title: Acceptance Probability (P a) Analysis for Process Validation Lifecycle Stages.
abstract: This paper introduces an innovative statistical approach towards understanding how variation impacts the acceptance criteria of quality attributes. Because of more complex stage-wise acceptance criteria, traditional process capability measures are inadequate for general application in the pharmaceutical industry. The probability of acceptance concept provides a clear measure, derived from specific acceptance criteria for each quality attribute. In line with the 2011 FDA Guidance, this approach systematically evaluates data and scientifically establishes evidence that a process is capable of consistently delivering quality product. The probability of acceptance provides a direct and readily understandable indication of product risk. As with traditional capability indices, the acceptance probability approach assumes that underlying data distributions are normal. The computational solutions for dosage uniformity and dissolution acceptance criteria are readily applicable. For dosage uniformity, the expected AV range may be determined using the s lo and s hi values along with the worst case estimates of the mean. This approach permits a risk-based assessment of future batch performance of the critical quality attributes. The concept is also readily applicable to sterile/non sterile liquid dose products. Quality attributes such as deliverable volume and assay per spray have stage-wise acceptance that can be converted into an acceptance probability. Accepted statistical guidelines indicate processes with C pk > 1.33 as performing well within statistical control and those with C pk < 1.0 as "incapable" (1). A C pk > 1.33 is associated with a centered process that will statistically produce less than 63 defective units per million. This is equivalent to an acceptance probability of >99.99%.
authors.affiliation: Apotex Inc., 150 Signet Drive, Toronto, Ontario, M9L 1T9, Canada.
authors.forename: Daniel
authors.initials: D
authors.lastname: Alsmeyer
authors.affiliation: Apotex Inc., 150 Signet Drive, Toronto, Ontario, M9L 1T9, Canada. apazhaya@apotex.com.
authors.forename: Ajay
authors.initials: A
authors.lastname: Pazhayattil
authors.affiliation: Apotex Inc., 150 Signet Drive, Toronto, Ontario, M9L 1T9, Canada.
authors.forename: Shu
authors.initials: S
authors.lastname: Chen
authors.affiliation: Apotex Inc., 150 Signet Drive, Toronto, Ontario, M9L 1T9, Canada.
authors.forename: Francesco
authors.initials: F
authors.lastname: Munaretto
authors.affiliation: Apotex Inc., 150 Signet Drive, Toronto, Ontario, M9L 1T9, Canada.
authors.forename: Maksuda
authors.initials: M
authors.lastname: Hye
authors.affiliation: Apotex Inc., 150 Signet Drive, Toronto, Ontario, M9L 1T9, Canada.
authors.forename: Pradeep
authors.initials: P
authors.lastname: Sanghvi
mesh_terms: D002626:Chemistry, Pharmaceutical / Q000379:methods*; D004345:Drug Industry; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D011336:Probability; D011786:Quality Control; D018570:Risk Assessment; D012995:Solubility; D012996:Solutions / Q000737:chemistry; D013678:Technology, Pharmaceutical / Q000379:methods*
chemical_list: D004364:Pharmaceutical Preparations; D012996:Solutions
keywords: FDA guidance; GMP and statistics; acceptance probability; pharmaceutical quality statistics; process validation lifecycle stages