Statistics & PAT Expert
Job Description Summary Purpose: Provide excellence in statistical and process analytical technology support to the site and within the global network to drive the application of advanced and state-of-the-art statistical principles, tools and methodologies to improve process understanding, quality and compliance of the products, efficiency and capability of the processes and profitability of the organization.
Job Description Major Accountabilities Manufacturing Excellence – Statistics & PAT: Process Validation and Transfers Statistical analysis of process validation data for demonstrating validity and equivalence Contribute to risk assessments, e.g.
FMEA or risk matrix. Planning and evaluation of Design of Experiments (DoEs) in the frame of the Novartis Quality by Design validation strategy. Trending analysis in the frame of Ongoing Process Verification. Implementation and application of Statistical Process Control principles, e.g. control charts, and other pattern recognition techniques.
Support the compilation of Annual Product Review (APR)/Product Quality Reviews(PQRs). Facilitate and enable (multivariate) process monitoring and control principles, e.g. by Multivariate data analysis (MVDA). Review of stability data and definition of Internal Release Limits (IRL) Support critical root cause Investigation.
Support the analysis of complex data sets to facilitate Rapid Root Cause Investigation (rRCI). Accountable for providing meaningful statistical conclusions. Analytical method validation and transfer, in particular Process Analytical Technology (PAT) methods.
Support the design of an analytical robustness test, e.g. by means of DoE Statistical assessment of method validation data and technology and process transfer across sites. Development and validation of multivariate models for online PAT methods.
Enable Process improvement initiatives (also in alignment with operational excellence organization and methodologies (e.g. IQP, Six Sigma, Lean Manufacturing): Capability and stability assessments. Hypothesis testing Models for facilitating process improvements, e.g.
DoE, MVDA, etc. Training: Enable the Site to have the necessary competencies in advanced applied statistical tools, cross-functionally (MS&T, manufacturing, QA, QC, operational excellence, ...) by designing and delivering training on available tools and how to use them in practice, and providing ongoing coaching.
Instruct how to collect (e.g. sampling plans that are statistically meaningful), set up, and interpret data sets and statistical results highlighting constraints and limitations. Interacts with internal and external Reg bodies and Health Authorities, as well as internal functions (development organization, RegCMC, QA/QC, Engineering, global MS&T) as appropriate (e.g. during inspections, investigations etc.) in statistical aspects of data analysis and rationales.
Key Performance Indicators Success rate of Health Authorities' Inspections Successful PAT transfer and implementation in the DSS site. Technology transfers and new product launches on time, right first time. Technical reports executed on time and with the right expectations.
Applied statistics training in place and executed. Specific Professional Competencies cGMP and Good Documentation Practices Root Cause Analysis (RCA) Corrective Action and Preventive Action Statistical Process Monitoring Knowledgeable on Effectiveness Checks Continuous Process Improvement Drug Substance Manufacturing Process Design and Control Gap Assessment and Risk Analysis Complaints and OOXs Handling Technology Transfer Report writing Data Analytics Project Management Ideal Background Education: Masters in Statistics, Mathematics, Chemical Engineering, or its equivalent education is desirable.
Languages: English (oral and written). Experiences: Minimum 10 years of experience in MS&T or in the manufacturing of Biologics in large molecules. At least 5 years of experience in MS&T or Manufacturing operations. Proven process understanding (Pharma, GMP, Regulatory aspects).
Proven experience in applied statistics is a must, e.g., in the field of DOEs and multivariate data analysis. Experience in the following software and tools is a plus: SAS, R, Python, Minitab, SIMCA-P+, Modde, JMP, SPSS Good communication, presentation, and interpersonal skills.
Skills Desired Applied Statistics, Change Control, Data Analytics and Digital, GDP Knowledge, gmp knowledge, HSE Knowledge, Manufacturing Process, Manufacturing Production, Manufacturing Technologies, Operational Excellence, Process and Cleaning Validation, Process Control, Quality Compliance, Regulatory Compliance, Resilience and Risk Management, Technical Leadership, Technology Transfer