Simulations Plus, Inc. · NASDAQ:SLP
Simulations Plus — MIDD+ 2023
34 slides from Simulations Plus's conference presentation, February 2023
Slide 1: Application of PBBM Modeling in Generic Product Development: Regulatory Applications and Case Studies
Application of PBBM Modeling in Generic Product Development: Regulatory Applications and Case Studies Dr. Tausif Ahmed Head-Biopharmaceutics and Bioequivalnce, Global Clinical Management Dr. Reddy‘s Laboratories, Hyderabad, India Model Informed Drug Development MIDD+, Feb 2023
Slide 2: Disclaimer
Disclaimer The opinions expressed herein are solely those of the presenter and do not represent statements or opinions of Dr. Reddy’s Laboratories Ltd. 2
Slide 3: Agenda
Agenda • PBBM modeling in generic product development • PBBM model development • General modeling workflow • Dissolution data integration • Bio-predictive vs QC dissolution media • Case studies • Biowaiver of lower strength due to f2 mismatch • Biowaiver for BE leverage • Dissolution specification j
Slide 4: Applications of PBBM modeling drug product life cycle
Applications of PBBM modeling drug product life cycle • PBBM modeling in generic product development can be initiated as early as Ph-III/IV or Ph-IV/launch 4
Slide 5: PBBM Modeling in generic product development
PBBM Modeling in generic product development • PBBM / PBPK modeling is a tool that can combine API, formulation, pharmacokinetics with physiology to enable prediction of in vivo exposures (i.e. plasma conc. time profiles) in fasting & fed conditions • In generic industry, PBBM modeling has various a
Slide 6: PBBM Modeling – Regulatory guidance’s
PBBM Modeling – Regulatory guidance’s • Apart from USFDA, EMA, other agencies such as ANVISA, MEDSAFE, CDE are also open to PBBM submissions 6
Slide 7: PBBM model development – general workflow
PBBM model development – general workflow • Literature data, experimental data, ADMET predicted data • Adequate justification for all input parameters • Validation against literature data, in-house data, population bioequivalence and virtual simulations • Population – representative of clinical stud
Slide 8: Dissolution data integration
Dissolution data integration • Dissolution is critical input into PBBM models as it governs in vivo exposure • Multiple models are available for IR, MR and DR formulations • IR: API PSD, direct dissolution input, z-factors • MR: direct dissolution input, Weibull function, IVIVC/IVIVR • DR: z-factor,
Slide 9: P-PSD model using DDDPlus
P-PSD model using DDDPlus • P-PSD determines effective API PSD in the formulation • It can be transferred to Gastroplus without having need of additional dissolution input • P-PSD to be further validated with additional media’s and formulation variants Ref: Best Practices for Integration of Dissolut
Slide 10: QC Vs Bio-predictive dissolution media
QC Vs Bio-predictive dissolution media • All regulatory queries or justifications are based on QC media, however it may not be bio-predictive • Along with QC media, separate bio-predictive media can help to imbed quality into product development – from manufacturability and clinical perspectives 10
Slide 11: Dissolution safe space
Dissolution safe space • Dissolution / BE safe space is based on pivotal test BE lot and can further be verified using other clinical studies data and helps to identify non-BE batches 11
Slide 12: Case studies
DrReddy's @ Case studies
Slide 13: Case study#1: Bio-waiver of lower strength in case of f2 mismatch
Case study#1: Bio-waiver of lower strength in case of f2 mismatch • Weakly acidic BCS III compound available in 5 strengths: 40, 80, 120, 160, 320mg • Solubility low in acidic and increases significantly in basic condition • Crossover fasting BE study conducted on higher strength and BE achieved at
Slide 14: Case study#1: Biowaiver of lower strength in case of f2 mismatch
Case study#1: Biowaiver of lower strength in case of f2 mismatch No impact of failing f2 on BE, biowaiver for 40mg was granted 14
Slide 15: Case study#1: Biowaiver of lower strength in case of f2 mismatch
Case study#1: Biowaiver of lower strength in case of f2 mismatch Pivotal 320mg study BE validation Cost, time With Z-factor vs pH input savings, early launch Pivotal 320mg study BE validation 40mg disso against Cmax AUC0-t AUC0-inf T/R (90% CI) 320mg pivotal Test 99.36 99.44 99.40 (89.65- (89.13- (8
Slide 16: Case study#2: Biowaiver for study leverage, f2 failure
Case study#2: Biowaiver for study leverage, f2 failure • BCS Class III API, formulation available in two strengths 50mg and 100mg • Reference & test have two salts, but with same solubility • BE fasting study was conducted on 100mg in Market-A and while leveraging product to Market-B, reference prod
Slide 17: Case study#2: Biowaiver for study leverage, f2 failure
Case study#2: Biowaiver for study leverage, f2 failure Pivotal 100mg study validation Z-factor vs pH input PK parameter Predicted values Geometric mean ratio 90% confidence intervals 100mg Pivotal Ref vs Pivotal Test Cmax (ng/mL) 100.4 [104.36] * 91.64-109.90 [97.63-111.56] * AUC0-inf (ng.h/mL) 100.
Slide 18: Case study#2: Biowaiver for study leverage, f2 failure
Case study#2: Biowaiver for study leverage, f2 failure BE safe space of 85% in 60 min was determined without impacting bioequivalence 18
Slide 19: Case study#2: Biopharmaceutics risk assessment strategy for BCS I, III biowaivers
Case study#2: Biopharmaceutics risk assessment strategy for BCS I, III biowaivers 19
Slide 20: Case study#3: Dissolution specifications justification for ER formulation
Case study#3: Dissolution specifications justification for ER formulation • Product is formulated as extended release, with Specification time Existing Revised three time point specification point specifications specifications • Proposal was made to revise dissolution 2h ≤10% ≤10% specifications at
Slide 21: Case study#3: Dissolution specifications justification for ER formulation
Case study#3: Dissolution specifications justification for ER formulation Pivotal study validation of Reference (A) and Virtual Disso profiles generated at low profile Test (B) (LP) and single point lower profile (SPLP) Parameter Geometric Means % Geometric (90 % CI) Test Reference Mean Ratio Hypoth
Slide 22: Common regulatory queries on PBBM justifications
Common regulatory queries on PBBM justifications Query / concern Probable solution Justification / optimization performed for model Experimental or literature support for model parameters inputs (e.g. Peff) PSA to demonstrate optimized value, details about optimization algorithm used Z-factor for di
Slide 23: Conclusions
Conclusions ● PBBM modeling has demonstrated applications in both generic and innovator domain ● Apart from USFDA, other agencies such as ANVISA, MEDSAFE, CDE open to modeling based justifications ● For generics, PBBM modeling has clearly demonstrated its value to avoid BE studies in cases of dissol
Slide 24: Acknowledgements
Acknowledgements ● Sivacharan K and Biopharmaceutics team at Global Clinical Management (GCM) group at DRL ● DRL Management for providing all infrastructure and support ● All other CFTs, collaborators and Regulator’s who have contributed to the data generation/feedback for these case studies ● Simul
Slide 25: References
References • Wu D et al. Physiologically Based Pharmacokinetics Modeling in Biopharmaceutics: Case Studies for Establishing the Bioequivalence Safe Space for Innovator and Generic Drugs, Pharm. Res. doi: 10.1007/s11095-022-03319-6 • Kollipara S et al. Best Practices for Integration of Dissolution Da
Slide 26: Thank You
Dr.Reddy's @* Thank You
Slide 27: BACKUP
BACKUP 27
Slide 28: PBBM Modeling
PBBM Modeling Dissolution data Calculate ) Evaluate Check impact of Validate with y.Reddy's q (solubilit 5 solubility, time multiple Sleetaatetetaiatiatataiatetetetetatatel fs ty, z-factor z-factor fitting : ty, Pr leieietetetetatetatalal volume, dose) points, shape formulations (a) Impact of solubi
Slide 29: PBBM Modeling
PBBM Modeling (a) Simple time scaling with Weibull Develop model for MR formulation H M4 Input physchem, elimination kinetics Time sang approach - Invitro data 1» 4 9 0 io 8 so —~-Original data a6 ites caiigs * 30 2 ° os os mm mo Time (h) ‘Time scaling approach - In vivo data Criginal observed data
Slide 30: PBBM Modeling
PBBM Modeling (a) _| Fit original dissolution data to Weibull (single/double/triple) | Use same shape factor, adjust extent to get required release Virtual profiles with different release rates Virtual profiles using Weibull equation ~~-Original data ——-85% in 30, 85% in 45 min. —-85% in 60 min 10 2
Slide 31: MR formulation development using PBBM modeling
MR formulation development using PBBM modeling 31
Slide 32: Safe space using PBBM
Safe space using PBBM Dissolution Safe Space API PSD Safe Space CPP/CMA Safe Space Dissolution profiles with Dissolution profiles with different API PSD. different CPP’s / CMA’s t ' Disso spec Virtual profiles Non BE batch In vitro / In vivo Disso spe generation correlation (IVIVC) justification Tow
Slide 33: Case study: Biowaiver of lower strength of Dasatinib tablets with PBBM modeling
Case study: Biowaiver of lower strength of Dasatinib tablets with PBBM modeling • Weakly basic molecule with pH dependent solubility (high in acidic and extremely poor in basic) • Full replicate study was conducted on higher strength 100mg, waiver requested for 20mg based on comparative dissolution
Slide 34: Case study: Biowaiver of lower strength of Dasatinib tablets with PBBM modeling
Case study: Biowaiver of lower strength of Dasatinib tablets with PBBM modeling Cost, time 20mg input to savings, 100mg 100mg 20mg 100mg model early launch validation PK Parameter T/R [Faster disso of 20mg / 100mg] Cmax (ng/mL) 100.15 AUCt (ng.h/mL) 101.34 AUCinf (ng.h/mL) 100.76 No impact of faster