Dissolution with Functional DOE
This study delves into the importance of drug dissolution, presenting a comparison of multivariate modeling with functional DOE techniques. Explore the impact of dissolution testing on drug availability and the need for innovative approaches in pharmaceutical research.
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Presentation Transcript
A New Resolve to Dissolve-Model Drug Dissolution with Functional DOE 2021- US 30MP - 916 Amanjot (AJ) Kaur Statistician-Perrigo Rob Lievense Senior Systems Engineer-JMP
Topics Introduction Dissolution and why it is important Current methods Why new approach? Demonstrate the comparison of multivariate least squares modeling with functional DOE Closure Acceptance Criteria?
Introduction Immediate Release Extended Release 24 Hour Period 24 Hour Period
Drug Availability in Humans In a human body, a solid dose will release the active drug ingredient and will process the drug out of the body at given rates. Clinical studies will show a peaked result when the maximum amount is present in the blood, how long the dose is sustained, and the eventual decline of the drug in the bloodstream as it is excreted from the body. https://bpac.org.nz/BPJ/2009/generics/bio.aspx Sim D.S.M. (2015) Drug Absorption and Bioavailability. In: Chan Y., Ng K., Sim D. (eds) Pharmacological Basis of Acute Care. Springer, Cham. https://doi.org/10.1007/978-3-319-10386-0_3
Dissolution Dissolution testing measures the extent and rate of solution formation from a solid dosage form. The laboratory testing typically involves continuous build of drug concertation in media
Techniques we use today Trial and Error with F2 testing Similarity criterion used to compile the sum of square differences of percent released in media for multiple time points F2 value of 50 or higher indicates that the candidate batch is at most +/- 10% different from target batch at the same time points Multivariate least squares models Why we need new approach? F2 similarity trials and multivariate least squares models treat the time points as independent outputs. FDOE treats release over time as dependent functions and is anextremely robust and easy to use technique.
Techniques we use today Multivariate least squares models Creation of Multivariate Structured Experimentation (AKA: DOE) to try change many inputs in a series of runs to gain insight on the response dissolved 60 = 101.944120311185 -0.00605059236637259 * main compression force -302.365207463522 * polymer A% - 764.600918702791 * polymer B% + (main compression force - 2000) * ((polymer A% - 0.116666666666667) * 0.212190053883057) + (main compression force - 2000) * ((polymer B% - 0.03) * -0.0225652807332826) + (polymer A% - 0.116666666666667) * ((polymer B% - 0.03) *12744.8224101781)
Demonstration of Multivariate Least Squares Modeling (DOE)
Why we need new approach? F2 similarity trials and multivariate least squares models treat the time points as independent outputs, which does not make sense. FDOE treats release over time as dependent functions and is an extremely robust and easy to use technique.
Demonstration of Functional Design of Experiments (a JMP PRO capability)
Considerations A measurement plan must be established with the laboratory to ensure that there are enough early pulls of media to create a realistic early profile (<90 minutes) The accuracy and precision of the apparatus must be established to know the low limit as very small amounts in media may not be measured accurately The variation of the results within the time points must be known as high variability (>10% RSD) may require other methods
Next Steps Acceptance Criteria We found that the model error for the FDOE seems to be greater at early time points; likely due to low % dissolved and rapid rate of increase (creating higher variability) The amount of model error is critical for the establishment of acceptance criteria; there is likely a cumulative contribution of FPC s too low for practical use The integrated error from target might provide evidence for acceptance. Creating a sum of squares for the difference from target of important time points could allow for F2 similarity used for acceptance; however, more work is needed to explore the concept
