ability to translate statistical observations into quality risk assessments and business recommendations using risk‑management tools and structured decision‑making methodologies.
• Proficiency in statistical analysis platforms such as Minitab, JMP or SAS for process trending and control charting.
• Demonstrated experience applying statistical methodologies including control charting, process capability analysis, trend analysis, regression analysis, hypothesis testing, ANOVA, sampling plans and statistical…