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Linking Drug Stability to Manufacturing Risk Assessment Approaches. L. E. Kirsch Stability team leader. Stability in Design Space. L t End of Expiry. Post-Manuf. Kinetic Model. Manuf. Design Space Model. L 0 D 0. Manufacturing stability measurements: criteria and uses
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Linking Drug Stability to ManufacturingRisk Assessment Approaches L. E. Kirsch Stability team leader
Stability in Design Space Lt End of Expiry Post-Manuf. Kinetic Model Manuf. Design Space Model L0 D0 • Manufacturing stability measurements: criteria and uses • Rationality based on understanding of instability • Correlates to shelf-life • Correlates to risk: failure to reach desired shelf-life without exceeding critical instability target
Correlation between Shelf-life and Manufacturing-stability Measurements(preliminary long term stability studies) Shelf-life estimated from linear extrapolation of room temperature stability data
1.00 1 0.75 failure prob 0.50 0 0.25 0.00 .175 .200 .225 .250 .275 .300 D0 + L0 Logistical Regression Model for Stability Risk Assessment • Shelf-life = Time to 0.4 % lactam(linear extrapolation of long-term stability data) • Stability failure: Shelf-life < Desired target dating (e.g. 2 years) • Logistical Regression model: • probability of stability failure as a function of the manufacturing-stability measurements (L0 and D0, mole %)
Estimated Stability Risk application of logistical regression model Intermediate Scale Lab Bench Lots
21 20 19 18 17 16 compress force 15 14 13 12 11 10 9 500 1000 1500 2000 2500 total drying time Stability Risk Design SpacePilot scale-up gabapentin tablets using granulation drying time and compression force Stability Risk (%) <= 1.250 <= 2.500 <= 3.750 <= 5.000 <= 6.250 <= 7.500 <= 8.750 <= 10.000 > 10.000
Long-term stability • Objectives • Demonstrate relationship between Manufacturing-related stability measurement (MSM: D0 and L0) and shelf-life • Demonstrate/validate solid state degradation model • Construct definitive “Risk-based” Design Space Models • Current state • Studies underway