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Fifty-Eight Years and Counting: High-Impact Publishing in Computational Pharmaceutical Sciences and Mechanism-Based Modeling
Journal of Pharmaceutical Sciences xxx (2018) 1-6
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Journal of Pharmaceutical Sciences journal homepage: www.jpharmsci.org
General Commentary
Fifty-Eight Years and Counting: High-Impact Publishing in Computational Pharmaceutical Sciences and Mechanism-Based Modeling Gregory E. Amidon 1, *, Bradley D. Anderson 2, Joseph P. Balthasar 3, Christel A.S. Bergstrom 4, Shiew-Mei Huang 5, Gerald Kasting 6, Filippos Kesisoglou 7, Johannes G. Khinast 8, Donald E. Mager 3, Christopher J. Roberts 9, Lian Yu 10 1
University of Michigan, Ann Arbor, Michigan 48109 University of Kentucky, Lexington, Kentucky 40506 3 University at Buffalo, State University of New York, Buffalo, New York 14260 4 Uppsala University, Uppsala, Sweden 5 Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland 20993 6 University of Cincinnati, Cincinnati, Ohio 45220 7 Merck & Co., Inc., Kenilworth, New Jersey 07033 8 Institute for Process and Particle Engineering, Graz University of Technology, Graz, Austria 9 University of Delaware, Newark, Delaware 19716 10 University of Wisconsin, Madison, Wisconsin 53706 2
a r t i c l e i n f o
a b s t r a c t
Article history: Received 1 November 2018 Accepted 2 November 2018
With this issue of the Journal of Pharmaceutical Sciences, we celebrate the nearly 6 decades of contributions to mechanistic-based modeling and computational pharmaceutical sciences. Along with its predecessor, The Journal of the American Pharmaceutical Association: Scientific Edition first published in 1911, JPharmSci has been a leader in the advancement of pharmaceutical sciences beginning with its inaugural edition in 1961. As one of the first scientific journals focusing on pharmaceutical sciences, JPharmSci has established a reputation for publishing high-quality research articles using computational methods and mechanism-based modeling. The journal’s publication record is remarkable. With over 15,000 articles, 3000 notes, and more than 650 reviews from industry, academia, and regulatory agencies around the world, JPharmSci has truly been the leader in advancing pharmaceutical sciences. © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
Keywords: absorption, distribution, metabolism, and excretion (ADME) biophysical model(s) in silico modeling in vitro model(s) mathematical model(s) mechanistic modeling molecular modeling pharmacokinetic/pharmacodynamic (PKPD) modeling physiologically based pharmacokinetic (PBPK) modeling
Introduction In this issue, we bring together the latest research in mechanismbased modeling and computational pharmaceutical sciences in a variety of areas where the Journal has excelled. Topics covered in this special issue include the following: Multiphase modeling applications in drug delivery and pharmaceutical technology. * Correspondence to: Gregory E. Amidon (Telephone: þ1-734-936-7438). E-mail address: [email protected] (G.E. Amidon).
Dissolution and transport considerations often combined with physiological models that enable better predictions of oral bioavailability, tumor, lymphatic, and brain delivery predictions. Mechanistic pharmacokinetic-pharmacodynamic (PKPD) modeling at the cellular, organ, and system levels leading to a better understanding of biological processes underlying drug delivery, efficacy, and safety with application in clinical studies. Mechanistic approaches and predictive modeling of biopharmaceutical stability and delivery.
https://doi.org/10.1016/j.xphs.2018.11.002 0022-3549/© 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
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Fundamental models to predict transport and binding phenomena through bilayers and biomembranes such as the skin, intestine, cornea, and blood-brain barrier. Models and mechanism-based predictions of phase miscibility, solubility, crystallization, or maintenance of supersaturation obtained by release from or dissolution of metastable delivery systems. Mechanism-based models to account for chemical and physical stability of therapeutic agents. The following sections capture a few of the most highly cited and high-impact articles published in the Journal of Pharmaceutical Sciences over the past 6 decades that have advanced our understanding of pharmaceutical science through mechanistic modeling and computational tools. Drug Delivery and Pharmaceutical Technology Among the earliest issues of the Journal are several landmark publications focusing on drug delivery and technology. The work of Takeru Higuchi1 and William Higuchi2 set the tone for quantitative mathematical modeling of dissolution from drug delivery systems with their landmark publications addressing the rate of release of drug suspended in ointment bases in the early 1960s. The 1963 publication by Takeru Higuchi3 on modeling of the mechanism of drug release of solid drug particles dispersed in solid matrices is the most cited publication from the Journal with nearly 3000 citations, and it continues to be highly referenced today. In the pharmaceutical technology area, Fell and Newton4 published a highly cited reference in 1970 quantitating tablet tensile strength as a critical quality attribute of tablet dosage forms while Hiestand et al.5 in the late 1960s and early 70s provided mechanistic insights into the mechanical properties of pharmaceutical solids along with novel experimental methods. More recently, the work of Lum and Duncan-Hewitt in 1999 addressed the mechanistic basis of particleparticle interactions and emphasized the importance of viscoelastic material properties,6 while the work of Tye, Sun, and Amidon advanced the science of tablet compaction with their 2005 publication demonstrating the process-independent relationship between tensile strength and tablet solid fraction.7 In advancing drug delivery technologies, Chiou and Riegelman reviewed the pharmaceutical applications of solid dispersion delivery systems8 and in 1975, Theeuwes9 described the novel technology of the osmotic pump for drug delivery. In the following decades, highly cited references include work by Henry and colleagues10 describing microfabricated microneedles as a novel approach to transdermal delivery. The work of Batycky and others developed a mechanistic model of erosion and macromolecular drug release from biodegradable microspheres11 and more recently, the review by Adams et al.12 captured the state of the science related to the use of amphiphilic block copolymers and the opportunity to tailor drug delivery through a mechanistic understanding of polymer properties. The advancement of nanoparticulate drug delivery systems came of age in the last part of the last century with publications by Bazile et al., Stella et al., Hilgenbrink and Low, and Hillyer and Albrecht.13-16 In their work, they addressed the mechanism of nanoparticle transport across the intestinal tract, the design of targeted nanoparticles, and stealth nanoparticles. Over the last few years, the mechanistic process modeling of pharmaceutical unit operations has made significant progress. Moreover, modeling and simulation are being slowly but surely adopted by the pharmaceutical industry. The objectives of modeling efforts are obvious: modeling and simulation of processes allow a rational design, optimization, scale-up, or transfer of a
process from one equipment to another. In terms of process modeling, especially computational fluid dynamics (CFD) and discrete element methods (DEM) have had an impact on the field, yielding an improved understanding of processes and products in an in vitro or in vivo environment. CFD allows the simulation of (multiphase) fluid flows, whereas DEM provides a detailed understanding of granular flows. One of the first articles describing the use of such methods in the field of pharmaceutical technology was the review article by Kremer and Hancock17 focusing on process simulation in the pharmaceutical industry. An article by Ketterhagen et al.18 first described the state of art in granular flow modeling via DEM. Because these times, significant progress has been made in this field, for example, in the CFD modeling of disintegration testers by Kindgen et al.19 and in the simulation of fluidized systems €hling et al. via the large-scale coupling of CFD and DEM by Bo published in this special issue. With this issue, we see the continued advancement of drug delivery and technologies as the life-blood of innovative pharmaceutical sciences. After all, the pharmaceutical industry is a drug product industry, not a drug industry. Dissolution, Transport, and Physiological Models Mass transport and dissolution behavior have been extensively explored over the 60 years of the Journal’s history. Shefter and Higuchi20 in their 1963 publication addressed the dissolution behavior of crystalline solids and Gibaldi and Feldman21 addressed the theoretical underpinnings of dissolution and sink conditions for nondisintegrating dosage forms. The importance of pH at the surface of dissolving drug as a critical factor influencing the dissolution of acidic and basic drugs was described in the work of Mooney, Stella, and others in the late 1970s.22 Simonelli, Mehta, and Higuchi addressed the impact of high-energy solid coprecipitates in their 1969 publication23 along with a related article focusing on crystal growth inhibition.24 Amidon, Higuchi, and Ho explored the impact of micelle solubilization on thermodynamic activity and its impact on mass transport through the aqueous diffusion layer adjacent to an absorptive surface.25 Integrating physiological considerations into drug transport, Doluisio et al.26 integrated partitioning and membrane transport and described an in situ rat gut technique to assess absorption rates. In subsequent years, the works of Rowland, Shah, and Lennernas addressed a variety of aspects related to the biological and physiological aspects of drug delivery including the human intestinal tract.27-29 Mathematical models have herein been used to delineate different physiologically relevant rate constants and disposition patterns. Data from these experimental systems are often used as input parameters and combined with modeling to understand rate-limiting factors in drug disposition. These models are quickly becoming an integral part of the applications of physiologically based pharmacokinetics (PBPK) modeling in the oral absorption-biopharmaceutics field. In this special issue, we continue to see the advancement of physiologically based transport models that expand our understanding of the important components affecting drug delivery. Mechanistic Pharmacokinetic-Pharmacodynamic Modeling The early history of quantitative pharmacokinetics is written in the works of Wagner, Nelson, Levy, Riegelman, Loo, Benet, Gerlowksi, their colleagues and others who explored the kinetics of blood concentrations; these articles go back to the earliest issues of the Journal.30-35 These advancements came about at a time when analytical methods were coming of age and providing a means of quantifying drug concentrations in biological fluids. Mechanistic pharmacokinetic models, including those using physiologically
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based parameters (i.e., PBPK) may be traced to the work of Teorell in 1937.36 However, the feasibility and utility of PBPK in describing and predicting the disposition of drugs was first shown through articles published in the Journal in the late 60s and early 1970s by Bischoff et al.37-39 Parameter sets allowing the application of PBPK concepts to “scale-up” and predict drug disposition in humans based on findings in preclinical animal models were compiled and presented within the Journal by Gerlowski and Jain in 1983.40 Clausen and Bickel added new insights into drug distribution in different tissues in their 1993 publication41 and Balaz et al.42 pursued the idea of incorporating exposure time into quantitative structure-activity relationships. Poulin and Thiel43 advanced a mechanism-based approach to estimating steady-state volume of distribution in their highly cited work and, more recently, Thiel et al.44 addressed the opportunities to effectively use PK-PD modeling to translate mechanistic understanding across species. These and other new methodologies, past deconvolution, to estimate fraction dissolved/absorbed in vivo have emerged with the increased use of PBPK modeling and have opened up new opportunities for the establishment of in vitroein vivo correlations. Advances in this field continue today and we see in this special issue, research related to the latest advances in the science of PK/PD modeling and PBPK modeling applied to both clinical and drug product quality questions.
our field. These include numerous articles dating back over the past 3 decades that advanced our knowledge of the mechanisms of physical stability and stabilization of proteins in lyophilized and spray-dried formulations, the role of excipients such as surfactants and other formulation variables for stabilizing biotherapeutics, the control of physical properties such as solution viscosity and its dependence on concentration of the biopharmaceutical drug, and the importance of protein-protein interactions and conformational stability in formulating biotherapeutics. Seminal examples include some of the most highly cited articles in the journal, such as those from Brange et al.47 on insulin stability, those focused on gene delivery such as Wiethoff and Middaugh,48 and more recently those focused on high-concentration protein formulations by Shire et al.49 The work of Lobo, Hanson, and Balthasar addressed antibody pharmacokinetics and pharmacodynamics in their 2004 publication.50 The 2009 publication by Weiss, Young, and Roberts addressed the principles, approaches, and challenges of predicting protein aggregation rates and shelf life,51 whereas the 2011 paper by Singh52 addressed product-related factors that impact immunogenicity of biotherapeutics. The recent work of Kumar et al.,53 Thirumangalathu et al.,54 Roberts et al.,55 and Strickley and Anderson56 advanced the science of protein physical and chemical stability. This is a growth area for the Journal and we see that reflected in the high quality of the articles for this special issue.
Regulatory Science
Transport and Binding Through Biological Membranes and Bilayers
The utility of modeling and simulation in drug development and regulatory review has been recently reviewed where efforts by the U.S. Food and Drug Administration's Office of Clinical Pharmacology in the development and application of regulatory science were described.45 To promote the application of modeling and simulation approaches in drug regulation, key issues and challenges were identified. The provisions in the recently enacted Prescription Drug User Fee Act VI include model-informed drug development.46 Continuing efforts to leverage modeling and simulation knowledgebase to inform clinical study design and optimize individual dosing regimens are ongoing. Recognizing the need for “fit for purpose” approaches, several articles are included in this issue describing recent applications of established pharmacokineticpharmacodynamic relationships with varying complexity in drug review, ranging from the evaluation of QT prolongation to PBPK and systems pharmacology as well as recent experiences in biosimilar product development that also demonstrate the continuing utility of modeling and simulation. Biopharmaceutical Delivery and Stability Biopharmaceuticals span a wide range of motifs, including therapeutic proteins, vaccines, gene therapies, and most recently cell therapies. They typically are used to treat chronic and/or lifethreatening diseases such as various forms of cancer and autoimmune diseases that are difficult or impractical to treat or cure with small-molecule drugs. Biopharmaceuticals are inherently labile, and this fact has been a long-standing challenge to their commercial development as medicines. There have been many advances in our mechanistic understanding and modeling of how biopharmaceuticals degrade, and these have provided insights and new methods to stabilize biopharmaceutical products. The Journal of Pharmaceutical Sciences is among the leading journals that first promoted publication of cutting-edge research focused on mechanistic approaches and predictive modeling of this class of medicines. The Journal added its Biotechnology section in 2007 but had been publishing leading research in this area long before that formal acknowledgment of the now established role of biotherapeutics in
Among the most highly cited research related to transport and binding through biological membranes and bilayers is the work of Meyer and Guttman57 in 1968 addressing protein binding. This was followed by others such as Loo and Riegelman in 196858 who addressed intrinsic absorption rate and Artursson59 in 1990 who explored the utility of Caco-2 cells as a model for studying passive absorption of drugs. Hansch and Dunn and Hansch and Claytonin their 1972 and 1973 articles, respectively, explored the relationship between lipophilic character and biological activity.60,61 In the 1990s, the work of individuals such as Mitragotri et al.,62 and Edwards and Langer63 undertook mechanistic studies of transdermal transport phenomena. More recently, the work of Lian and Ho addressed the trends and developments in liposome drug delivery systems,64 whereas Burton et al.65 in their 1996 article addressed how structural features influence biomembrane permeability of peptides. The 2016 paper of Olander et al.66 addressed the importance of considering transporter expression in Caco-2 cells to correctly interpret transport. The work of Badhan et al.67 addressed the development of a physiological model incorporating transporters for the prediction of intestinal drug absorption, and in their 2001 article, Zhao et al.68 provided additional insight into human intestinal absorption integrated in with quantitative structure-activity relationships, while Palm et al.69 explored the mechanistic basis of drug absorption using molecular surface properties. During the last decade, Loftsson et al. explored the impact of cyclodextrins on transport through biological membranes in their 2007 and 2012 publications,70,71 whereas the review by Rajewski and Stella72 described the mechanistic understanding of the application of cyclodextrins to deliver poorly soluble drugs. Tejwani et al.73 addressed the functional group dependence of solute partitioning within 1,2-dioleoyl-snglycero-3-phosphocholine bilayers using molecular dynamic simulations. The very recent work of Nitsche and Kasting74 addressed the correlation between permeability coefficients of phospholipidcholesterol bilayers and basic chemical properties of dissolving solutes. Research in this area continues today as demonstrated in this special issue.
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Mechanism-Based Predictions of Phase Miscibility, Solubility, Crystallization, Supersaturation Mechanism-based predictions of solubility, crystallization, supersaturation, and phase miscibility are well represented among the most highly cited publications of the Journal. The work of Kier, Murray, Hall, and colleagues in the mid 1970s, for example, provided several highly cited publications related to molecular connectivity, partitioning, density, and pharmacological activity.75-79 The classic work of Flynn, Amidon, Yalkowsky, Valvani and others brought to light the factors impacting solubility and partitioning in ever greater detail throughout the 1970s and early 80s.80-83 More recently, examples of the development and characterization of crystallization, supersaturation, and amorphous solid dispersions by Rodriguez-Hornedo, Alonzo, Konno, Brouwers, Gao, Guzman, Baird, Taylor and their colleagues has been advanced by these highly cited publications84-90 in the Journal and the applications of cyclodextrin solubilization as described by Stella, Loftsson, and others.70-72,91-93 The work of Xiang and Anderson94 used molecular dynamics simulations of amorphous indomethacinepolyvinyl pyrrolidone glasses to estimate drug solubility in polyvinyl pyrrolidone. The work of Baird et al.90 provided further insight through a classification system to assess crystallization tendency. In this issue, the continued advancement of the science of solubility, crystallization, and supersaturation continues, as it is critical to the development of challenging therapeutic agents. Mechanism-Based Models of Physical and Chemical Stabilities The Journal is replete with publications addressing the physical and chemical stabilities of drugs and drug products. The highly cited review of Haleblian and McCrone laid out the opportunities and challenges associated with polymorphs in their 1969 review95 and the work of Gu, Young, and Grant provided a mechanistic understanding of solvent effects on polymorph formation.96 The 1995 work of Yu97 provided additional insight into the thermodynamic stability of polymorphs from melting data. The work of Yamana and Tsuji98 on the comparative stability of cephalosporins in aqueous solutions is among the most cited early references in 1976 as is the 2004 article by Shire et al.49 on the development of high protein concentration formulations and the 2007 article by Wang et al.99 on antibody structure, instability, and formulation. The 1992 work of Fassberg and Stella on the kinetics and mechanism of hydrolysis of camptothecin and analogs,100 and the work of Zhou, Grant, and others provided mechanistic insights into the physical stability of amorphous pharmaceuticals and the importance of thermodynamics and molecular mobility.101 The review of Zhang, Hancock, Zografi and colleagues together captured the mechanistic understanding of the physical stability and chemical stability properties of amorphous systems in several highly cited publications.102-105 Conclusion In this brief glance through the history of the Journal of Pharmaceutical Sciences, it has been a major resource of innovative computational pharmaceutical sciences and mechanism-based modeling for nearly 6 decades. With this issue, we celebrate its history and communicate the future of pharmaceutical sciences. The Journal is proud of its history. The contributions of thousands of scientists from around the world have provided the knowledge needed to support the discovery, development, and manufacture of therapeutic agents well into the 21st century.
References 1. Higuchi T. Rate of release of medicaments from ointment bases containing drugs in suspension. J Pharm Sci. 1961;50(10):874-875. 2. Higuchi WI. Analysis of data on medicament release from ointments. J Pharm Sci. 1962;51(8):802-804. 3. Higuchi T. Mechanism of sustained-action medication - theoretical analysis of rate of release of solid drugs dispersed in solid matrices. J Pharm Sci. 1963;52(12):1145-1149. 4. Fell JT, Newton JM. Determination of tablet strength by diametralcompression test. J Pharm Sci. 1970;59(5):688-691. 5. Hiestand EN, Wells JE, Peot CB, Ochs JF. Physical processes of tableting. J Pharm Sci. 1977;66(4):510-519. 6. Lum SK, Duncan-Hewitt WC. Powder densification. 1. Particle-particle basis for incorporation of viscoelastic material properties. J Pharm Sci. 1999;88(2): 261-276. 7. Tye CK, Sun CC, Amidon GE. Evaluation of the effects of tableting speed on the relationships between compaction pressure, tablet tensile strength, and tablet solid fraction. J Pharm Sci. 2005;94(3):465-472. 8. Chiou WL, Riegelman S. Pharmaceutical applications of solid dispersion systems. J Pharm Sci. 1971;60(9):1281-1302. 9. Theeuwes F. Elementary osmotic pump. J Pharm Sci. 1975;64(12):1987-1991. 10. Henry S, McAllister DV, Allen MG, Prausnitz MR. Microfabricated microneedles: a novel approach to transdermal drug delivery. J Pharm Sci. 1998;87(8):922-925. 11. Batycky RP, Hanes J, Langer R, Edwards DA. A theoretical model of erosion and macromolecular drug release from biodegrading microspheres. J Pharm Sci. 1997;86(12):1464-1477. 12. Adams ML, Lavasanifar A, Kwon GS. Amphiphilic block copolymers for drug delivery. J Pharm Sci. 2003;92(7):1343-1355. 13. Bazile D, Prudhomme C, Bassoullet MT, Marlard M, Spenlehauer G, Veillard M. Stealth me.peg-pla nanoparticles avoid uptake by the mononuclear phagocytes system. J Pharm Sci. 1995;84(4):493-498. 14. Stella B, Arpicco S, Peracchia MT, et al. Design of folic acid-conjugated nanoparticles for drug targeting. J Pharm Sci. 2000;89(11):1452-1464. 15. Hilgenbrink AR, Low PS. Folate receptor-mediated drug targeting: from therapeutics to diagnostics. J Pharm Sci. 2005;94(10):2135-2146. 16. Hillyer JF, Albrecht RM. Gastrointestinal persorption and tissue distribution of differently sized colloidal gold nanoparticles. J Pharm Sci. 2001;90(12):19271936. 17. Kremer DM, Hancock BC. Process simulation in the pharmaceutical industry: a review of some basic physical models. J Pharm Sci. 2006;95(3):517-529. 18. Ketterhagen WR, am Ende MT, Hancock BC. Process modeling in the pharmaceutical industry using the discrete element method. J Pharm Sci. 2009;98(2):442-470. 19. Kindgen S, Wachtel H, Abrahamsson B, Langguth P. Computational fluid dynamics simulation of hydrodynamics and stresses in the PhEur/USP disintegration tester under fed and fasted fluid characteristics. J Pharm Sci. 2015;104(9):2956-2968. 20. Shefter E, Higuchi T. Dissolution behavior of crystalline solvated and nonsolvated forms of some pharmaceuticals. J Pharm Sci. 1963;52(8):781-791. 21. Gibaldi M, Feldman S. Establishment of sink conditions in dissolution rate determinationsetheoretical considerations and application to nondisintegrating dosage forms. J Pharm Sci. 1967;56(10):1238-1242. 22. Mooney KG, Mintun MA, Himmelstein KJ, Stella VJ. Dissolution kinetics of carboxylic-acids .1. Effect of ph under unbuffered conditions. J Pharm Sci. 1981;70(1):13-22. 23. Simonelli AP, Mehta SC, Higuchi WI. Dissolution rates of high energy polyvinylpyrrolidone (pvp)-sulfathiazole coprecipitates. J Pharm Sci. 1969;58(5): 538-549. 24. Simonelli AP, Mehta SC, Higuchi WI. Inhibition of sulfathiazole crystal growth by polyvinylpyrrolidone. J Pharm Sci. 1970;59(5):633. 25. Amidon GE, Higuchi WI, Ho NFH. Theoretical and experimental studies of transport of micelle-solubilized solutes. J Pharm Sci. 1982;71(1):77-84. 26. Doluisio JT, Billups NF, Dittert LW, Sugita ET, Swintosky JV. Drug absorption. I. An in situ rat gut technique yielding realistic absorption rates. J Pharm Sci. 1969;58(10):1196-1200. 27. Rowland M, Riegelman S. Determination of acetylsalicylic acid and salicylic acid in plasma. J Pharm Sci. 1967;56(6):717-720. 28. Shah VP, Midha KK, Dighe S, et al. Analytical methods validation - bioavailability, bioequivalence, and pharmacokinetic studies. J Pharm Sci. 1992;81(3): 309-312. 29. Lennernas H. Human intestinal permeability. J Pharm Sci. 1998;87(4):403-410. 30. Wagner JG, Nelson E. Per cent absorbed time plots derived from blood level and/or urinary excretion data. J Pharm Sci. 1963;52(6):610-611. 31. Wagner JG, Nelson E. Kinetic analysis of blood levels þ urinary excretion in absorptive phase after single doses of drug. J Pharm Sci. 1964;53(11):1392-1403. 32. Levy G. Pharmacokinetics of salicylate elimination in man. J Pharm Sci. 1965;54(7):959-967. 33. Riegelman S, Loo JCK, Rowland M. Shortcomings in pharmacokinetic analysis by conceiving body to exhibit properties of a single compartment. J Pharm Sci. 1968;57(1):117-123. 34. Loo JCK, Riegelman S. Assessment of pharmacokinetic constants from postinfusion blood curves obtained after IV infusion. J Pharm Sci. 1970;59(1):53-55.
G.E. Amidon et al. / Journal of Pharmaceutical Sciences xxx (2018) 1-6 35. Benet LZ, Galeazzi RL. Noncompartmental determination of the steady-state volume of distribution. J Pharm Sci. 1979;68(8):1071-1074. 36. Teorell T. Kinetics of distribution of substances administered to the body. Arch Int Pharmacodyn Ther. 1937;57:205-240. 37. Bischoff KB, Dedrick RL, Zaharko DS, Longstreth JA. Methotrexate pharmacokinetics. J Pharm Sci. 1971;60(8):1128-1133. 38. Bischoff KB, Dedrick RL. Thiopental pharmacokinetics. J Pharm Sci. 1968;57(8): 1346-1351. 39. Bischoff KB, Dedrick RL, Zaharko DS. Preliminary model for methotrexate pharmacokinetics. J Pharm Sci. 1970;59(2):149-154. 40. Gerlowski LE, Jain RK. Physiologically based pharmacokinetic modeling principles and applications. J Pharm Sci. 1983;72(10):1103-1127. 41. Clausen J, Bickel MH. Prediction of drug distribution in distribution dialysis and in vivo from binding to tissues and blood. J Pharm Sci. 1993;82(4):345349. Wiese M, Seydel JK. A time hierarchy-based model for kinetics of drug 42. Bal a z S, disposition and its use in quantitative structuredactivity relationships. J Pharm Sci. 1992;81(9):849-857. 43. Poulin P, Theil FP. Prediction of pharmacokinetics prior to in vivo studies. 1. Mechanism-based prediction of volume of distribution. J Pharm Sci. 2002;91(1):129-156. 44. Thiel C, Schneckener S, Krauss M, et al. A systematic evaluation of the use of physiologically based pharmacokinetic modeling for cross-species extrapolation. J Pharm Sci. 2015;104(1):191-206. 45. Huang S-M, Abernethy DR, Wang Y, Zhao P, Zineh I. The utility of modeling and simulation in drug development and regulatory review. J Pharm Sci. 2013;102(9):2912-2923. 46. U.S. Food and Drug Administration. PDUFA VI Commitment letter: pdufa reauthorization performance goals and procedures fiscal years 2018 through 2022. Silver Spring, MD: FDA; 2018. Available at: https://www.fda.gov/ downloads/ForIndustry/UserFees/PrescriptionDrugUserFee/UCM511438.pdf. Accessed November 26, 2018. 47. Brange J, Andersen L, Laursen ED, Meyn G, Rasmussen E. Toward understanding insulin fibrillation. J Pharm Sci. 1997;86(5):517-525. 48. Wiethoff CM, Middaugh CR. Barriers to nonviral gene delivery. J Pharm Sci. 2003;92(2):203-217. 49. Shire SJ, Shahrokh Z, Liu J. Challenges in the development of high protein concentration formulations. J Pharm Sci. 2004;93(6):1390-1402. 50. Lobo ED, Hansen RJ, Balthasar JP. Antibody pharmacokinetics and pharmacodynamics. J Pharm Sci. 2004;93(11):2645-2668. 51. Weiss WF, Young TM, Roberts CJ. Principles, approaches, and challenges for predicting protein aggregation rates and shelf life. J Pharm Sci. 2009;98(4): 1246-1277. 52. Singh SK. Impact of product-related factors on immunogenicity of biotherapeutics. J Pharm Sci. 2011;100(2):354-387. 53. Kumar S, Mitchell MA, Rup B, Singh SK. Relationship between potential aggregation-prone regions and HLA-DR-binding T-cell immune epitopes: implications for rational design of novel and follow-on therapeutic antibodies. J Pharm Sci. 2012;101(8):2686-2701. 54. Thirumangalathu R, Krishnan S, Brems DN, Randolph TW, Carpenter JF. Effects of pH, temperature, and sucrose on benzyl alcohol-induced aggregation of recombinant human granulocyte colony stimulating factor. J Pharm Sci. 2006;95(7):1480-1497. 55. Roberts CJ, Darrington RT, Whitley MB. Irreversible aggregation of recombinant bovine granulocyte-colony stimulating factor (bG-CSF) and implications for predicting protein shelf life. J Pharm Sci. 2003;92(5):1095-1111. 56. Strickley RG, Anderson BD. Solid-state stability of human insulin. II. Effect of water on reactive intermediate partitioning in lyophiles from pH 2-5 solutions: stabilization against covalent dimer formation. J Pharm Sci. 1997;86(6):645-653. 57. Meyer MC, Guttman DE. Binding of drugs by plasma proteins. J Pharm Sci. 1968;57(6):895-918. 58. Loo JCK, Riegelman S. New method for calculating intrinsic absorption rate of drugs. J Pharm Sci. 1968;57(6):918-928. 59. Artursson P. Epithelial transport of drugs in cell-culture .1. A model for studying the passive diffusion of drugs over intestinal absorptive (caco-2) cells. J Pharm Sci. 1990;79(6):476-482. 60. Hansch C, Dunn WJ. Linear relationships between lipophilic character and biological-activity of drugs. J Pharm Sci. 1972;61(1):1-19. 61. Hansch C, Clayton JM. Lipophilic character and biological-activity of drugs .2. Parabolic case. J Pharm Sci. 1973;62(1):1-21. 62. Mitragotri S, Edwards DA, Blankschtein D, Langer R. Mechanistic study of ultrasonically-enhanced transdermal drug-delivery. J Pharm Sci. 1995;84(6): 697-706. 63. Edwards DA, Langer R. A linear theory of transdermal transport phenomena. J Pharm Sci. 1994;83(9):1315-1334. 64. Lian T, Ho RJY. Trends and developments in liposome drug delivery systems. J Pharm Sci. 2001;90(6):667-680. 65. Burton PS, Conradi RA, Ho NFH, Hilgers AR, Borchardt RT. How structural features influence the biomembrane permeability of peptides. J Pharm Sci. 1996;85(12):1336-1340. 66. Olander M, Wisniewski JR, Matsson P, Lundquist P, Artursson P. The proteome of filter-grown caco-2 cells with a focus on proteins involved in drug disposition. J Pharm Sci. 2016;105(2):817-827.
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67. Badhan R, Penny J, Galetin A, Houston JB. Methodology for development of a physiological model incorporating CYP3A and P-glycoprotein for the prediction of intestinal drug absorption. J Pharm Sci. 2009;98(6):21802197. 68. Zhao YH, Le J, Abraham MH, et al. Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors. J Pharm Sci. 2001;90(6):749-784. 69. Palm K, Luthman K, Ungell AL, Strandlund G, Artursson P. Correlation of drug absorption with molecular surface properties. J Pharm Sci. 1996;85(1):32-39. 70. Loftsson T, Vogensen SB, Brewster ME, Konradsdottir F. Effects of cyclodextrins on drug delivery through biological membranes. J Pharm Sci. 2007;96(10):2532-2546. 71. Loftsson T, Brewster ME. Cyclodextrins as functional excipients: methods to enhance complexation efficiency. J Pharm Sci. 2012;101(9):3019-3032. 72. Rajewski RA, Stella VJ. Pharmaceutical applications of cyclodextrins .2. In vivo drug delivery. J Pharm Sci. 1996;85(11):1142-1169. 73. Tejwani RW, Davis ME, Anderson BD, Stouch TR. Functional group dependence of solute partitioning to various locations within a DOPC bilayer: a comparison of molecular dynamics simulations with experiment. J Pharm Sci. 2011;100(6):2136-2146. 74. Nitsche JM, Kasting GB. A universal correlation predicts permeability coefficients of fluid- and gel-phase phospholipid and phospholipid-cholesterol bilayers for arbitrary solutes. J Pharm Sci. 2016;105(5):1762-1771. 75. Kier LB, Roche EB. Medicinal chemistry of mesoionic compounds. J Pharm Sci. 1967;56(2):149-168. 76. Kier LB, Hall LH, Murray WJ, Randic M. Molecular connectivity .1. Relationship to nonspecific local anesthesia. J Pharm Sci. 1975;64(12):1971-1974. 77. Murray WJ, Hall LH, Kier LB. Molecular connectivity. 3. Relationship to partition-coefficients. J Pharm Sci. 1975;64(12):1978-1981. 78. Hall LH, Kier LB, Murray WJ. Molecular connectivity. 2. Relationship to water solubility and boiling-point. J Pharm Sci. 1975;64(12):1974-1977. 79. Kier LB, Murray WJ, Randic M, Hall LH. Molecular connectivity.5. Connectivity series concept applied to density. J Pharm Sci. 1976;65(8):1226-1230. 80. Flynn GL, Yalkowsky SH. Correlation and prediction of mass-transport across membranes .1. Influence of alkyl chain-length on flux-determining properties of barrier and diffusant. J Pharm Sci. 1972;61(6):838-852. 81. Amidon GL, Yalkowsky SH, Leung S. Solubility of nonelectrolytes in polarsolvents .2. Solubility of aliphatic-alcohols in water. J Pharm Sci. 1974;63(12):1858-1866. 82. Yalkowsky SH, Valvani SC. Solubility and partitioning .1. Solubility of nonelectrolytes in water. J Pharm Sci. 1980;69(8):912-922. 83. Yalkowsky SH, Valvani SC, Roseman TJ. Solubility and partitioning .6. Octanol solubility and octanol-water partition-coefficients. J Pharm Sci. 1983;72(8): 866-870. 84. Rodriguez-Hornedo N, Murphy D. Significance of controlling crystallization mechanisms and kinetics in pharmaceutical systems. J Pharm Sci. 1999;88(7): 651-660. 85. Alonzo DE, Gao Y, Zhou DL, Mo HP, Zhang GGZ, Taylor LS. Dissolution and precipitation behavior of amorphous solid dispersions. J Pharm Sci. 2011;100(8):3316-3331. 86. Konno H, Taylor LS. Influence of different polymers on the crystallization tendency of molecularly dispersed amorphous felodipine. J Pharm Sci. 2006;95(12):2692-2705. 87. Brouwers J, Brewster ME, Augustijns P. Supersaturating drug delivery systems: the answer to solubility-limited oral bioavailability? J Pharm Sci. 2009;98(8):2549-2572. 88. Gao P, Rush BD, Pfund WP, et al. Development of a supersaturable SEDDS (SSEDDS) formulation of paclitaxel with improved oral bioavailability. J Pharm Sci. 2003;92(12):2386-2398. 89. Guzman HR, Tawa M, Zhang Z, et al. Combined use of crystalline salt forms and precipitation inhibitors to improve oral absorption of celecoxib from solid oral formulations. J Pharm Sci. 2007;96(10):2686-2702. 90. Baird JA, Van Eerdenbrugh B, Taylor LS. A classification system to assess the crystallization tendency of organic molecules from undercooled melts. J Pharm Sci. 2010;99(9):3787-3806. 91. Loftsson T, Brewster ME. Pharmaceutical applications of cyclodextrins .1. Drug solubilization and stabilization. J Pharm Sci. 1996;85(10):1017-1025. 92. Loftsson T, Magnusdottir A, Masson M, Sigurjonsdottir JF. Self-association and cyclodextrin solubilization of drugs. J Pharm Sci. 2002;91(11):2307-2316. 93. Loftsson T, Masson M, Brewster ME. Self-association of cyclodextrins and cyclodextrin complexes. J Pharm Sci. 2004;93(5):1091-1099. 94. Xiang TX, Anderson BD. Molecular dynamics simulation of amorphous indomethacin-poly(vinylpyrrolidone) glasses: solubility and hydrogen bonding interactions. J Pharm Sci. 2013;102(3):876-891. 95. Haleblian J, McCrone W. Pharmaceutical applications of polymorphism. J Pharm Sci. 1969;58(8):911-929. 96. Gu CH, Young V, Grant DJW. Polymorph screening: influence of solvents on the rate of solvent-mediated polymorphic transformation. J Pharm Sci. 2001;90(11):1878-1890. 97. Yu L. Inferring thermodynamic stability relationship of polymorphs from melting data. J Pharm Sci. 1995;84(8):966-974.
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98. Yamana T, Tsuji A. Comparative stability of cephalosporins in aqueous-solution - kinetics and mechanisms of degradation. J Pharm Sci. 1976;65(11):1563-1574. 99. Wang W, Singh S, Zeng DL, King K, Nema S. Antibody structure, instability, and formulation. J Pharm Sci. 2007;96(1):1-26. 100. Fassberg J, Stella VJ. A kinetic and mechanistic study of the hydrolysis of camptothecin and some analogs. J Pharm Sci. 1992;81(7):676-684. 101. Zhou DL, Zhang GGZ, Law D, Grant DJW, Schmitt EA. Physical stability of amorphous pharmaceuticals: importance of configurational thermodynamic quantities and molecular mobility. J Pharm Sci. 2002;91(8):18631872.
102. Yoshioka M, Hancock BC, Zografi G. Crystallization of indomethacin from the amorphous state below and above its glass-transition temperature. J Pharm Sci. 1994;83(12):1700-1705. 103. Yoshioka M, Hancock BC, Zografi G. Inhibition of indomethacin crystallization in poly(vinylpyrrolidone) coprecipitates. J Pharm Sci. 1995;84(8):983-986. 104. Hancock BC, Zograf G. Characteristics and significance of the amorphous state in pharmaceutical systems. J Pharm Sci. 1997;86(1):1-12. 105. Zhang J, Zografi G. The relationship between “BET” and “free volume”-derived parameters for water vapor absorption into amorphous solids. J Pharm Sci. 2000;89(8):1063-1072.
Contents lists available at ScienceDirect
Journal of Pharmaceutical Sciences journal homepage: www.jpharmsci.org
General Commentary
Fifty-Eight Years and Counting: High-Impact Publishing in Computational Pharmaceutical Sciences and Mechanism-Based Modeling Gregory E. Amidon 1, *, Bradley D. Anderson 2, Joseph P. Balthasar 3, Christel A.S. Bergstrom 4, Shiew-Mei Huang 5, Gerald Kasting 6, Filippos Kesisoglou 7, Johannes G. Khinast 8, Donald E. Mager 3, Christopher J. Roberts 9, Lian Yu 10 1
University of Michigan, Ann Arbor, Michigan 48109 University of Kentucky, Lexington, Kentucky 40506 3 University at Buffalo, State University of New York, Buffalo, New York 14260 4 Uppsala University, Uppsala, Sweden 5 Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland 20993 6 University of Cincinnati, Cincinnati, Ohio 45220 7 Merck & Co., Inc., Kenilworth, New Jersey 07033 8 Institute for Process and Particle Engineering, Graz University of Technology, Graz, Austria 9 University of Delaware, Newark, Delaware 19716 10 University of Wisconsin, Madison, Wisconsin 53706 2
a r t i c l e i n f o
a b s t r a c t
Article history: Received 1 November 2018 Accepted 2 November 2018
With this issue of the Journal of Pharmaceutical Sciences, we celebrate the nearly 6 decades of contributions to mechanistic-based modeling and computational pharmaceutical sciences. Along with its predecessor, The Journal of the American Pharmaceutical Association: Scientific Edition first published in 1911, JPharmSci has been a leader in the advancement of pharmaceutical sciences beginning with its inaugural edition in 1961. As one of the first scientific journals focusing on pharmaceutical sciences, JPharmSci has established a reputation for publishing high-quality research articles using computational methods and mechanism-based modeling. The journal’s publication record is remarkable. With over 15,000 articles, 3000 notes, and more than 650 reviews from industry, academia, and regulatory agencies around the world, JPharmSci has truly been the leader in advancing pharmaceutical sciences. © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
Keywords: absorption, distribution, metabolism, and excretion (ADME) biophysical model(s) in silico modeling in vitro model(s) mathematical model(s) mechanistic modeling molecular modeling pharmacokinetic/pharmacodynamic (PKPD) modeling physiologically based pharmacokinetic (PBPK) modeling
Introduction In this issue, we bring together the latest research in mechanismbased modeling and computational pharmaceutical sciences in a variety of areas where the Journal has excelled. Topics covered in this special issue include the following: Multiphase modeling applications in drug delivery and pharmaceutical technology. * Correspondence to: Gregory E. Amidon (Telephone: þ1-734-936-7438). E-mail address: [email protected] (G.E. Amidon).
Dissolution and transport considerations often combined with physiological models that enable better predictions of oral bioavailability, tumor, lymphatic, and brain delivery predictions. Mechanistic pharmacokinetic-pharmacodynamic (PKPD) modeling at the cellular, organ, and system levels leading to a better understanding of biological processes underlying drug delivery, efficacy, and safety with application in clinical studies. Mechanistic approaches and predictive modeling of biopharmaceutical stability and delivery.
https://doi.org/10.1016/j.xphs.2018.11.002 0022-3549/© 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
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Fundamental models to predict transport and binding phenomena through bilayers and biomembranes such as the skin, intestine, cornea, and blood-brain barrier. Models and mechanism-based predictions of phase miscibility, solubility, crystallization, or maintenance of supersaturation obtained by release from or dissolution of metastable delivery systems. Mechanism-based models to account for chemical and physical stability of therapeutic agents. The following sections capture a few of the most highly cited and high-impact articles published in the Journal of Pharmaceutical Sciences over the past 6 decades that have advanced our understanding of pharmaceutical science through mechanistic modeling and computational tools. Drug Delivery and Pharmaceutical Technology Among the earliest issues of the Journal are several landmark publications focusing on drug delivery and technology. The work of Takeru Higuchi1 and William Higuchi2 set the tone for quantitative mathematical modeling of dissolution from drug delivery systems with their landmark publications addressing the rate of release of drug suspended in ointment bases in the early 1960s. The 1963 publication by Takeru Higuchi3 on modeling of the mechanism of drug release of solid drug particles dispersed in solid matrices is the most cited publication from the Journal with nearly 3000 citations, and it continues to be highly referenced today. In the pharmaceutical technology area, Fell and Newton4 published a highly cited reference in 1970 quantitating tablet tensile strength as a critical quality attribute of tablet dosage forms while Hiestand et al.5 in the late 1960s and early 70s provided mechanistic insights into the mechanical properties of pharmaceutical solids along with novel experimental methods. More recently, the work of Lum and Duncan-Hewitt in 1999 addressed the mechanistic basis of particleparticle interactions and emphasized the importance of viscoelastic material properties,6 while the work of Tye, Sun, and Amidon advanced the science of tablet compaction with their 2005 publication demonstrating the process-independent relationship between tensile strength and tablet solid fraction.7 In advancing drug delivery technologies, Chiou and Riegelman reviewed the pharmaceutical applications of solid dispersion delivery systems8 and in 1975, Theeuwes9 described the novel technology of the osmotic pump for drug delivery. In the following decades, highly cited references include work by Henry and colleagues10 describing microfabricated microneedles as a novel approach to transdermal delivery. The work of Batycky and others developed a mechanistic model of erosion and macromolecular drug release from biodegradable microspheres11 and more recently, the review by Adams et al.12 captured the state of the science related to the use of amphiphilic block copolymers and the opportunity to tailor drug delivery through a mechanistic understanding of polymer properties. The advancement of nanoparticulate drug delivery systems came of age in the last part of the last century with publications by Bazile et al., Stella et al., Hilgenbrink and Low, and Hillyer and Albrecht.13-16 In their work, they addressed the mechanism of nanoparticle transport across the intestinal tract, the design of targeted nanoparticles, and stealth nanoparticles. Over the last few years, the mechanistic process modeling of pharmaceutical unit operations has made significant progress. Moreover, modeling and simulation are being slowly but surely adopted by the pharmaceutical industry. The objectives of modeling efforts are obvious: modeling and simulation of processes allow a rational design, optimization, scale-up, or transfer of a
process from one equipment to another. In terms of process modeling, especially computational fluid dynamics (CFD) and discrete element methods (DEM) have had an impact on the field, yielding an improved understanding of processes and products in an in vitro or in vivo environment. CFD allows the simulation of (multiphase) fluid flows, whereas DEM provides a detailed understanding of granular flows. One of the first articles describing the use of such methods in the field of pharmaceutical technology was the review article by Kremer and Hancock17 focusing on process simulation in the pharmaceutical industry. An article by Ketterhagen et al.18 first described the state of art in granular flow modeling via DEM. Because these times, significant progress has been made in this field, for example, in the CFD modeling of disintegration testers by Kindgen et al.19 and in the simulation of fluidized systems €hling et al. via the large-scale coupling of CFD and DEM by Bo published in this special issue. With this issue, we see the continued advancement of drug delivery and technologies as the life-blood of innovative pharmaceutical sciences. After all, the pharmaceutical industry is a drug product industry, not a drug industry. Dissolution, Transport, and Physiological Models Mass transport and dissolution behavior have been extensively explored over the 60 years of the Journal’s history. Shefter and Higuchi20 in their 1963 publication addressed the dissolution behavior of crystalline solids and Gibaldi and Feldman21 addressed the theoretical underpinnings of dissolution and sink conditions for nondisintegrating dosage forms. The importance of pH at the surface of dissolving drug as a critical factor influencing the dissolution of acidic and basic drugs was described in the work of Mooney, Stella, and others in the late 1970s.22 Simonelli, Mehta, and Higuchi addressed the impact of high-energy solid coprecipitates in their 1969 publication23 along with a related article focusing on crystal growth inhibition.24 Amidon, Higuchi, and Ho explored the impact of micelle solubilization on thermodynamic activity and its impact on mass transport through the aqueous diffusion layer adjacent to an absorptive surface.25 Integrating physiological considerations into drug transport, Doluisio et al.26 integrated partitioning and membrane transport and described an in situ rat gut technique to assess absorption rates. In subsequent years, the works of Rowland, Shah, and Lennernas addressed a variety of aspects related to the biological and physiological aspects of drug delivery including the human intestinal tract.27-29 Mathematical models have herein been used to delineate different physiologically relevant rate constants and disposition patterns. Data from these experimental systems are often used as input parameters and combined with modeling to understand rate-limiting factors in drug disposition. These models are quickly becoming an integral part of the applications of physiologically based pharmacokinetics (PBPK) modeling in the oral absorption-biopharmaceutics field. In this special issue, we continue to see the advancement of physiologically based transport models that expand our understanding of the important components affecting drug delivery. Mechanistic Pharmacokinetic-Pharmacodynamic Modeling The early history of quantitative pharmacokinetics is written in the works of Wagner, Nelson, Levy, Riegelman, Loo, Benet, Gerlowksi, their colleagues and others who explored the kinetics of blood concentrations; these articles go back to the earliest issues of the Journal.30-35 These advancements came about at a time when analytical methods were coming of age and providing a means of quantifying drug concentrations in biological fluids. Mechanistic pharmacokinetic models, including those using physiologically
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based parameters (i.e., PBPK) may be traced to the work of Teorell in 1937.36 However, the feasibility and utility of PBPK in describing and predicting the disposition of drugs was first shown through articles published in the Journal in the late 60s and early 1970s by Bischoff et al.37-39 Parameter sets allowing the application of PBPK concepts to “scale-up” and predict drug disposition in humans based on findings in preclinical animal models were compiled and presented within the Journal by Gerlowski and Jain in 1983.40 Clausen and Bickel added new insights into drug distribution in different tissues in their 1993 publication41 and Balaz et al.42 pursued the idea of incorporating exposure time into quantitative structure-activity relationships. Poulin and Thiel43 advanced a mechanism-based approach to estimating steady-state volume of distribution in their highly cited work and, more recently, Thiel et al.44 addressed the opportunities to effectively use PK-PD modeling to translate mechanistic understanding across species. These and other new methodologies, past deconvolution, to estimate fraction dissolved/absorbed in vivo have emerged with the increased use of PBPK modeling and have opened up new opportunities for the establishment of in vitroein vivo correlations. Advances in this field continue today and we see in this special issue, research related to the latest advances in the science of PK/PD modeling and PBPK modeling applied to both clinical and drug product quality questions.
our field. These include numerous articles dating back over the past 3 decades that advanced our knowledge of the mechanisms of physical stability and stabilization of proteins in lyophilized and spray-dried formulations, the role of excipients such as surfactants and other formulation variables for stabilizing biotherapeutics, the control of physical properties such as solution viscosity and its dependence on concentration of the biopharmaceutical drug, and the importance of protein-protein interactions and conformational stability in formulating biotherapeutics. Seminal examples include some of the most highly cited articles in the journal, such as those from Brange et al.47 on insulin stability, those focused on gene delivery such as Wiethoff and Middaugh,48 and more recently those focused on high-concentration protein formulations by Shire et al.49 The work of Lobo, Hanson, and Balthasar addressed antibody pharmacokinetics and pharmacodynamics in their 2004 publication.50 The 2009 publication by Weiss, Young, and Roberts addressed the principles, approaches, and challenges of predicting protein aggregation rates and shelf life,51 whereas the 2011 paper by Singh52 addressed product-related factors that impact immunogenicity of biotherapeutics. The recent work of Kumar et al.,53 Thirumangalathu et al.,54 Roberts et al.,55 and Strickley and Anderson56 advanced the science of protein physical and chemical stability. This is a growth area for the Journal and we see that reflected in the high quality of the articles for this special issue.
Regulatory Science
Transport and Binding Through Biological Membranes and Bilayers
The utility of modeling and simulation in drug development and regulatory review has been recently reviewed where efforts by the U.S. Food and Drug Administration's Office of Clinical Pharmacology in the development and application of regulatory science were described.45 To promote the application of modeling and simulation approaches in drug regulation, key issues and challenges were identified. The provisions in the recently enacted Prescription Drug User Fee Act VI include model-informed drug development.46 Continuing efforts to leverage modeling and simulation knowledgebase to inform clinical study design and optimize individual dosing regimens are ongoing. Recognizing the need for “fit for purpose” approaches, several articles are included in this issue describing recent applications of established pharmacokineticpharmacodynamic relationships with varying complexity in drug review, ranging from the evaluation of QT prolongation to PBPK and systems pharmacology as well as recent experiences in biosimilar product development that also demonstrate the continuing utility of modeling and simulation. Biopharmaceutical Delivery and Stability Biopharmaceuticals span a wide range of motifs, including therapeutic proteins, vaccines, gene therapies, and most recently cell therapies. They typically are used to treat chronic and/or lifethreatening diseases such as various forms of cancer and autoimmune diseases that are difficult or impractical to treat or cure with small-molecule drugs. Biopharmaceuticals are inherently labile, and this fact has been a long-standing challenge to their commercial development as medicines. There have been many advances in our mechanistic understanding and modeling of how biopharmaceuticals degrade, and these have provided insights and new methods to stabilize biopharmaceutical products. The Journal of Pharmaceutical Sciences is among the leading journals that first promoted publication of cutting-edge research focused on mechanistic approaches and predictive modeling of this class of medicines. The Journal added its Biotechnology section in 2007 but had been publishing leading research in this area long before that formal acknowledgment of the now established role of biotherapeutics in
Among the most highly cited research related to transport and binding through biological membranes and bilayers is the work of Meyer and Guttman57 in 1968 addressing protein binding. This was followed by others such as Loo and Riegelman in 196858 who addressed intrinsic absorption rate and Artursson59 in 1990 who explored the utility of Caco-2 cells as a model for studying passive absorption of drugs. Hansch and Dunn and Hansch and Claytonin their 1972 and 1973 articles, respectively, explored the relationship between lipophilic character and biological activity.60,61 In the 1990s, the work of individuals such as Mitragotri et al.,62 and Edwards and Langer63 undertook mechanistic studies of transdermal transport phenomena. More recently, the work of Lian and Ho addressed the trends and developments in liposome drug delivery systems,64 whereas Burton et al.65 in their 1996 article addressed how structural features influence biomembrane permeability of peptides. The 2016 paper of Olander et al.66 addressed the importance of considering transporter expression in Caco-2 cells to correctly interpret transport. The work of Badhan et al.67 addressed the development of a physiological model incorporating transporters for the prediction of intestinal drug absorption, and in their 2001 article, Zhao et al.68 provided additional insight into human intestinal absorption integrated in with quantitative structure-activity relationships, while Palm et al.69 explored the mechanistic basis of drug absorption using molecular surface properties. During the last decade, Loftsson et al. explored the impact of cyclodextrins on transport through biological membranes in their 2007 and 2012 publications,70,71 whereas the review by Rajewski and Stella72 described the mechanistic understanding of the application of cyclodextrins to deliver poorly soluble drugs. Tejwani et al.73 addressed the functional group dependence of solute partitioning within 1,2-dioleoyl-snglycero-3-phosphocholine bilayers using molecular dynamic simulations. The very recent work of Nitsche and Kasting74 addressed the correlation between permeability coefficients of phospholipidcholesterol bilayers and basic chemical properties of dissolving solutes. Research in this area continues today as demonstrated in this special issue.
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Mechanism-Based Predictions of Phase Miscibility, Solubility, Crystallization, Supersaturation Mechanism-based predictions of solubility, crystallization, supersaturation, and phase miscibility are well represented among the most highly cited publications of the Journal. The work of Kier, Murray, Hall, and colleagues in the mid 1970s, for example, provided several highly cited publications related to molecular connectivity, partitioning, density, and pharmacological activity.75-79 The classic work of Flynn, Amidon, Yalkowsky, Valvani and others brought to light the factors impacting solubility and partitioning in ever greater detail throughout the 1970s and early 80s.80-83 More recently, examples of the development and characterization of crystallization, supersaturation, and amorphous solid dispersions by Rodriguez-Hornedo, Alonzo, Konno, Brouwers, Gao, Guzman, Baird, Taylor and their colleagues has been advanced by these highly cited publications84-90 in the Journal and the applications of cyclodextrin solubilization as described by Stella, Loftsson, and others.70-72,91-93 The work of Xiang and Anderson94 used molecular dynamics simulations of amorphous indomethacinepolyvinyl pyrrolidone glasses to estimate drug solubility in polyvinyl pyrrolidone. The work of Baird et al.90 provided further insight through a classification system to assess crystallization tendency. In this issue, the continued advancement of the science of solubility, crystallization, and supersaturation continues, as it is critical to the development of challenging therapeutic agents. Mechanism-Based Models of Physical and Chemical Stabilities The Journal is replete with publications addressing the physical and chemical stabilities of drugs and drug products. The highly cited review of Haleblian and McCrone laid out the opportunities and challenges associated with polymorphs in their 1969 review95 and the work of Gu, Young, and Grant provided a mechanistic understanding of solvent effects on polymorph formation.96 The 1995 work of Yu97 provided additional insight into the thermodynamic stability of polymorphs from melting data. The work of Yamana and Tsuji98 on the comparative stability of cephalosporins in aqueous solutions is among the most cited early references in 1976 as is the 2004 article by Shire et al.49 on the development of high protein concentration formulations and the 2007 article by Wang et al.99 on antibody structure, instability, and formulation. The 1992 work of Fassberg and Stella on the kinetics and mechanism of hydrolysis of camptothecin and analogs,100 and the work of Zhou, Grant, and others provided mechanistic insights into the physical stability of amorphous pharmaceuticals and the importance of thermodynamics and molecular mobility.101 The review of Zhang, Hancock, Zografi and colleagues together captured the mechanistic understanding of the physical stability and chemical stability properties of amorphous systems in several highly cited publications.102-105 Conclusion In this brief glance through the history of the Journal of Pharmaceutical Sciences, it has been a major resource of innovative computational pharmaceutical sciences and mechanism-based modeling for nearly 6 decades. With this issue, we celebrate its history and communicate the future of pharmaceutical sciences. The Journal is proud of its history. The contributions of thousands of scientists from around the world have provided the knowledge needed to support the discovery, development, and manufacture of therapeutic agents well into the 21st century.
References 1. Higuchi T. Rate of release of medicaments from ointment bases containing drugs in suspension. J Pharm Sci. 1961;50(10):874-875. 2. Higuchi WI. Analysis of data on medicament release from ointments. J Pharm Sci. 1962;51(8):802-804. 3. Higuchi T. Mechanism of sustained-action medication - theoretical analysis of rate of release of solid drugs dispersed in solid matrices. J Pharm Sci. 1963;52(12):1145-1149. 4. Fell JT, Newton JM. Determination of tablet strength by diametralcompression test. J Pharm Sci. 1970;59(5):688-691. 5. Hiestand EN, Wells JE, Peot CB, Ochs JF. Physical processes of tableting. J Pharm Sci. 1977;66(4):510-519. 6. Lum SK, Duncan-Hewitt WC. Powder densification. 1. Particle-particle basis for incorporation of viscoelastic material properties. J Pharm Sci. 1999;88(2): 261-276. 7. Tye CK, Sun CC, Amidon GE. Evaluation of the effects of tableting speed on the relationships between compaction pressure, tablet tensile strength, and tablet solid fraction. J Pharm Sci. 2005;94(3):465-472. 8. Chiou WL, Riegelman S. Pharmaceutical applications of solid dispersion systems. J Pharm Sci. 1971;60(9):1281-1302. 9. Theeuwes F. Elementary osmotic pump. J Pharm Sci. 1975;64(12):1987-1991. 10. Henry S, McAllister DV, Allen MG, Prausnitz MR. Microfabricated microneedles: a novel approach to transdermal drug delivery. J Pharm Sci. 1998;87(8):922-925. 11. Batycky RP, Hanes J, Langer R, Edwards DA. A theoretical model of erosion and macromolecular drug release from biodegrading microspheres. J Pharm Sci. 1997;86(12):1464-1477. 12. Adams ML, Lavasanifar A, Kwon GS. Amphiphilic block copolymers for drug delivery. J Pharm Sci. 2003;92(7):1343-1355. 13. Bazile D, Prudhomme C, Bassoullet MT, Marlard M, Spenlehauer G, Veillard M. Stealth me.peg-pla nanoparticles avoid uptake by the mononuclear phagocytes system. J Pharm Sci. 1995;84(4):493-498. 14. Stella B, Arpicco S, Peracchia MT, et al. Design of folic acid-conjugated nanoparticles for drug targeting. J Pharm Sci. 2000;89(11):1452-1464. 15. Hilgenbrink AR, Low PS. Folate receptor-mediated drug targeting: from therapeutics to diagnostics. J Pharm Sci. 2005;94(10):2135-2146. 16. Hillyer JF, Albrecht RM. Gastrointestinal persorption and tissue distribution of differently sized colloidal gold nanoparticles. J Pharm Sci. 2001;90(12):19271936. 17. Kremer DM, Hancock BC. Process simulation in the pharmaceutical industry: a review of some basic physical models. J Pharm Sci. 2006;95(3):517-529. 18. Ketterhagen WR, am Ende MT, Hancock BC. Process modeling in the pharmaceutical industry using the discrete element method. J Pharm Sci. 2009;98(2):442-470. 19. Kindgen S, Wachtel H, Abrahamsson B, Langguth P. Computational fluid dynamics simulation of hydrodynamics and stresses in the PhEur/USP disintegration tester under fed and fasted fluid characteristics. J Pharm Sci. 2015;104(9):2956-2968. 20. Shefter E, Higuchi T. Dissolution behavior of crystalline solvated and nonsolvated forms of some pharmaceuticals. J Pharm Sci. 1963;52(8):781-791. 21. Gibaldi M, Feldman S. Establishment of sink conditions in dissolution rate determinationsetheoretical considerations and application to nondisintegrating dosage forms. J Pharm Sci. 1967;56(10):1238-1242. 22. Mooney KG, Mintun MA, Himmelstein KJ, Stella VJ. Dissolution kinetics of carboxylic-acids .1. Effect of ph under unbuffered conditions. J Pharm Sci. 1981;70(1):13-22. 23. Simonelli AP, Mehta SC, Higuchi WI. Dissolution rates of high energy polyvinylpyrrolidone (pvp)-sulfathiazole coprecipitates. J Pharm Sci. 1969;58(5): 538-549. 24. Simonelli AP, Mehta SC, Higuchi WI. Inhibition of sulfathiazole crystal growth by polyvinylpyrrolidone. J Pharm Sci. 1970;59(5):633. 25. Amidon GE, Higuchi WI, Ho NFH. Theoretical and experimental studies of transport of micelle-solubilized solutes. J Pharm Sci. 1982;71(1):77-84. 26. Doluisio JT, Billups NF, Dittert LW, Sugita ET, Swintosky JV. Drug absorption. I. An in situ rat gut technique yielding realistic absorption rates. J Pharm Sci. 1969;58(10):1196-1200. 27. Rowland M, Riegelman S. Determination of acetylsalicylic acid and salicylic acid in plasma. J Pharm Sci. 1967;56(6):717-720. 28. Shah VP, Midha KK, Dighe S, et al. Analytical methods validation - bioavailability, bioequivalence, and pharmacokinetic studies. J Pharm Sci. 1992;81(3): 309-312. 29. Lennernas H. Human intestinal permeability. J Pharm Sci. 1998;87(4):403-410. 30. Wagner JG, Nelson E. Per cent absorbed time plots derived from blood level and/or urinary excretion data. J Pharm Sci. 1963;52(6):610-611. 31. Wagner JG, Nelson E. Kinetic analysis of blood levels þ urinary excretion in absorptive phase after single doses of drug. J Pharm Sci. 1964;53(11):1392-1403. 32. Levy G. Pharmacokinetics of salicylate elimination in man. J Pharm Sci. 1965;54(7):959-967. 33. Riegelman S, Loo JCK, Rowland M. Shortcomings in pharmacokinetic analysis by conceiving body to exhibit properties of a single compartment. J Pharm Sci. 1968;57(1):117-123. 34. Loo JCK, Riegelman S. Assessment of pharmacokinetic constants from postinfusion blood curves obtained after IV infusion. J Pharm Sci. 1970;59(1):53-55.
G.E. Amidon et al. / Journal of Pharmaceutical Sciences xxx (2018) 1-6 35. Benet LZ, Galeazzi RL. Noncompartmental determination of the steady-state volume of distribution. J Pharm Sci. 1979;68(8):1071-1074. 36. Teorell T. Kinetics of distribution of substances administered to the body. Arch Int Pharmacodyn Ther. 1937;57:205-240. 37. Bischoff KB, Dedrick RL, Zaharko DS, Longstreth JA. Methotrexate pharmacokinetics. J Pharm Sci. 1971;60(8):1128-1133. 38. Bischoff KB, Dedrick RL. Thiopental pharmacokinetics. J Pharm Sci. 1968;57(8): 1346-1351. 39. Bischoff KB, Dedrick RL, Zaharko DS. Preliminary model for methotrexate pharmacokinetics. J Pharm Sci. 1970;59(2):149-154. 40. Gerlowski LE, Jain RK. Physiologically based pharmacokinetic modeling principles and applications. J Pharm Sci. 1983;72(10):1103-1127. 41. Clausen J, Bickel MH. Prediction of drug distribution in distribution dialysis and in vivo from binding to tissues and blood. J Pharm Sci. 1993;82(4):345349. Wiese M, Seydel JK. A time hierarchy-based model for kinetics of drug 42. Bal a z S, disposition and its use in quantitative structuredactivity relationships. J Pharm Sci. 1992;81(9):849-857. 43. Poulin P, Theil FP. Prediction of pharmacokinetics prior to in vivo studies. 1. Mechanism-based prediction of volume of distribution. J Pharm Sci. 2002;91(1):129-156. 44. Thiel C, Schneckener S, Krauss M, et al. A systematic evaluation of the use of physiologically based pharmacokinetic modeling for cross-species extrapolation. J Pharm Sci. 2015;104(1):191-206. 45. Huang S-M, Abernethy DR, Wang Y, Zhao P, Zineh I. The utility of modeling and simulation in drug development and regulatory review. J Pharm Sci. 2013;102(9):2912-2923. 46. U.S. Food and Drug Administration. PDUFA VI Commitment letter: pdufa reauthorization performance goals and procedures fiscal years 2018 through 2022. Silver Spring, MD: FDA; 2018. Available at: https://www.fda.gov/ downloads/ForIndustry/UserFees/PrescriptionDrugUserFee/UCM511438.pdf. Accessed November 26, 2018. 47. Brange J, Andersen L, Laursen ED, Meyn G, Rasmussen E. Toward understanding insulin fibrillation. J Pharm Sci. 1997;86(5):517-525. 48. Wiethoff CM, Middaugh CR. Barriers to nonviral gene delivery. J Pharm Sci. 2003;92(2):203-217. 49. Shire SJ, Shahrokh Z, Liu J. Challenges in the development of high protein concentration formulations. J Pharm Sci. 2004;93(6):1390-1402. 50. Lobo ED, Hansen RJ, Balthasar JP. Antibody pharmacokinetics and pharmacodynamics. J Pharm Sci. 2004;93(11):2645-2668. 51. Weiss WF, Young TM, Roberts CJ. Principles, approaches, and challenges for predicting protein aggregation rates and shelf life. J Pharm Sci. 2009;98(4): 1246-1277. 52. Singh SK. Impact of product-related factors on immunogenicity of biotherapeutics. J Pharm Sci. 2011;100(2):354-387. 53. Kumar S, Mitchell MA, Rup B, Singh SK. Relationship between potential aggregation-prone regions and HLA-DR-binding T-cell immune epitopes: implications for rational design of novel and follow-on therapeutic antibodies. J Pharm Sci. 2012;101(8):2686-2701. 54. Thirumangalathu R, Krishnan S, Brems DN, Randolph TW, Carpenter JF. Effects of pH, temperature, and sucrose on benzyl alcohol-induced aggregation of recombinant human granulocyte colony stimulating factor. J Pharm Sci. 2006;95(7):1480-1497. 55. Roberts CJ, Darrington RT, Whitley MB. Irreversible aggregation of recombinant bovine granulocyte-colony stimulating factor (bG-CSF) and implications for predicting protein shelf life. J Pharm Sci. 2003;92(5):1095-1111. 56. Strickley RG, Anderson BD. Solid-state stability of human insulin. II. Effect of water on reactive intermediate partitioning in lyophiles from pH 2-5 solutions: stabilization against covalent dimer formation. J Pharm Sci. 1997;86(6):645-653. 57. Meyer MC, Guttman DE. Binding of drugs by plasma proteins. J Pharm Sci. 1968;57(6):895-918. 58. Loo JCK, Riegelman S. New method for calculating intrinsic absorption rate of drugs. J Pharm Sci. 1968;57(6):918-928. 59. Artursson P. Epithelial transport of drugs in cell-culture .1. A model for studying the passive diffusion of drugs over intestinal absorptive (caco-2) cells. J Pharm Sci. 1990;79(6):476-482. 60. Hansch C, Dunn WJ. Linear relationships between lipophilic character and biological-activity of drugs. J Pharm Sci. 1972;61(1):1-19. 61. Hansch C, Clayton JM. Lipophilic character and biological-activity of drugs .2. Parabolic case. J Pharm Sci. 1973;62(1):1-21. 62. Mitragotri S, Edwards DA, Blankschtein D, Langer R. Mechanistic study of ultrasonically-enhanced transdermal drug-delivery. J Pharm Sci. 1995;84(6): 697-706. 63. Edwards DA, Langer R. A linear theory of transdermal transport phenomena. J Pharm Sci. 1994;83(9):1315-1334. 64. Lian T, Ho RJY. Trends and developments in liposome drug delivery systems. J Pharm Sci. 2001;90(6):667-680. 65. Burton PS, Conradi RA, Ho NFH, Hilgers AR, Borchardt RT. How structural features influence the biomembrane permeability of peptides. J Pharm Sci. 1996;85(12):1336-1340. 66. Olander M, Wisniewski JR, Matsson P, Lundquist P, Artursson P. The proteome of filter-grown caco-2 cells with a focus on proteins involved in drug disposition. J Pharm Sci. 2016;105(2):817-827.
5
67. Badhan R, Penny J, Galetin A, Houston JB. Methodology for development of a physiological model incorporating CYP3A and P-glycoprotein for the prediction of intestinal drug absorption. J Pharm Sci. 2009;98(6):21802197. 68. Zhao YH, Le J, Abraham MH, et al. Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors. J Pharm Sci. 2001;90(6):749-784. 69. Palm K, Luthman K, Ungell AL, Strandlund G, Artursson P. Correlation of drug absorption with molecular surface properties. J Pharm Sci. 1996;85(1):32-39. 70. Loftsson T, Vogensen SB, Brewster ME, Konradsdottir F. Effects of cyclodextrins on drug delivery through biological membranes. J Pharm Sci. 2007;96(10):2532-2546. 71. Loftsson T, Brewster ME. Cyclodextrins as functional excipients: methods to enhance complexation efficiency. J Pharm Sci. 2012;101(9):3019-3032. 72. Rajewski RA, Stella VJ. Pharmaceutical applications of cyclodextrins .2. In vivo drug delivery. J Pharm Sci. 1996;85(11):1142-1169. 73. Tejwani RW, Davis ME, Anderson BD, Stouch TR. Functional group dependence of solute partitioning to various locations within a DOPC bilayer: a comparison of molecular dynamics simulations with experiment. J Pharm Sci. 2011;100(6):2136-2146. 74. Nitsche JM, Kasting GB. A universal correlation predicts permeability coefficients of fluid- and gel-phase phospholipid and phospholipid-cholesterol bilayers for arbitrary solutes. J Pharm Sci. 2016;105(5):1762-1771. 75. Kier LB, Roche EB. Medicinal chemistry of mesoionic compounds. J Pharm Sci. 1967;56(2):149-168. 76. Kier LB, Hall LH, Murray WJ, Randic M. Molecular connectivity .1. Relationship to nonspecific local anesthesia. J Pharm Sci. 1975;64(12):1971-1974. 77. Murray WJ, Hall LH, Kier LB. Molecular connectivity. 3. Relationship to partition-coefficients. J Pharm Sci. 1975;64(12):1978-1981. 78. Hall LH, Kier LB, Murray WJ. Molecular connectivity. 2. Relationship to water solubility and boiling-point. J Pharm Sci. 1975;64(12):1974-1977. 79. Kier LB, Murray WJ, Randic M, Hall LH. Molecular connectivity.5. Connectivity series concept applied to density. J Pharm Sci. 1976;65(8):1226-1230. 80. Flynn GL, Yalkowsky SH. Correlation and prediction of mass-transport across membranes .1. Influence of alkyl chain-length on flux-determining properties of barrier and diffusant. J Pharm Sci. 1972;61(6):838-852. 81. Amidon GL, Yalkowsky SH, Leung S. Solubility of nonelectrolytes in polarsolvents .2. Solubility of aliphatic-alcohols in water. J Pharm Sci. 1974;63(12):1858-1866. 82. Yalkowsky SH, Valvani SC. Solubility and partitioning .1. Solubility of nonelectrolytes in water. J Pharm Sci. 1980;69(8):912-922. 83. Yalkowsky SH, Valvani SC, Roseman TJ. Solubility and partitioning .6. Octanol solubility and octanol-water partition-coefficients. J Pharm Sci. 1983;72(8): 866-870. 84. Rodriguez-Hornedo N, Murphy D. Significance of controlling crystallization mechanisms and kinetics in pharmaceutical systems. J Pharm Sci. 1999;88(7): 651-660. 85. Alonzo DE, Gao Y, Zhou DL, Mo HP, Zhang GGZ, Taylor LS. Dissolution and precipitation behavior of amorphous solid dispersions. J Pharm Sci. 2011;100(8):3316-3331. 86. Konno H, Taylor LS. Influence of different polymers on the crystallization tendency of molecularly dispersed amorphous felodipine. J Pharm Sci. 2006;95(12):2692-2705. 87. Brouwers J, Brewster ME, Augustijns P. Supersaturating drug delivery systems: the answer to solubility-limited oral bioavailability? J Pharm Sci. 2009;98(8):2549-2572. 88. Gao P, Rush BD, Pfund WP, et al. Development of a supersaturable SEDDS (SSEDDS) formulation of paclitaxel with improved oral bioavailability. J Pharm Sci. 2003;92(12):2386-2398. 89. Guzman HR, Tawa M, Zhang Z, et al. Combined use of crystalline salt forms and precipitation inhibitors to improve oral absorption of celecoxib from solid oral formulations. J Pharm Sci. 2007;96(10):2686-2702. 90. Baird JA, Van Eerdenbrugh B, Taylor LS. A classification system to assess the crystallization tendency of organic molecules from undercooled melts. J Pharm Sci. 2010;99(9):3787-3806. 91. Loftsson T, Brewster ME. Pharmaceutical applications of cyclodextrins .1. Drug solubilization and stabilization. J Pharm Sci. 1996;85(10):1017-1025. 92. Loftsson T, Magnusdottir A, Masson M, Sigurjonsdottir JF. Self-association and cyclodextrin solubilization of drugs. J Pharm Sci. 2002;91(11):2307-2316. 93. Loftsson T, Masson M, Brewster ME. Self-association of cyclodextrins and cyclodextrin complexes. J Pharm Sci. 2004;93(5):1091-1099. 94. Xiang TX, Anderson BD. Molecular dynamics simulation of amorphous indomethacin-poly(vinylpyrrolidone) glasses: solubility and hydrogen bonding interactions. J Pharm Sci. 2013;102(3):876-891. 95. Haleblian J, McCrone W. Pharmaceutical applications of polymorphism. J Pharm Sci. 1969;58(8):911-929. 96. Gu CH, Young V, Grant DJW. Polymorph screening: influence of solvents on the rate of solvent-mediated polymorphic transformation. J Pharm Sci. 2001;90(11):1878-1890. 97. Yu L. Inferring thermodynamic stability relationship of polymorphs from melting data. J Pharm Sci. 1995;84(8):966-974.
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G.E. Amidon et al. / Journal of Pharmaceutical Sciences xxx (2018) 1-6
98. Yamana T, Tsuji A. Comparative stability of cephalosporins in aqueous-solution - kinetics and mechanisms of degradation. J Pharm Sci. 1976;65(11):1563-1574. 99. Wang W, Singh S, Zeng DL, King K, Nema S. Antibody structure, instability, and formulation. J Pharm Sci. 2007;96(1):1-26. 100. Fassberg J, Stella VJ. A kinetic and mechanistic study of the hydrolysis of camptothecin and some analogs. J Pharm Sci. 1992;81(7):676-684. 101. Zhou DL, Zhang GGZ, Law D, Grant DJW, Schmitt EA. Physical stability of amorphous pharmaceuticals: importance of configurational thermodynamic quantities and molecular mobility. J Pharm Sci. 2002;91(8):18631872.
102. Yoshioka M, Hancock BC, Zografi G. Crystallization of indomethacin from the amorphous state below and above its glass-transition temperature. J Pharm Sci. 1994;83(12):1700-1705. 103. Yoshioka M, Hancock BC, Zografi G. Inhibition of indomethacin crystallization in poly(vinylpyrrolidone) coprecipitates. J Pharm Sci. 1995;84(8):983-986. 104. Hancock BC, Zograf G. Characteristics and significance of the amorphous state in pharmaceutical systems. J Pharm Sci. 1997;86(1):1-12. 105. Zhang J, Zografi G. The relationship between “BET” and “free volume”-derived parameters for water vapor absorption into amorphous solids. J Pharm Sci. 2000;89(8):1063-1072.