Integrated biopharmaceutical approach in pharmaceutical development and drug characterization: general concept and application

Main Article Content

Sandra Cvijić
Svetlana Ibrić
Jelena Parojčić

Abstract

The importance of biopharmaceutical considerations in pharmaceutical development and drug characterization has been well recognized both by pharmaceutical industry and regulatory authorities as a tool to establish predictive relationships between drug product quality attributes (in vitro data) and its clinical performance (in vivo data). In the present paper, contemporary biopharmaceutics toolkit including in vivo predictive dissolution testing, Biopharmaceutics Classification System, physiologically based pharmacokinetic and biopharmaceutics modeling and simulation, in vitro-in vivo correlation and biowaiver, are reviewed with regards to relevant general principles and applicability. The recently introduced innovative strategy for patient-centric drug development using an integrated systems approach grounded in fundamental biopharmaceutics concepts, clinical insights and therapeutic drug delivery targets, described as Biopharmaceutics Risk Assessment Roadmap (BioRAM) is also presented. Further development in the field will benefit from joint efforts and exchange of knowledge and experiences between pharmaceutical industry and regulatory authorities for the common goal to accelerate development of effective and safe drug products designed in accordance with patients needs and expectations.

Article Details

How to Cite
[1]
S. Cvijić, S. Ibrić, and J. Parojčić, “Integrated biopharmaceutical approach in pharmaceutical development and drug characterization: general concept and application”, Hem Ind, vol. 74, no. 6, pp. 389–397, Jan. 2021, doi: 10.2298/HEMIND210104002C.
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How to Cite

[1]
S. Cvijić, S. Ibrić, and J. Parojčić, “Integrated biopharmaceutical approach in pharmaceutical development and drug characterization: general concept and application”, Hem Ind, vol. 74, no. 6, pp. 389–397, Jan. 2021, doi: 10.2298/HEMIND210104002C.

References

Kaplan SA. Biopharmaceutical Considerations in Drug Formulation Design and Evaluation, Drug Metab Rev 1972; 1 (1): 15-33.

Kaplan SA. Biological implications of in vitro dissolution testing. In Leeson L, Cartensen JT, Eds. Dissolution Technology: The Industrial Pharmaceutical Technology Section of Pharmaceutical Sciences, Washington DC.1974; p. 167

Amidon GL, Lennernäs H, Shah VP, Crison JR, A Theoretical Basis for a Biopharmaceutic Drug Classification: The Correlation of in Vitro Drug Product Dissolution and in Vivo Bioavailability, Pharm Res. 1995; 12: 413–420.

Hodgson J. ADMET—turning chemicals into drugs. Nat Biotechnol 2001; 19: 722–726.

EMA Committee for Human Medicinal Products ICH guideline Q8 (R2) on pharmaceutical development (EMA/CHMP/ICH/167068/2004), 2017

Yu LX, Amidon G, Khan MA, Hoag SW, Polli J, Raju GK, Woodcock J. Understanding pharmaceutical quality by design. AAPS J. 2014; 16(4):771-783.

Selen A, Dickinson PA, Müllertz A, Crison JR, Mistry HB, Cruañes MT, Martinez MN, Lennernäs H, Wigal TL, Swinney DC, Polli JE, Serajuddin ATM, Cook JA, Dressman JB. The Biopharmaceutics Risk Assessment Roadmap for Optimizing ClinicalDrug Product Performance. J Pharm Sci. 2014;103: 3377–3397.

Dickinson PA, Kesisoglou F, Flanagan T, Martinez MN, Mistry HB, Crison JR, Polli JE, Cruañes MT, Serajuddin ATM, Müllertz A, Cook JA, Selen A. Optimizing Clinical Drug Product Performance: Applying Biopharmaceutics Risk Assessment Roadmap (BioRAM) and the BioRAM Scoring Grid. J Pharm Sci. 2016;105(11):3243-3255.

Selen A, Müllertz A, Kesisoglou F, Ho RJY, Cook AU, Dickinson PA, Flanagan T. Integrated Multi-stakeholder Systems Thinking Strategy: Decision-making with Biopharmaceutics Risk Assessment Roadmap (BioRAM) to Optimize Clinical Performance of Drug Products. AAPS J. 2020; 22:97.

Tsume Y, Mudie DM, Langguth P, Amidon GE, Amidon GL. The biopharmaceutics classification system: subclasses for in vivo predictive dissolution (IPD) methodology and IVIVC. Eur J Pharm Sci. 2014;57:152–163.

Lennernäs H, Lindahl A, Van Peer A, Ollier C, Flanagan T, Lionberger T, Nordmark T, Yamashita S, Yu L, Amidon GL, Fischer V, Sjögren E, Zane P, McAllister M, B Abrahamsson B. In Vivo Predictive Dissolution (IPD) and Biopharmaceutical Modeling and Simulation: Future Use of Modern Approaches and Methodologies in a Regulatory Context. Mol Pharm. 2017;14 (4): 1307-1314.

Bermejo M, Meulman J, Davanço MG, de O. Carvalho P, Gonzalez-Alvarez I, Campos DR. In vivo predictive dissolution (Ipd) for carbamazepine formulations: Additional evidence regarding a biopredictive dissolution medium. Pharmaceutics. 2020;12 (6): 558.

Garbacz G, Klein S, Weitschies W. A biorelevant dissolution stress test device – background and experiences. Expert Opin Drug Deliv 2010; 7 (11): 1251-1261.

Amidon GL, Tsume Y. Oral product input to the GI tract: GIS an oral product performance technology. Front Chem Sci Eng. 2017; 11: 516–520.

Felicijan T, Pislar M, Vene K, Bogataj M. The influence of simulated fasted gastrointestinal pH profiles on diclofenac sodium dissolution in a glass-bead flow-through system. AAPS PharmSciTech. 2018;19(7):2875–2884.

Butler J, Hens B, Vertzoni M, Brouwers J, Berben P, Dressman J, Andreas CJ, Schaefer KJ, Mann J, McAllister M, Jamei M, Kostewicz E, Kesisoglou F, Langguth P, Minekus M, Müllertz A, Schilderink R, Koziolek M, Jedamzik P, Weitschies W, Reppas C, Augustijns P. In vitro models for the prediction of in vivo performance of oral dosage forms: recent progress from partnership through the IMI OrBiTo collaboration, Eur J Pharm Biopharm. 2019; 136: 70-83.

Grady H, Elder D, Webster GK, Mao Y, Lin Y, Flanagan T, Mann J, BlanchardA, Cohen MJ, Lin J, Kesisoglou F, Hermans A, Abend A, Zhang L, Curran D, Industrys View on UsingQuality Control, Biorelevant and Clinically Relevant Dissolution Tests for Pharmaceutical Development, Registration and Commercialization, J Pharm Sci. 2018; 107 (1):34-41.

McAllister M, Flanagan T, Boon K, Pepin X, Tistaert C, Jamei M, Abend A, Kotzagiorgis E, Mackie C. Developing Clinically Relevant Dissolution Specifications for Oral Drug Products-Industrial and Regulatory Perspectives. Pharmaceutics. 2019;12(1):19.

Hermans A, Abend AM, Kesisoglou F, Flanagan T, Cohen MJ, Diaz DA, Mao Y, Yhang L, Webster GK, Lin Y, Hahn DA, Coutant CA, Grady H. Approaches for Establishing Clinically Relevant Dissolution Specifications for Immediate Release Solid Oral Dosage Forms. AAPS J 2017;19: 1537–1549.

Zane P, Gieschen H, Kersten E, Mathias N, Ollier C, Johansson P, Van den Bergh A, Van Hemelryck S, Reichel A, Rotgeri A, Schäfer K, Müllertz A, Langguth P. In vivo models and decision trees for formulation development in early drug development: A review of current practices and recommendations for biopharmaceutical development. Eur J Pharm Biopharm. 2019;142:222-231.

EMA Committee for Human Medicinal Products ICH M9 guideline on biopharmaceutics classification system-based biowaivers (EMA/CHMP/ICH/493213/2018), 2020

Tsume Y, Mudie DM, Langguth P, Amidon GE, Amidon GL. The Biopharmaceutics Classification System: subclasses for in vivo predictive dissolution (IPD) methodology and IVIVC. Eur J Pharm Sci. 2014;57:152-163.

Wu CY, Benet LZ. Predicting drug disposition via application of BCS: transport/absorption/ elimination interplay and development of a biopharmaceutics drug disposition classification system. Pharm Res. 2005;22(1):11-23.

Butler JM, Dressman JB. The developability classification system: application of biopharmaceutics concepts to formulation development. J Pharm Sci. 2010;99(12):4940-4954.

Sugano K. Theoretical Investigation of Dissolution Test Criteria for Waiver of Clinical Bioequivalence Study. J Pharm Sci. 2016;105(6):1947-1951.

Macheras P, Karalis V. A non-binary biopharmaceutical classification of drugs: the ABΓ system. Int J Pharm. 2014;464(1-2):85-90.

Gatarić B, Parojčić J. Application of data mining approach to identify drug subclasses based on solubility and permeability. Biopharm Drug Dispos. 2019;40(2):51-61.

Shawahna R. Pediatric Biopharmaceutical Classification System: Using Age-Appropriate Initial Gastric Volume. AAPS J. 2016;18(3):728-736.

Martinez M, Augsburger L, Johnston T, Jones WW. Applying the biopharmaceutics classification system to veterinary pharmaceutical products. Part I: biopharmaceutics and formulation considerations. Adv Drug Deliv Rev. 2002;54(6):805-824.

Hastedt JE, Bäckman P, Clark AR, Doub W, Hickey A, Hochhaus G, Kuehl PJ, Lehr C-M, Mauser P, McConville J, Niven R, Sakagimi M, Weers JG. Scope and relevance of a pulmonary biopharmaceutical classification system AAPS/FDA/USP Workshop March 16-17th, 2015 in Baltimore, MD. AAPS Open 2016;2: 1.

Shah VP, Rădulescu FŞ, Miron DS, Yacobi A. Commonality between BCS and TCS. Int J Pharm. 2016;509(1-2):35-40.

Yu LX, Amidon GL. A compartmental absorption and transit model for estimating oral drug absorption. Int J Pharm. 1999;186(2):119-125.

Agoram B, Woltosz WS, Bolger MB. Predicting the impact of physiological and biochemical processes on oral drug bioavailability. Adv Drug Deliv Rev. 2001;50 Suppl 1:S41-S67.

Kostewicz ES, Aarons L, Bergstrand M, Bolger MB, Galetin A, Hatley O, Jamei M, Lloyd R, Pepin X, Rostami-Hodjegan A, Sjögren E, Tannergren C, Turner DB, Wagner C, Weitschies W, Dressman J. PBPK models for the prediction of in vivo performance of oral dosage forms. Eur J Pharm Sci. 2014;57:300-321.

Lamberti G, Cascone S, Marra F, Titomanlio G, dAmore M, Barba AA, Gastrointestinal behavior and ADME phenomena: II. In silico simulation. J Drug Deliv Sci Technol. 2016; 35: 165-171.

Lin L, Wong H. Predicting Oral Drug Absorption: Mini Review on Physiologically-Based Pharmacokinetic Models. Pharmaceutics. 2017; 9: 41.

Li GF, Wang K, Chen R, Zhao HR, Yang J, Zheng QS. Simulation of the pharmacokinetics of bisoprolol in healthy adults and patients with impaired renal function using whole-body physiologically based pharmacokinetic modeling. Acta Pharmacol Sin. 2012; 33: 1359-1371.

Almukainzi M, Jamali F, Aghazadeh-Habashi A, Löbenberg R. Disease specific modeling: Simulation of the pharmacokinetics of meloxicam and ibuprofen in disease state vs. healthy conditions. Eur J Pharm Biopharm. 2016; 100:77-84.

Villiger A, Stillhart C, Parrott N, Kuentz M. Using Physiologically Based Pharmacokinetic (PBPK) Modelling to Gain Insights into the Effect of Physiological Factors on Oral Absorption in Paediatric Populations. AAPS J. 2016; 18: 933-947.

Chetty M, Johnson TN, Polak S, Salem F, Doki K, Rostami-Hodjegan A. Physiologically based pharmacokinetic modelling to guide drug delivery in older people. Adv Drug Deliv Rev. 2018; 135: 85-96.

EMA Committee for Human Medicinal Products Guideline on the pharmacokinetic and clinical evaluation of modified release dosage forms (EMA/CPMP/EWP/280/96 Corr1), 2014.

Dickinson PA, Lee WW, Stott PW, Townsend AI, Smart JP, Ghahramani P, Hammett T, Billett L, Behn S, Gibb RC, Abrahamsson B. Clinical Relevance of Dissolution Testing in Quality by Design. AAPS J 2008;10: 380–390.

Suarez-Sharp S, Li M, Duan J, Shah H, Seo P. Regulatory Experience with In Vivo In Vitro Correlations (IVIVC) in New Drug Applications. AAPS J. 2016;18(6):1379-1390.

Kovačević I, Parojčić J, Homšek I, Tubić –Grozdanis M, Langguth P. Justification of Biowaiver for Carbamazepine, a LowSoluble High Permeable Compound, in Solid DosageForms Based on IVIVC and Gastrointestinal Simulation. Mol Pharm 2009; 6 (1): 40-47.

Grbić S, Parojčić J, Ibrić S, Đurić Z. In Vitro–In Vivo Correlation for Gliclazide Immediate-Release Tablets Based on Mechanistic Absorption Simulation. AAPS PharmSciTech. 2011; 12: 165–171.

Ilić M, Ðuriš J, Kovačević I, Ibrić S, Parojčić J. In vitro--in silico--in vivo drug absorption model development based on mechanistic gastrointestinal simulation and artificial neural networks: nifedipine osmotic release tablets case study. Eur J Pharm Sci. 2014; 62:212-218.

Beloica S, Cvijić S, Homšek I, Bogataj M, Parojčić J. An in vitro - in silico - in vivo approach in biopharmaceutical drug characterization: metformin hydrochloride IR tablets. Pharmazie. 2015; 70: 458-465.

Stillhart C, Pepin X, Tistaert C, Good D, Van Den Bergh A, Parrott N, Kesisoglou F. PBPK Absorption Modeling: Establishing the In Vitro-In Vivo Link-Industry Perspective. AAPS J. 2019; 21:19.

Bermejo M, Hens B, Dickens J, Mudie D, Paixão P, Tsume Y, Shedden K, Amidon GL. A Mechanistic Physiologically-Based Biopharmaceutics Modeling (PBBM) Approach to Assess the In Vivo Performance of an Orally Administered Drug Product: From IVIVC to IVIVP. Pharmaceutics. 2020; 12(1): 74.

FDA Guidance for Industry: Extended Release Solid Oral Dosage Forms: Development, Evaluation and Application of In Vitro/In Vivo Correlations, September 1997.

EMA Guideline on quality of oral modified release products (EMA/CHMP/QWP/428693/2013) 2014

EMA Reflection Paper on the Dissolution Specification for Generic Solid OralImmediate Release Products with Systemic Action (EMA/CHMP/CVMP/QWP/336031/2017); 2017

EMA Guideline on the reporting of physiologically based pharmacokinetic (PBPK) modelling and simulation (EMA/CHMP/458101/2016), 2018

Food and Drug Administration Center for Drug Evaluation and Research, Guidance for Industry Physiologically Based Pharmacokinetic Analyses — Format and Content, 2018

Food and Drug Administration Center for Drug Evaluation and Research, The Use of Physiologically Based Pharmacokinetic Analyses — Biopharmaceutics Applications for Oral Drug Product Development, Manufacturing Changes, and Controls Guidance for Industry, 2020

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