In Vivo Predictive Dissolution Flux Measurements. Konstantin Tsinman, PhD Chief Scientific Officer Pion Inc
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1 In Vivo Predictive Dissolution Flux Measurements Konstantin Tsinman, PhD Chief Scientific Officer Pion Inc
2 What do we mean by IVIVC? USP 1 : The establishment of a rational relationship between a biological property, or a parameter derived from a biological property produced by a dosage form, and a physicochemical property or characteristic of the same dosage form. FDA 2 : IVIVC is a predictive mathematical model describing the relationship between an in vitro property of a dosage form and a relevant in vivo response. 1. United States Pharmacopoeia. In vitro and In vivo Evaluations of Dosage Forms, 27th edition, Revision, Mack Publishing Co., Easton, PA., Guidance for industry, extended release oral dosage forms: development, evaluation and application of an in vitro/in vivo correlation. FDA, CDER, 1997.
3 What is Our Goal? FDA 2 : IVIVC is a predictive mathematical model describing the relationship between an in vitro property of a dosage form and a relevant in vivo response. In Vitro Property Math. Model In Vivo Response The Holy Grail of in vitro assay In Vitro Property In Vivo Response
4 Chasing the Perfect Model Real Man Plumbing Man
5 Looking for a Robust Predictive Model Real Man Absolutely Cylindrical Man Stomach of Absolutely Cylindrical Man Small intestine of Absolutely Cylindrical Man
6 Absorption is related to mass transport of drug compound from GIT through membranes Mass J ( GIT location, time) dadt ABS t
7 Flux is a measure of transport: the net number of moles of particles crossing unit area per unit time perpendicular to unit area Definition Fick s First Law Flux J 1 A dm dt V A A dc dt A P e c D ( t)
8 Permeability, Solubility Excipients Classification Gradient Map Permeability Suppressed Solubility Enhanced Flux Unchanged ph Collaborative Effort of Pion and H. La Roche Avdeef et al. Eur J Pharm Sci. 2008;33(1):29 41; Avdeef et al. Pharm. Res., 2007, 24, ; Bendels et al. Pharm. Res. 2006, 23,
9 Permeability, Solubility Excipients Classification Gradient Map Permeability Suppressed Solubility Enhanced Flux Enhanced ph Collaborative Effort of Pion and H. La Roche Avdeef et al. Eur J Pharm Sci. 2008;33(1):29 41; Avdeef et al. Pharm. Res., 2007, 24, ; Bendels et al. Pharm. Res. 2006, 23,
10 Why Dissolution Study May Not Predict In Vivo Data? M. Kataoka, et al., Pharm. Res., 2012, 29,
11 Flux Studies using µflux Setup Flux dm J ( t) Pe cd ( t) Adt Fiber Optic Probes Donor Compartment SGF->FaSSIF transition Separating Membrane Pion GIT-PAMPA Receiver Compartment Sink buffer ph 7.4 Combining benefits of in situ concentration monitoring with parallel dissolution-permeability setup
12 Dissolution/Flux in FaSSIF Research Compound SGF FaSSIF transformation after 30 min of the assay Winner formulation performed best in dog model
13 Risk Assessment of ph Modifying Drugs Small Volume Flux Measurements Andy Z. X. Zhu, et. al. Utilizing In Vitro Dissolution-Permeation Chamber for the Quantitative Prediction of ph-dependent Drug-Drug Interactions with Acid-Reducing Agents: a Comparison with Physiologically Based Pharmacokinetic Modeling AAPS J., 2016, DOI: /s
14 Relating Flux Increase In Vivo Absorption Rate Vessel-in-Vessel Flux Setup Relative Max Abs Rate In Vivo Itraconazole Bend Research (Lonza) Relative Flux In Vitro Fed Conditions 1. Stewart AM et al. Development of a Biorelevant, Material-Sparing Membrane Flux Test for Rapid Screening of Bioavailability-Enhancing Drug Product Formulations. Mol Pharm [Internet] Jun 5;14(6): Stewart AM, et al. Impact of Drug-Rich Colloids of Itraconazole and HPMCAS on Membrane Flux in Vitro and Oral Bioavailability in Rats. Mol Pharm [Internet] Jul 3;14(7):
15 Formulations of Itraconazole 1 µflux Results (in vitro) Correlation with Rat PK data (in vivo) 1 Tsinman et al. Ranking Itraconazole Formulations Based on the Flux through Artificial Lipophilic Membrane. Pharm Res. 2018;35(8).
16 Can Flux Data Predict Absorption? Dose Number Dissolution Number D 0 S GIT Dose ( mg) ( mg / ml) V GIT ( ml) D k t 1 n Diss(min ) tran (min) Permeability Number P k t 1 n Perm(min ) tran (min) F a 1 exp 1 D n 1 D P 0 n Sugano K. Biopharmaceutics Modelling and Simulation. Wiley & Sons. 2012
17 How to Capture Biorelevance for Absorption Numbers Permeability Number A P k t k P V 1 GIT n Perm(min ) tran(min); Perm eff GIT For Biorelevance either k ( in vitro) k ( in vivo) Perm or Perm P ( in vitro) P ( in vivo) eff A V GIT GIT eff ( in vivo) is used
18 How Biorelevant is Double-Sink PAMPA? For HJ Permeability absorption rate was measured and the cylindrical model was applied, i.e. A GIT V GIT 2 R SI Avdeef et al. J Pharm Sci (11): The same membrane is used in FLUX Measurements!
19 Solubility/Permeability in Formulation Developability Classification System (DCS) Solubility Limited Cases: Flux J P e S J. Buttler, J. Dressman. The Developability Classification System: Application of Biopharmaceutics Concepts to Formulation Development. J. Pharm. Sci., Vol. 99, (2010)
20 DCS and Flux What Flux value should be a target to be Class 1 of DCS? J P e S 10 4 ( cm / s) Dose ( mg) 3 500( cm ) Dose( mg min 1 cm 2 ) Example: Q. Projected Dose is 200 mg. What flux should we target by changing formulations? A. J = 1.2*200*10-5 = 2.4*10-3 mg/(min cm 2 ) = 2.4 µg/(min cm 2 ) Assumptions: Permeability through PAMPA membrane represents human jejunum permeability; Flux does not change (no supersaturation/precipitation phenomenon)
21 Projected Dose and Flux Example: What is the Dose limit to stay DCS Class 1 for a particular Flux value Dose J ( mg) Q. The measured flux for my formulation is 0.1 µg/(min cm 2 ). What dose would still be classified as DCS Class 1? A. D 0 = 8.3*10 4 *0.1*10-3 = 8.3 (mg) Assumptions: Permeability through PAMPA membrane represents human jejunum permeability; Flux does not change (no supersaturation/precipitation phenomenon)
22 Estimation of the Fraction Absorbed Solubility-Permeability Limiting Cases F a P D n 0 J A ( SI ) T VSI mdose V SI transit For the Case of Absolutely Cylindrical Man A SI V SI 2 2 m ; Dose Dose( mg) / 250( ml) R 1.5( cm) V SI SI
23 Formulations of Itraconazole 1 F a (max) *100% % F a (min) *100% % 1 Tsinman et al. Ranking Itraconazole Formulations Based on the Flux through Artificial Lipophilic Membrane. Pharm Res. 2018;35(8).
24 Maximum and Minimum Absorbable Dose Supersaturating-Precipitating Formulations Donor Chamber Supersaturating Formulation FLUX Receiver Chamber Late Flux Initial Flux M M ABS ABS max min k k t t J J init late dadt dadt
25 MacroFLUX to Study Final Dosage Forms FO Probe connected to Rainbow instrument Absorption Chamber Separating lipophilic membrane FO Probe connected to Rainbow instrument USP compatible Vessel 250 ml 900 ml Overhead stirrer BioFLUX
26 Bioequivalence Study for Generics Brand and Generic Formulations of Telmisartan O OH CH 3 N N CH 3 N CH 3 N Borbás E, et al. The effect of formulation additives on in vitro dissolution-absorption profile and in vivo bioavailability of telmisartan from brand and generic formulations. Eur J Pharm Sci. 2018;114(1):310 7.
27 Sorbitol Formulations Ingredients Lactose Mannitol
28 Predicting Risks in Bioequivalence Studies
29 Drug-Drug Interaction (Drug Products) ph Modifying Agents Type-I Type-II ph 1.6 ph 6.5 ph 4.0 ph 6.5 Normal SGF FaSSIF ph 1.6 ph 6.5 Alkalized SGF FaSSIF ph 4.0 ph 6.5 Li et al. Using ph Gradient Dissolution with In-Situ Flux Measurement to Evaluate Bioavailability and DDI for Formulated Poorly Soluble Drug Products. AAPS PharmSciTech (in publication)
30 GDC , BCS Class IIb Strong DDI Expected in Clinical Studies >90% reduction in flux and absorbed amount in vitro ~80% reduction in AUC due to DDI of ARA in Pang J, Dalziel G, Dean B, Ware JA, Salphati L. Mol Pharm. 2013;10(11): dog PK studies
31 Compound C (BCS Class IIb) Product Formulated to Minimize DDI from ARA
32 Food Effect To eat or not to eat Commercial Itraconazole Formulations
33 BioFLUX In Vitro In Vivo 250 ml FaSSIF FeSSIF Negative Positive In Vivo: Positive Food Effect for Capsules Slight Negative for Solution Brouwers J, Geboers S, Mols R, Tack J, Augustijns P. Int J Pharm. 2017;525(1):211 7.
34 Conclusions Flux assays allow investigation of complex formulations and building realistic PK predictions Introduction of absorption chamber into dissolution setup can lead to more biorelevant dissolution studies It was demonstrated that relatively simple and robust flux measurements can provide great in vitro tool capable of capturing major factors related to absorption thus leading to realistic IVIVC Complication of the in vitro model does not necessary mean that better IVIVC can be achieved
35 Select Your Man Wisely For Biorelevance Study
36 Acknowledgements Oksana Tsinman Bálint Sinko Larry Wigman Jane Li Enikó Borbas Zsombor K. Nagy Bernd Riebesehl Michael Juhnke Arnaud Grandeury Bernard Van Eerdenbrugh Saijie Zhu
37 Thank You! Konstantin Tsinman, Ph.D. Chief Scientific Officer Pion Inc.
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