Control System Development – Learnings from the QbD Journey towards Approval PDA: A Global Association Christof Finkler, PhD Section Head Analytical Development an d QC Biotech Europe Global Lead Roche QbD Large Molecule Team F. Hoffmann-La Roche, Basel Outline • Introduction • QbD Roadmap - CQA Assessment - Process Controls - Control System • Learnings and Benefits of QbD 2 Approaches to Process Development Application of ICH Q11 Definition Traditional Approach: Identify potential CQAs Define an appropriate manufacturing process Process development research often conducted one variable at a time Define a control strategy to ensure process performance and Drug Substance quality Control Strategy not systematically linked to understanding of CQA criticality or process control Enhanced Approach: Identify potential CQAs Determining the functional relationships that link material attributes and process parameters to CQAs Multivariate experiments to understand product and process Use enhanced knowledge to establish a risk based control strategy which can include a proposal for a design space(s) or real-time release testing Control Strategy systematically linked to understanding of CQA criticality and process control 3 QbD Roadmap Critical Quality Attributes Process Control CQA Identification Using RA Tool Determine CQA Acceptance Criterion (CQA-AC) Assess Process Impact/ Stability Impact What attributes are important? What levels are acceptable? Does the process control the CQAs within those levels? Are they stable? Overall Control Strategy Determine Attribute Testing Strategy based on CQA and Process Impact Knowledge Do we have a robust process & testing strategy? What needs to be tested? Control Strategy QbD provides a systematic approach to answer these questions 4 CQAs for a MAb ICH Q8 R1: Critical Quality Attribute: A physical, chemical, biological or microbiological property or characteristic that should be within an appropriate limit, range, or distribution to ensure the desired product quality. High Molecular Weight Species Fragments Composition and Strength Adventitious Agents Glycation Aspartic Acid Isomerization Oxidation Variants Leached Protein A Glycosylation Variants Host Cell DNA Host Cell Protein N-terminal Variants C-terminal Lysine Deamidation Raw Materials Sequence Variants Proline Amidation Cysteine Forms Leachables Drug Product Specific 5 Critical Quality Attributes (CQAs) Categorization Category of Attribute Assessment Rationale for Approach Product Variants Risk Ranking and Filtering Impact to patient safety and product efficacy is specific to variant in question, mechanisms of action, route of administration, etc. Process-related impurities Risk Ranking and Filtering Clinical data from similar products can be used to assess safety Composition and Strength Obligate CQA Potentially high impact to safety and efficacy Adventitious Agents Obligate CQA Potentially high impact to safety Raw Materials Compare Estimated Daily Intake and Acceptable Daily Exposure Extensive data available from safety and toxicity studies 6 CQA Identification Risk Ranking & Filtering Tool Risk = Impact Score x Uncertainty Score (2, 4, 12, 16, 20) Risk that an attribute impacts safety or efficacy. (1, 2, 3, 5, 7) Impact attribute has on safety and efficacy. Determined by the available knowledge. More severe impact higher value. Safety Uncertainty in assigning impact. Determined by relevance of knowledge. Reflects the degree of confidence. Higher uncertainty higher value. Bioactivity PK Immunogenicity Impact and Uncertainty rankings have different scales to reflect the relative importance 7 CQA Acceptance Criteria (CQA-AC) The CQA-AC represents a numerical limit a CQA must meet at the Drug Product end of shelf life in order to ensure the desired quality of the product. – based on patient impact and not limited to product-specific clinical and manufacturing experience – collective effect of CQAs considered to ensure PK and biological activity – drive CPP and Design Space identification and definition of control strategy – based on product-specific non-clinical and clinical experience as well as platform knowledge and published literature – Process capability is considered. Extension of limits beyond clinical experience is feasible if patient safety is ensured 8 QbD Roadmap Critical Quality Attributes Process Control CQA Identification Using RA Tool Determine CQA Acceptance Criterion (CQA-AC) Assess Process Impact/ Stability Impact What attributes are important? What levels are acceptable? Does the process control the CQAs within those levels? Are they stable? Overall Control Strategy Determine Attribute Testing Strategy based on CQA and Process Impact Knowledge Do we have a robust process & testing strategy? What needs to be tested? Control Strategy 9 Process Control CQAs • Identify CQAs for the product • Determine relevant levels for each CQA at each step Cell Culture/ Fermentation Characterize the process • Perform scale-down uni- and multivariate or worst-case experiments for each unit operation • Monitor all relevant CQAs • Defines site- and scale-independent PP impacts Confirm a Design Space (optional) • Linkage studies at worst-case limits for all CPPs across the whole process • Monitor process-wide performance for relevant CQAs Traditional atscale Process Validation • Confirms consistency of the process at scale in the commercial manufacturing site • Confirms site- and scale-dependent validation Centrifugation Chromatography Steps Concentration and Formulation 10 Drug Product Manufacturing QbD Roadmap Critical Quality Attributes Process Control CQA Identification Using RA Tool Determine CQA Acceptance Criterion (CQA-AC) Assess Process Impact/ Stability Impact What attributes are important? What levels are acceptable? Does the process control the CQAs within those levels? Are they stable? Overall Control Strategy Determine Attribute Testing Strategy based on CQA and Process Impact Knowledge Do we have a robust process & testing strategy? What needs to be tested? Control Strategy 11 Overall Commercial Control Strategy Acceptance Ranges INPUT: Process Parameter OUTPUT: Quality Attribute CPPs CQAs CPPs CQAs Acceptance Criteria Overall Control Strategy Control of Process Parameters GMP - Procedural Controls + GMP - Environmental Controls 12 (CPPs & Non-CPP) Control of Materials + Attribute Testing Strategy Specified CQAs Monitored CQAs 12 The Overall Control Strategy is a Risk Management Strategy Using the QbD approach, lot release & stability testing is risk-based and addresses highly critical or less well-controlled attributes Process impact/ stability impact CQA Risk Ranking and Filtering CQA-AC definition CQA High Process Impact Non-CQA How critical is the attribute? Lot Release Testing Medium Process Impact Low Process Impact QAs Attribute Testing Strategy Risk Ranking and Filtering Attribute Monitoring Robustness assessment No Testing How well does the process control it? Does it change on Stability Either high criticality or high process/stability impact drive testing Attribute Testing Strategy confirmed 13 Attribute Testing Strategy Score Defines Testing Strategy CQA Impact Score (2,4,12,16,20) X Process/Stability Impact Score (1,2,4,10) = Stability Impact Tree Process Impact Tree Attribute Testing Strategy (ATS) Score Attribute Testing Strategy Score <21 No testing required 21-50 Monitoring required >50 Control System testing required 14 Impact assessment is done for the individual steps by the aid of risk ranking and filtering tools Drug Substance Production Decision Tree for Process Impact Drug Substance Storage Decision Tree for Stability Impact Table Drug Product Production (through filling ops) Drug Product Storage, Finishing, Distribution Decision Tree for Process Impact Decision Tree for Stability Impact Table Process Impact Assessment and Residual Risk CQA assessment process capability independent Non-CQA CQA Worst case prediction CQA target range 70 % of CQA target range CQA RRF Process studies & Linkage <1.0% Abundance Variant not susceptible to change (Equivalent to RS) Process mean 70 % of CQA target range CQA target range No impact low impact low moderate high impact impact impact 16 Stability Impact Assessment and Residual Risk Amount variant xyz Allowable Stabiliy Range CQA-AC Potential space for allowable excursions (e.g. temperature) Release specification Target manufacturing Probability to exceed allowable stability range defines stability impact and attribute testing strategy: >1.0% high stability impact 0.1-1.0% moderate stability impact <0.1% low stability impact = predicted change for individual data point over shelf-life Upper/lower prediction interval Residual risk (high impact) can be covered by control system testing Attribute Testing Strategy - Example No Testing Process Impact Score Stability Impact Score Batch Release Stability Monitoring Considered for Stability in Comparability Exercises 10 80 200 4 2 80 40 LMWS 16 4 2 64 32 2 2 32 32 Deamidation 16 in CDR 1 1 16 1 1 16 Deamidation 16 in non-CDR 1 1 16 1 1 16 10 2 120 24 2 10 120 24 Oxidation in 12 CDR (Met) 2 2 24 24 2 2 24 24 Oxidation in 16 CDR (Trp) 1 1 16 1 1 16 Oxidation in 16 non-CDR (Met) 2 2 32 32 2 2 32 32 Unknown Acidic Charge Variants 12 No Testing Considered for Stability in Comparability Exercises 4 Monitoring Batch Releasea 20 Stability Stability Impact Score Control System Testing Process Impact Score Control System Testing Drug Product HMWS CQA Category Size related variants Charge-Related Variants: Acidic Variants Oxidation-Related Variants Drug Substance CQA Impact Score CQA 18 QbD Roadmap Critical Quality Attributes Process Control CQA Identification Using RA Tool Determine CQA Acceptance Criterion (CQA-AC) Assess Process Impact/ Stability Impact What attributes are important? What levels are acceptable? Does the process control the CQAs within those levels? Are they stable? Overall Control Strategy Determine Attribute Testing Strategy based on CQA and Process Impact Knowledge Do we have a robust process & testing strategy? What needs to be tested? Control Strategy 19 Outline • Introduction • QbD Roadmap - CQA Assessment - Process Controls - Control System • Learnings and Benefits of QbD 20 Key Learnings – CQA Assessment (1) • Structured CQA assessment is an extensive exercise – ensure timely start in order be ready to support PC/PV studies • Involvement of preclinical an clinical experts is key to draw the right conclusions • Include all relevant mode of actions into CQA assessment to ensure that all CQAs and hence all CPPs are identified. Early agreement with health authorities on relevant mode of actions is beneficial. • Risk assessments and justification thereof require proper and timely documentation 21 Key Learnings – CQA Assessment (2) •In silico analysis is a valuable tool to support CQA assessment •Criticality assessment of individual quality attributes should be performed independent of levels present in clinical trial material •Type and amount of information provided in filings to convey enhanced understanding is increased 22 Key Learnings – Control Strategy (1) • Extention of CQA acceptance criteria beyond actual levels present in clinical trial material is possible but requires proper justification. Acceptable levels of attributes affecting immunogenicity and safety are usually more closer to clinical history • Collective effect of CQAs needs to be considered to ensure PK and biological activity • Risk based control strategy provides oppertunity to reduce redundant or low/non-value added QC test 23 Key Learnings – Control Strategy (2) • Evaluation of process impact on CQAs should include the identification of interactions of process parameters and worst-case linkage of all unit operations affecting that CQA in order to reduce the risk of unexpected product quality/process failure. • Thorough explanation of tools and approaches that are used as part of the enhanced approach to process- and control strategy development is required in the dossier • Summaries on CQA criticality, process and stability impact, and control strategy robustness assessment strongly supports the justification of specification(s) in S.4.5 and P.5.6. • The dossier need to include a clear overview of the remaining risks/uncertainties and how the control strategy managed these 24 Benefits of QbD for Control System Development • Systematic risk based CQA assessment leads to a better understanding of the molecule • The more extensive evaluation of process impacts on CQAs generates the knowledge which CQA are affected by the process parameters for each unit operation • Documented risk assessments is a strong basis for knowledge management • QbD approach allows a more rigor development of overall control strategy Acknowledgements Thanks to: Roche Global QbD Large Molecule Team Multiple Technical Development Teams Lynne Krummen, Mary Cromwell, Paul Motchnik, Reed Harris Gerald Gellermann, Felix Kepert, Nadja Alt, Ettore Ohage, ... 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