quality by design (qbd) step guide by shivang chaudhary ciie iim a

1
Define QTPP (Quality Target Product Profile) On the basis of Therapeutic Equivalence for Pharmaceutical Abbreviated New Drug Application (ANDA- Generics)= Pharmaceutical Equivalence (same dosage form, route of administration, strength & same quality) + Bio-Equivalence (same pharmacokinetics in terms of Cmax, AUC/ On the basis of Therapeutic Safety & Efficacy for Pharmaceutical New Chemical Entities (NCE-Innovator) / New Drug Applications (NDA-Novel Drug Delivery Systems as compared to already approved & available conventional dosage forms) Determine CQAs (Critical Quality Attributes) On the basis of Quality [Assay, Uniformity of Dosage units, Redispersibility, Reconstitution time, Aerodynamic property], Safety [Impurities (Related substances), Residual Solvents, Osmolarity & Isotonicity, Microbiological limits, Sterility & Particulate matter], Efficacy [Diffusion, Dissolution & Permeation] & Multidisciplinary [Patient Acceptance & Compliance] Risk Assessment of CMAs (Critical Material Attributes) & CPPs (Critical Process Parameters) thru (1) Risk Identification (Qualitative): by Ishikawa Fishbone & Relative Risk based Matrix Analysis (2) Risk Analysis (Quantitative): by Failure Mode Effective Analysis (3) Risk Evaluation: by Design of Experiments (DoE) Design of Experiments (DoE) (A) For Screening purpose: 2 level full / fractional factorial, plackette burman designs & (B) For Optimization purpose : 3 or 5 level full factorial, Central Composite, Box-behnken, Simplex Mixture, D-optimal mixture designs can be used Development of Design Space (DS) Proven acceptable ranges & Edges of failure for Multifactor, Multidimensional combinations & interactions of CMAs & CPPs with respect to CQAs for QA, SUPAC & RA [by way of successively evaluations of Effect plots: Normal Distribution & Pareto plots > ANOVA & Prediction equation > 2D Contour plots > 3D Response Surface plots > 4D Cube plots> Desirability plot based upon studied range of factors > Overlay plot based upon desired ranges of Responses for optimizing & fixing range of studied factors] Implementation of Control Strategy (CS) For Control of CMAs, CPPs, Specifications, Real Time Release Testing, Monitoring System [based upon previous results on Lab scale development, Pilot Scale Up. Plant scale Exhibit/ Validation batches] Continual Improvement based upon continual risk review & risk communication between Plant, QA, QC, RA, FR&D, AR&D during routine commercial manufacturing Process Analytical Technology (PAT) A system for Designing, Analyzing & Controlling Manufacturing through timely measurements of CQAs & CPAs with the goal of automatic ensuring finished product quality by automatic inline, at line & on line sensors & controllers. <<((QbD))>> © Created & Copyrighted by Shivang Chaudhary ([email protected]) © Created & Copyrighted by Shivang Chaudhary ([email protected]) © Created & Copyrighted by Shivang Chaudhary

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Page 1: Quality by Design (QbD) Step Guide by Shivang Chaudhary ciie IIM A

Define QTPP (Quality Target Product Profile) On the basis of Therapeutic Equivalence for Pharmaceutical Abbreviated New Drug Application (ANDA- Generics)= Pharmaceutical Equivalence

(same dosage form, route of administration, strength & same quality) + Bio-Equivalence (same pharmacokinetics in terms of Cmax, AUC/ On the basis of Therapeutic Safety & Efficacy for Pharmaceutical New Chemical Entities (NCE-Innovator) / New Drug Applications (NDA-Novel

Drug Delivery Systems as compared to already approved & available conventional dosage forms)

Determine CQAs (Critical Quality Attributes) On the basis of Quality [Assay, Uniformity of Dosage units, Redispersibility, Reconstitution time, Aerodynamic property],

Safety [Impurities (Related substances), Residual Solvents, Osmolarity & Isotonicity, Microbiological limits, Sterility & Particulate matter], Efficacy [Diffusion, Dissolution & Permeation] & Multidisciplinary [Patient Acceptance & Compliance]

Risk Assessment of CMAs (Critical Material Attributes) & CPPs (Critical Process Parameters) thru

(1) Risk Identification (Qualitative): by Ishikawa Fishbone & Relative Risk based Matrix Analysis

(2) Risk Analysis (Quantitative): by Failure Mode Effective Analysis (3) Risk Evaluation: by Design of Experiments (DoE)

Design of Experiments (DoE) (A) For Screening purpose: 2 level full / fractional factorial, plackette burman designs &

(B) For Optimization purpose : 3 or 5 level full factorial, Central Composite, Box-behnken, Simplex Mixture, D-optimal mixture designs can be used

Development of Design Space (DS) Proven acceptable ranges & Edges of failure for Multifactor, Multidimensional combinations

& interactions of CMAs & CPPs with respect to CQAs for QA, SUPAC & RA [by way of successively evaluations of Effect plots: Normal Distribution & Pareto plots > ANOVA &

Prediction equation > 2D Contour plots > 3D Response Surface plots > 4D Cube plots> Desirability plot based upon studied range of factors > Overlay plot based upon desired

ranges of Responses for optimizing & fixing range of studied factors]

Implementation of Control Strategy (CS) For Control of CMAs, CPPs, Specifications, Real Time Release Testing,

Monitoring System [based upon previous results on Lab scale development, Pilot Scale Up. Plant scale Exhibit/ Validation batches]

Continual Improvement based upon continual risk review & risk

communication between Plant, QA, QC, RA, FR&D, AR&D during routine commercial manufacturing

Process Analytical Technology (PAT) A system for Designing, Analyzing & Controlling Manufacturing through timely

measurements of CQAs & CPAs with the goal of automatic ensuring finished product quality by automatic

inline, at line & on line sensors & controllers.

<<((QbD))>>

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© Created & Copyrighted by Shivang Chaudhary