Polymorphism in the Pharmaceutical Industry E-Book
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- Herausgeber: Wiley-VCH Verlag GmbH & Co. KGaA
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
"Polymorphism in the Pharmaceutical Industry - Solid Form and Drug Development" highlights the relevance of polymorphism in modern pharmaceutical chemistry, with a focus on quality by design (QbD) concepts. It covers all important issues by way of case studies, ranging from properties and crystallization, via thermodynamics, analytics and theoretical modelling right up to patent issues.
As such, the book underscores the importance of solid-state chemistry within chemical and pharmaceutical development. It emphasizes why solid-state issues are important, the approaches needed to avoid problems and the opportunities offered by solid-state properties. The authors include true polymorphs as well as solvates and hydrates, while providing information on physicochemical properties, crystallization thermodynamics, quantum-mechanical modelling, and up-scaling. Important analytical tools to characterize solid-state forms and to quantify mixtures are summarized, and case studies on solid-state development processes in industry are also provided.
Written by acknowledged experts in the field, this is a high-quality reference for researchers, project managers and quality assurance managers in pharmaceutical, agrochemical and fine chemical companies as well as for academics and newcomers to organic solid-state chemistry.
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Seitenzahl: 970
Veröffentlichungsjahr: 2019
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Table of Contents
Cover
Preface to the Second Edition
1 Solid State and Polymorphism of the Drug Substance in the Context of Quality by Design and ICH Guidelines Q8–Q12
1.1 Introduction
1.2 A Short Introduction to Polymorphism and Solid‐State Development
1.3 A Short Introduction to Quality by Design (QbD)
1.4 The Solid State in the Context of Pharmaceutical Development
1.5 Solid‐State Development at Various Stages of the Pharmaceutical Development Process
1.6 Conclusions
References
2 Alternative Solid Forms: Salts
2.1 Introduction
2.2 Salt Formation and Polymorphism in Pharmaceutical Development
2.3 Target Properties of Active Substances for Drug Products
2.4 The Basics of Salt Formation
2.5 Approaches to Salt Preparation and Characterization
2.6 Selection Strategies
2.7 Case Reports
2.8 Discussion and Decision
References
3 Alternative Solid Forms: Co‐crystals
3.1 Introduction
3.2 Types of Pharmaceutical Co‐crystals
3.3 Relevant Pharmaceutical Co‐crystal Properties
3.4 Analytical Tools to Characterize Co‐crystals
3.5 Patent Literature Review
3.6 Current View on Regulatory Aspects of PCCs
3.7 Conclusions
Acknowledgment
References
4 Thermodynamics of Polymorphs and Solvates
4.1 Basic Notions
4.2 Unary System or Unary Section with Polymorphism
4.3 Polymorphism in Binary Systems
4.4 Ternary Systems
4.5 Temperature of Desolvation –
and New Polymorphs Only Accessible Through a Smooth Solvation – Desolvation Process
4.6 Concluding Remarks
Acknowledgments
References
5 Toward Computational Polymorph Prediction
5.1 Could a Computer Predict Polymorphs for the Pharmaceutical Industry?
5.2 Methods of Calculating the Relative Energies of Crystals
5.3 Searching for Possible Crystal Structures
5.4 Comparing Crystal Structures
5.5 Calculation of Properties from Crystal Structures
5.6 Crystal Energy Landscapes
5.7 Potential Uses of Crystal Energy Landscapes in the Pharmaceutical Industry
5.8 Outlook
References
6 Hygroscopicity and Hydrates in Pharmaceutical Solids
6.1 Introduction
6.2 Thermodynamics of Water–Solid Interactions
6.3 Hygroscopicity
6.4 Hydrates
6.5 Significance and Strategies for Developing Hydrate‐Forming Systems
6.6 Conclusions
References
7 The Amorphous State
7.1 Introduction
7.2 Amorphous/Crystalline Solids: Terminology and Brief Confrontation
7.3 Order and Disorder: Structural Identification of Amorphous and Crystal States
7.4 Amorphous Stability, Crystallization Avoidance, and Glass Formation
7.5 The Glass Transition
7.6 Molecular Mobility for
T
>
T
g
7.7 Molecular Mobility and Instability for
T
<
T
g
7.8 Multicomponent Amorphous Systems: Solubility and Stability Issues
7.9 Methods of Amorphization
7.10 Influence of Processing on Properties
7.11 Concluding Remarks
References
8 Approaches to Solid‐Form Screening
8.1 Screening for Salts and Co‐crystals
8.2 Polymorphs, Hydrates, and Solvates
8.3 Screening for Polymorphs, Hydrates, and Solvates
8.4 Conclusion
References
9 Nucleation
9.1 Introduction
9.2 Homogeneous Nucleation
9.3 Heterogeneous and Secondary Nucleation
9.4 Characterization of Nucleation
9.5 Order of Polymorph Appearance – Ostwald's Rule of Stages
9.6 To Seed or Not to Seed?
References
10 Crystallization Process Modeling
10.1 Introduction
10.2 System Characterization and Optimization
10.3 Multidimensional Population Balance Modeling
10.4 Conclusion
References
11 Crystallization Process Scale‐Up, a Quality by Design (QbD) Perspective
11.1 Introduction
11.2 API Critical Quality Attributes (CQAs)
11.3 Statistical Design of Experiments (DoE) for Crystallization Process Development
11.4 Process Analytical Technology (PAT) for Polymorph Control
11.5 Mixing and Scale‐Up Investigations
11.6 Conclusions and Outlook
References
12 Processing‐Induced Phase Transformations and Their Implications on Pharmaceutical Product Quality
12.1 Introduction
12.2 Pharmaceutical Processes Causing Unintended Phase Transformations
12.3 Pharmaceutical Processes Causing Intended Phase Transformations – Obtaining the Desired Physical Form
12.4 Phase Transformations During Pharmaceutical Processing – Implications
12.5 Conclusion
References
13 Surface and Mechanical Properties of Molecular Crystals
13.1 Introduction
13.2 Surface Properties
13.3 Remarks
13.4 Impact of Polymorphism on Powder Flow
13.5 Impact of Polymorphism on Mechanical Properties of Molecular Crystals
13.6 Impact of Polymorphism on Size Reduction by Milling
13.7 Impact of Polymorphism on Powder Compaction Properties
References
14 Analytical Tools to Characterize Solid Forms
14.1 Crystal Structure
14.2 Thermodynamic Properties
14.3 Composition Solvate/Hydrate Stoichiometry
14.4 Conclusion
References
15 Industry Case Studies
15.1 Introduction
15.2 Case Study #1: Holistic Control Strategy for Solid Form
15.3 Case Study #2: Solid‐Form Control of API for Low‐Dose Drug
15.4 Case Study #3: Development of Crystallization Process and Unexpected Influence of Impurity
15.5 Case Study #4: Hydrate/Anhydrate Dilemma
15.6 Case Study #5:
Quality by Design
by Selecting a Cocrystal
15.7 Case Study #6: Dealing with the Consecutive Appearance of New Polymorphs
15.8 Case Study #7: Amorphous API: Issues to be Considered in Drug Development
15.9 Case Study #8: Computational Prediction of Unknown Polymorphs and Experimental Confirmation
References
16 Pharmaceutical Crystal Forms and Crystal‐Form Patents: Novelty and Obviousness
1
16.1 Introduction
16.2 Novelty and Obviousness
16.3 The Scientific Perspective
16.4 The Role of Serendipity in Crystal Forms
16.5 History of Crystal‐Form Patents
16.6 Typical
Ex Post Facto
Arguments on Obviousness
16.7 Conclusion
Acknowledgment
References
Index
End User License Agreement
List of Tables
Chapter 1
Table 1.1 Risk analysis as a part of risk assessment.
Chapter 2
Table 2.1 Classification of acids and bases according to strength.
Table 2.2 Physicochemical properties of NVP‐BS002 solid forms.
Chapter 4
Table 4.1 Variance of a system as a function of the number of phases in equilibr...
Chapter 6
Table 6.1 Hygroscopicity classification.
Chapter 8
Table 8.1 “Classical” crystallization methods.
Chapter 11
Table 11.1 One of the DoE matrixes used to develop the casopitant mesylate cryst...
Table 11.2 Handling of the crystallization slurry in the reactors at three scale...
Table 11.3 Handling of the crystallization slurry in the reactors at three scale...
Table 11.4 VisiMix® calculated values for several turbulent shear rate values in...
Table 11.5 Handling of the crystallization slurry in the reactors at three scale...
Table 11.6 Mesomixing times calculated for the three reactors discussed, at cond...
Table 11.7 Cooling rates that could be attained in an 800 L plant reactor, opera...
Chapter 13
Table 13.1 Surface characterization techniques: relevance and information.
Table 13.2 Material‐dispersive surface energy response and crystal habit changes...
Table 13.3 Comparison of behavior of different polymorphs of carbamazepine under...
Chapter 15
Table 15.1 Physicochemical properties of form A and form B.
Table 15.2 Chemical structure of bitopertin and thermoanalytical data of the rel...
Table 15.3 Thermoanalytical data of the identified polymorphs.
List of Illustrations
Chapter 1
Figure 1.1 Schematic depiction of various types of solid forms.
Figure 1.2 Typical development process of a pharmaceutical product and re...
Figure 1.3 The interplay of form and formation resulting in powders that ...
Chapter 2
Figure 2.1 Salt and solid form selection.
Figure 2.2 Theoretical solubility diagram of a basic substance, p
K
a
= 9...
Figure 2.3 Theoretical solubility diagram of an acidic substance, p
K
a
=...
Figure 2.4 Theoretical solubility diagram of an amphoteric substance, p
K
...
Figure 2.5 Different phases of the search for an appropriate salt form.
Figure 2.6 Organizational sequence of activities in industrial research a...
Chapter 3
Scheme 3.1 UCB racetams, or 2‐oxo‐1‐pyrrolidine acetamides. Molecular s...
Figure 3.1 Morphology changes induced by co‐crystallization: comparison ...
Figure 3.2 Schematic representation of the co‐crystal domains. Ionic co‐c...
Figure 3.3 Packing diagram of the melatonin/pimelic acid co‐crystal showi...
Figure 3.4 (A) Microscopy picture of crystals of the candidate molecule, ...
Scheme 3.2 Structure of methyl paraben.
Scheme 3.3 Co‐crystal of melamine and cyanuric acid.
Figure 3.5 Evolution of the number of scientific papers and patents per y...
Figure 3.6 Major claimed advantages in the PatBase search on pharmaceutic...
Chapter 4
Figure 4.1 Illustration of the definition of stable, metastable, unstabl...
Figure 4.2 Unary system without polymorphism
P–T
projection (a)
P–V
...
Figure 4.3
P
–
T
diagrams for enantiotropy (left) and a system with a mon...
Figure 4.4 Enantiotropy with a fictive triple point T
4
. Source: Refs. [11...
Figure 4.5 (a) Enantiotropic and (b) monotropic character. In (a), the st...
Figure 4.6 〈A
1
〉 stands for A form 1, 〈A
2
〉 stands for A form 2, 〈A
3
〉 stand...
Figure 4.7 Representation of polymorphism for a stoichiometric compound. ...
Figure 4.8 ss stands for solid solution; sat. sol. stands for saturated s...
Figure 4.9 ss stands for solid solution; sat. sol. stands for saturated s...
Figure 4.10 Binary system between 1,3‐dimethyurea (DMU) and water (
P
= 1 ...
Figure 4.11 Presence of a complete solid solution for one polymorph. (a) ...
Figure 4.12 : Two stable polymorphic forms for component A both with limi...
Figure 4.13 Contrary to Figure 4.12d, the temperature of enantiotropic tr...
Figure 4.14 Binary system under constant pressure. The temperature of tra...
Figure 4.15 (a) The stable polymorph of one component (〈A
1
〉) forms a comp...
Figure 4.16 (a) The phases in stable equilibrium in every domain are ➀ ss...
Figure 4.17 The shaded domain corresponds to the solid solution ss2 stemm...
Figure 4.18 (a) Peritectoid invariant at
T
π
. The stable phases in ...
Figure 4.19 Ideal cases that show the moisture uptake and release vs rela...
Figure 4.20 Binary system showing a nonstoichiometric hydrate. Full lines...
Figure 4.21 (a) Evolution of a solute (up to deliquescence) exposed in an...
Figure 4.22 Isobaric binary system between a solute M and a solvent A. If...
Figure 4.23 Isobaric binary system between a solute M and a solvent A. If...
Figure 4.24 (a–d) Isothermal and isobaric ternary phase diagrams, M (solu...
Figure 4.25 Schematic ternary isotherm and binary system (increasing temp...
Figure 4.26 The stable phases in every domain are at
T
<
T
P
: ➀ 〈TMM(S)〉...
Figure 4.27 Polythermic projection of the ternary system between two dias...
Figure 4.28 If the system is in stable equilibrium, domains 1–8 contain t...
Figure 4.29 If the system is in stable equilibrium, domains 1–5 contain t...
Chapter 5
Figure 5.1 The molecules whose crystal structures have been used in the ...
Figure 5.2 A crystal structure prediction study of tazofelone: (a) Summar...
Chapter 6
Figure 6.1 Water–solid interactions.
Figure 6.2 (a) Sorption kinetics of microcrystalline cellulose, showing t...
Figure 6.3 Moisture sorption–desorption behaviors observed for pharmaceut...
Figure 6.4 Frequency of multiple crystal forms (CF), polymorphs, hydrates...
Figure 6.5 Calculated water activity of aqueous–organic solvent mixtures ...
Figure 6.6 Calculated water activity of methanol–water and acetone–water ...
Figure 6.7 (a) Moisture sorption isotherms and (b) crystal structures, sh...
Figure 6.8 (a) Empirically derived phase diagram of sodium (
S
)‐naproxen a...
Figure 6.9 (a) GVS isotherms of nonmicronized and micronized GSK ApoA‐1 u...
Figure 6.10 Flowchart for evaluating the water uptake (expressed as %w/w)...
Chapter 7
Figure 7.1 (a) Two‐dimensional representation of a molecular crystal. (b...
Figure 7.2 X‐ray diffraction patterns of ethanol. From top to bottom: The...
Figure 7.3 Bottom: neutron intensity measurement for low‐temperature amor...
Figure 7.4 X‐ray diffraction patterns of meta‐toluidine. Liquid state: 29...
Figure 7.5 Radial pair distribution function
G
(
r
) of anhydrous crystallin...
Figure 7.6 Schematic representation of the evolution of the Gibbs functio...
Figure 7.7 (a) Photomicrograph of the indomethacin α‐crystal form grown f...
Figure 7.8 Time–temperature–transformation (TTT) diagram for crystalli...
Figure 7.9 Schematic representation of the crystal/liquid interface showi...
Figure 7.10 (a) Temperature evolution of the specific heat (
C
p
) of indo...
Figure 7.11 Temperature dependence (schematic) of the excess entropy for ...
Figure 7.12 Examples of energy landscape topologies showing an example of...
Figure 7.13 (a) Real and imaginary part of the dielectric susceptibility ...
Figure 7.14
T
g
‐scaled Arrhenius representation, proposed by Angell [5...
Figure 7.15 Arrhenius plot (log (
τ
or
η
) as a function of 1000/
Figure 7.16 DSC heating scans for amorphous indomethacin aged during vari...
Figure 7.17 Enthalpic relaxation of amorphous sucrose at three temperatur...
Figure 7.18 Fictive temperature: Top: definition on the
H
(
T
) curve. It sh...
Figure 7.19 Arrhenius plot summarizing the temperature evolutions of the ...
Figure 7.20 (a) Δ
H
mix
≤ 0: No miscibility gap in the liquid state. Phas...
Figure 7.21 (a) The
in vitro
experimental aqueous solubility profiles of ...
Figure 7.22 Schematic state diagram of an API and a polymer. It allows to...
Figure 7.23 Principal routes for the formation of pharmaceutical glasses....
Figure 7.24 Illustration of the impact of the history of a glassy sample ...
Figure 7.25 Dissolution of felodipine in water–ethanol. Crystalline felod...
Chapter 8
Figure 8.1 Scheme for form selection process.
Figure 8.2 Microscope image of an API with an unfavorable needle‐like mor...
Figure 8.3 Possible interaction motif between an amide and a carboxylic a...
Figure 8.4 Frequency of occurrence of solid forms of organic molecules: (...
Figure 8.5 Energy barriers for polymorph crystallization.
Figure 8.6 Scheme for selecting the optimal form. White indicates good, l...
Chapter 9
Figure 9.1 Conceptual picture of the mechanisms of nucleation according ...
Figure 9.2 Free energy required according to classical nucleation theory ...
Figure 9.3 A qualitative representation of the energy profile of a cluste...
Figure 9.4 Conceptualization of different secondary nucleation mechanisms...
Figure 9.5 A typical example of detection time experiments in a 500 ml cr...
Figure 9.6 Typical examples of detection time distributions observed in s...
Figure 9.7 Behavior of the ratio
as a function of the concentration
Figure 9.8 Solubility and metastable zone of a stable polymorph (blue) an...
Figure 9.9 Seed chart.
Solid line
: ideal growth line;
diamonds
: product f...
Chapter 10
Figure 10.1 (a) Conceptual drawing of a plug flow crystallizer with cont...
Figure 10.2 Schematic overview of parameter estimation (A) and model‐base...
Figure 10.3 Evolution of solid composition and liquid concentration over ...
Figure 10.4 Comparis on of experimental (markers) and fitted modeling (so...
Figure 10.5 a) Contour plot of velocity magnitude in ms
for a stirring...
Figure 10.6 Pareto optimal set of the two‐objective optimization problem ...
Figure 10.7 Different combined cooling and antisolvent processes as inves...
Chapter 11
Figure 11.1 Casopitant mesylate.
Figure 11.2 Half normal probability plot (Design‐Expert®) showing that th...
Figure 11.3 Model term pareto chart (Fusion PRO®) indicating that seeding...
Figure 11.4 Preliminary sweet space (Fusion PRO®) for the casopitant mesy...
Figure 11.5 An example of a design space (green rectangle) and of a contr...
Figure 11.6 Monitoring of a crystallization process with the FBRM® and PV...
Figure 11.7 Selected values for input for VisiMix® calculations for the c...
Figure 11.8 Linear correlation between mean particle size and crystallize...
Figure 11.9 VisiMix® calculated tip velocity of the impeller for the benc...
Figure 11.10 VisiMix® calculated average power per mass for the bench (RC...
Figure 11.11 VisiMix® calculated turbulent shear rate (maximum value) for...
Figure 11.12 An example of a cubic cooling profile, with the temperature ...
Chapter 12
Figure 12.1 Schematic representation of processing‐induced phase transfo...
Figure 12.2 Schematic representation of the mechanism of phase transforma...
Figure 12.3 Milling‐induced transformations – influence of the physical f...
Figure 12.4 Phase transformations of amlodipine besylate during granulati...
Figure 12.5 Effect of PVP concentration (% w/w) on the weight fraction of...
Figure 12.6 A three‐dimensional empirical phase diagram based on water so...
Figure 12.7 Extent of indomethacin crystallization (expressed as crystall...
Figure 12.8 A plot summarizing the evidence of crystallization (based on ...
Figure 12.9 Phase transformations of
myo
‐inositol during freeze‐drying. F...
Figure 12.10 Chromatograms of unmilled furosemide and samples cryo‐milled...
Figure 12.11 (a) Lactamization rates of gabapentin milled for 10 min and ...
Figure 12.12 Dose‐normalized plasma concentration of vemurafenib after or...
Figure 12.13 Box plots comparing (a) the extent of
trehalose dihydrate
(
T
...
Figure 12.14 The stability of spray‐freeze‐dried PvdQ in three different ...
Figure 12.15 (a) Second‐derivative
Fourier transform infrared spectroscop
...
Figure 12.16 Dissolution profiles of theophylline tablets stored at 25 °C...
Figure 12.17 Dissolution profile of (i) crystalline
indomethacin
(
IMC
), (...
Figure 12.18 (a) Dissolution profiles of lornoxicam from granule/powder f...
Chapter 13
Figure 13.1 Techniques for surface characterization at different size sca...
Figure 13.2 Library of particles: structure–property–response/performance...
Figure 13.3 (a) Microscopy images for unmicronized material form A – need...
Figure 13.4 Surface energetics for both polymorphs represented in sorptio...
Figure 13.5 (a) SEM images of form A mixed with lactose (top) and form B ...
Figure 13.6 Process of milling: fracture and abrasion [28].
Figure 13.7 Same material, same lot divided into two: A – unchanged; B – ...
Figure 13.8 IGC results for the lactose monohydrate, hydrophilic anhydrou...
Figure 13.9 Representation of milling‐induced disorder in molecular cryst...
Figure 13.10 An higher surface energy is found for cryo‐milled material a...
Figure 13.11 Defects present in molecular crystals. Panel (a) presents an...
Figure 13.12 (a) Carbamazepine form I. (b) Carbamazepine form III.
Figure 13.13 Packing arrangement of (a) famotidine form A and (b) famotid...
Figure 13.14 Crystal packing and mechanical behavior of three crystal for...
Figure 13.15 Indomethacin crystal structure. (a) Form α. (b) Form γ.
Figure 13.16 Slip planes in indomethacin crystals. (a) Form α. (b) Form γ...
Figure 13.17 Crystal structure of ranitidine hydrochloride (a) form I and...
Chapter 14
Figure 14.1 Principle of Bragg's law: constructive interference occurs w...
Figure 14.2 XRPD patterns of paracetamol Form I (top, offset) and Form II...
Figure 14.3 Raman spectra of three anhydrous forms of
carbamazepine
(
CBZ
)...
Figure 14.4 Raman spectra of (from bottom to top) the co‐crystal former, ...
Figure 14.5 Comparison of
13
C CP/MAS ssNMR spectra of two different polym...
Figure 14.6 DSC thermogram of paracetamol Form I, measured with a heating...
Figure 14.7 DSC thermograms for carbamazepine Form III at different heati...
Figure 14.8 Comparison of the DSC curves of methylene blue pentahydrate i...
Figure 14.9 DSC thermogram of amorphous paracetamol, measured with a heat...
Figure 14.10 Amorphous content determination by isothermal microcalorimet...
Figure 14.11 IMC curves for 100% crystalline (dashed line) and 99.5% crys...
Figure 14.12Figure 14.12 Example of the evaluation of IMC measurements for...
Figure 14.13 Example of the SolCal curves of an amorphous and a crystalli...
Figure 14.14 TG–FTIR of three forms of carbamazepine. (a) TGA curves of t...
Figure 14.15 Continuous DVS scan exemplified with the pentahydrate of met...
Figure 14.16 DVS curve of microcrystalline cellulose measured with a step...
Figure 14.17 Comparison of the DVS scans from 0% to 80% relative humidity...
Chapter 15
Figure 15.1 Transformation scheme of the main solid forms of the drug sub...
Figure 15.2 Schematic energy–temperature diagram for the identified polym...
Figure 15.3 Solubility of bitopertin in ethanol, target point for seeding...
Figure 15.4 Chemical structure of dimer impurity
2
.
Figure 15.5 Transformation scheme of the relevant solid forms. The dotted...
Figure 15.6 Schematic energy–temperature diagram for the identified polym...
Figure 15.7 Transformation scheme of the known solid forms after completi...
Figure 15.8 Chemical structure of vemurafenib.
Figure 15.9 Transformation scheme of the relevant solid forms of vemurafe...
Figure 15.10 USP4 dissolution profiles of several vemurafenib preparation...
Figure 15.11 Chemical structure of dalcetrapib.
Guide
Cover
Table of Contents
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Polymorphism in the Pharmaceutical Industry
Solid Form and Drug Development
Edited by Rolf Hilfiker
Markus von Raumer
Copyright
Editors
Dr. Rolf Hilfiker
Solvias AG
Solid State Development
Römerpark 2
4303 Kaiseraugst
Switzerland
Dr. Markus von Raumer
Idorsia Pharmaceuticals Ltd
Preformulation & Preclinical Galenics
Hegenheimermattweg 91
4123 Allschwil
Switzerland
Cover
Close up image of crystal (Getty ID 626957019, Daniel Grizelj)
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Preface to the Second Edition
Since the first edition of “Polymorphism in the pharmaceutical industry,” pharmaceutical research and development continued to progress and evolve. Exploration of new chemical spaces and the trend to select very low soluble compounds for pharmaceutical development has, on the one hand, boosted the application of alternative formulation approaches such as amorphous solid dispersions, and on the other hand, it has stimulated the search for alternative crystalline solids such as cocrystals.
Thermodynamics and kinetics continue to rule the game and pose fascinating riddles and challenges to many scientists in the pharmaceutical industry and the academic world.
What has also changed is the view of the regulators and the industry on how pharmaceutical development should be done. Efforts to harmonize development and quality concepts resulted in new ICH guidelines Q8 to Q12 that introduce quality by design (QbD) to the pharmaceutical industry. One of the conclusions therein is that modern science should be better used throughout the product lifecycle. The ICH guideline Q11 general principle states that “The goal of manufacturing process development for the drug substance is to establish a commercial manufacturing process capable of consistently producing drug substance of the intended quality.” Furthermore, the drug substance quality is linked to the drug product: “The intended quality of the drug substance should be determined through consideration of its use in the drug product as well as from knowledge and understanding of its physical, chemical, biological, and microbiological properties and characteristics, which can influence the development of the drug product (e.g. the solubility of the drug substance can affect the choice of dosage form). …”. All QbD considerations, be it for drug substance or drug product, will therefore necessarily be influenced by the solid form and solid state of the drug substance.
The philosophy of the QbD framework with its knowledge‐ and science‐based approach calls for a very good understanding of the system under investigation, which obviously includes the solid state of the drug substance. Such an understanding is not only limited to the internal order or disorder but also encompasses surface aspects of solids. Understanding is closely related to qualitative and/or quantitative description, which in turn requires very powerful and cutting‐edge analytical technologies.
QbD in the pharmaceutical industry is a dynamic concept and interpretation of guidelines will and do change over time. However, the basic idea behind the QbD framework and the underlying concept will remain unchanged.
Several new chapters were introduced in this edition to provide a holistic view of very different aspects of solid‐form development in general and on polymorphism in particular. A general overview of the impact and importance of solid‐form properties on drug development is given in Chapter 1. Next to salts, which are discussed in Chapter 2, a new Chapter 3 covering cocrystals describes the expansion of the possible solid‐form space that can be considered for solid‐form development. As moisture is ubiquitous in ambient conditions, the interaction of solids with water is explained in depth in Chapter 6. Understanding the thermodynamics of the system under investigation and visualization of stable phases in phase diagrams help to appreciate and highlight the possible complexity that such systems can show (see Chapter 4). The first step of crystallization, and hence of polymorph formation, is nucleation, which is discussed in Chapter 9. Although one aspect is the identification of the polymorph landscape of a given species (see Chapter 8), the large‐scale making of the desired form, i.e. crystallization process development, remains one of the key challenges in pharmaceutical chemical development (Chapters and 11). As mentioned above, noncrystalline, amorphous solids (Chapter 7) play an increasingly important role. When solid drug substance is finally formulated into a drug product, aspects related to surface and mechanical properties (Chapter 13) as well as possible processing‐induced phase transformations (Chapter 12) become important. Chapter 5 demonstrates the power of polymorph prediction using sophisticated models while taking advantage of ever‐increasing computing power. The various chapters on various analytical techniques in the first edition are now summarized in Chapter 14. The diversity of problems and questions arising during solid‐form development are presented by industry cases in Chapter 15. Finally, Chapter 16 presents and elucidates the aspects of novelty and obviousness when considering crystal patents.
New chapters were introduced in the second edition, which means that some chapters of the first edition had to be omitted. The first edition, therefore, remains a useful tool that is complemented by this volume. What has remained the same is the excellent quality of the contributions for which we sincerely thank all authors. We are also grateful to Wiley‐VCH for their support and encouragement.
August 2018 Rolf Hilfiker
Markus von Raumer
1Solid State and Polymorphism of the Drug Substance in the Context of Quality by Design and ICH Guidelines Q8–Q12
Markus von Raumer1 and Rolf Hilfiker2
1Idorsia Pharmaceuticals Ltd., Hegenheimermattweg 91, Allschwil, 4123, Switzerland
2Solvias AG, Römerpark 2, Kaiseraugst, 4303, Switzerland
1.1 Introduction
The way in which the pharmaceutical industry is approaching technical development has evolved very much in the recent years. Fresh concepts coming from other industries have been introduced with the desire to push for a more science and risk‐based development approach throughout the product life cycle. Quality by design (QbD) in the pharmaceutical industry is an outcome of the efforts to harmonize development quality concepts and understandings by regulatory agencies and resulted in the International Conference of Harmonization (ICH) guidelines Q8 [1], Q9 [2], Q10 [3], Q11 [4], and Q12 [5]. Although first devised for pharmaceutical development (Q8), the QbD concepts and related tools were rapidly recognized as being very helpful for chemical development. A result of this process was the Q11 guideline that provides guidance for drug substance as defined in the scope of the ICH guideline Q6A [6] (this guideline contains the well‐known decision trees for polymorphism).
The scope of this chapter is to give a short introduction to the solid‐state development process in the pharmaceutical industry and to QbD. Questions on how QbD principles can be applied to solid‐state development will be discussed, highlighting how the solid state is an important parameter to be considered in the pharmaceutical development process. For that purpose, some general insights into the relevance of the drug substance (DS) solid state throughout various fields of pharmaceutical development will be given.
1.2 A Short Introduction to Polymorphism and Solid‐State Development
Only a brief overview of solid‐state development and polymorphism shall be given here. Subsequent chapters in this book will discuss the various aspects in more detail.
Many organic and inorganic compounds can exist in different solid forms [7–12]. They can be in the amorphous (Chapter ), i.e. disordered [13], or in the crystalline, i.e. ordered, state. In accordance with McCrone's definition [8], “The polymorphism of any element or compound is its ability to crystallize as more than one distinct crystal species,” we will call different crystal arrangements of the same chemical composition polymorphs (Figure 1.1). Especially in the pharmaceutical context, the term “polymorph or polymorphism” is used more broadly by many authors and regulatory agencies. The amorphous state, as well as hydrates or solvates (both of which do not have the same chemical composition), are tacitly included by the term. Because different inter‐ and intramolecular interactions such as van der Waals interactions and hydrogen bonds will be present in different crystal structures, different polymorphs will have different free energies and therefore different physical properties such as solubility, chemical stability, melting point, density, etc. (Chapter ). Hence, the crystal form of a solid material in development is often considered a critical quality attribute (CQA, see next section). Of practical importance are also solvates [14], sometimes called pseudopolymorphs, where solvent molecules are incorporated in the crystal lattice in a stoichiometric or nonstoichiometric [12, 15] way. Hydrates (Chapter ), where the solvent is water, are of particular interest because of the omnipresence of water. In addition to the crystalline, amorphous, and liquid states, condensed matter can exist in various mesophases. These mesophases are characterized by exhibiting partial order between that of a crystalline and an amorphous state [16, 17]. Several drug substances are known to form liquid crystalline phases, which can be either thermotropic, where the liquid crystal formation is induced by temperature, or lyotropic, where the transition is solvent induced [18–20].
Figure 1.1 Schematic depiction of various types of solid forms.
Polymorphism is a very common phenomenon [11, 21–25] in connection with small‐molecule drug substances. The literature values concerning the prevalence of true polymorphs range from 32% [26] to 51% [27–29] of small organic molecules (molecular weight <600 g mol–1). According to the same references, 56% and 87%, respectively, have more than one solid form if solvates are included in the count.
In the context of pharmaceutical solid‐state development, polymorph considerations are made subsequent to general considerations like salt [30] (Chapter ) or co‐crystal [31] (Chapter ) formation. When a compound is acidic or basic, it is often possible to create a salt with a suitable base or acid, and such a salt can, in turn, often be crystallized. Crystalline salts may then again be able to exist as various polymorphs or solvates. From the scientific perspective, solvates can be considered as co‐crystals of the active molecule and solvent. In the pharmaceutical industry, the term co‐crystal is used in a slightly different way, however. A pharmaceutical co‐crystal is a solid, where the constituting molecules are in the solid phase as single components at room temperature. Obviously, solvates, co‐crystals and salts will have different properties than the polymorphs of the active molecule. About half of all active molecules are marketed as salts [25, 30, 32]. Recently, also the first co‐crystal composed of two active molecules reached the market (Entresto from Novartis [33]). Polymorphs, solvates, salts, and co‐crystals are schematically depicted in Figure 1.1. We will use the term “drug substance” for the therapeutic moiety, which may be a solvate, salt, or a co‐crystal, whereas the single, uncharged molecule will be called the “active molecule.”
1.3 A Short Introduction to Quality by Design (QbD)
Only a brief overview of QbD shall be given here. Pharmaceutical applications thereof were described in a far more detailed and applied way elsewhere [34, 35].
QbD is not a new concept. Indeed, it was introduced in the manufacturing industry in the 1950s. The automobile and electronic industries were early users of QbD as shown in a comprehensive textbook on the subject by Juran [36]. This industry rapidly realized that the process of QbD provides a systematic and structured framework for documenting and presenting a development rationale while acquiring knowledge about the product and the process. As a result, it could be ensured that products were manufactured, which consistently fit the desired quality (and safety, and efficacy, if applied to pharma). In addition to being safe and cost effective, any process must be robust in order to be successfully implemented and transferred. In contrast to the traditional approach for process development, QbD leads to robust processes. Because of its business benefits, many pharmaceutical companies have already implemented or are now implementing QbD methodologies. QbD has recently evolved from a purely regulatory initiative to an industry initiative with strong encouragement from the regulatory agencies who are concerned about product quality issues and possible drug shortages [37].
QbD introduces a formalism for development based on first understanding the product, then understanding the processes leading to the product, and finally of controlling the process over the product life cycle. It starts with defining the development goal in a quality target product profile (QTPP). As in any other discipline, knowing what is to be developed makes the development easier or possible at all. This means that, for instance, for the development of a drug product (DP), the route of application (oral), the dosage form (tablet, immediate release), and the strength (efficacy and safety) should be defined and justified at the beginning of the process. Although definition is somehow easy, justification is more complicated as it requires quite a lot of prior knowledge. Here, knowledge management and the transfer of knowledge throughout the pharmaceutical development help to justify decisions that are taken. For example, preclinical pharmacokinetic results, possibly coupled with in silico considerations, can help to make informed decisions on the DS. A rationale for the solid form and, for example, target particle size can be gained here. Refined with the human PK data of clinical phases I and II, a rationale for phase III and market product can be developed. A QTPP can contain input from all stakeholders, i.e. the patient, the physician, and the pharmacist. Next comes the CQA, which should encompass various aspects related to quality, efficacy, and safety. Any physical, chemical, biological, or microbiological property or characteristic that should be within an appropriate limit, range, or distribution to ensure the desired product quality (or efficacy, or safety) is a CQA. As an example, the assay of a DP should be, for example, between 90% and 110% as a target. Assay variability would potentially affect safety and efficacy, and this quality attribute is hence set as critical. Process variables may affect the assay of the DP; hence, assay is to be evaluated throughout formulation development. Other CQAs can be the polymorphic form and the particle size distribution of the DS to name only few of them. Indeed, all DS attributes are candidates of being defined as CQA in a first round of contemplation. Generally, every DP CQA, except maybe appearance, is affected by DS attributes. Also the purity, the solid‐state form, the morphology, and the particle size distribution impact more than one DP CQA. In a next step, a risk assessment for critical material attributes (CMA) and critical process parameters (CPP) is conducted. Risk assessment and criticality are words that encompass quite some room for interpretation and they deserve some short discussion. A material attribute or a process parameter is deemed critical if its variability has an impact on a CQA and therefore has to be controlled within narrow specifications to ensure that the DS, or DP, will meet specifications. Risk assessment is done regularly in other industries and various tools and ways exist in doing so. One of the possibilities is a split in risk identification, risk analysis, and risk evaluation. Risk identification consists of identifying potential factors causing an overall effect. A popular way of doing so is a cause‐and‐effect analysis that can be graphically represented by an Ishikawa, or fishbone, diagram. The causes are traditionally grouped in six major categories, which are related to men (people), methods, machines, materials, measurements, and milieu (environment). For example, for a crystallization process and final particle size distribution as effect, the reactor with its baffles, stirrer, heat transfer characteristics, etc., would fall under the machine category and the crystallization process itself (concentration profiles, temperature, stoichiometry, addition rate, etc.) would fall in the method category. Risk analysis then picks up all process parameters and material attributes and links them to CQAs in a matrix‐type table (see Table 1.1 as an example). High risks are then further evaluated. Various tools and approaches exist for risk evaluation. One often cited in pharmaceutical QbD is the failure mode effect analysis (FMEA). The goal of this exercise is a ranking and priority ranking of risks. This is done by attribution of a risk priority number based on probability, severity, and detectability of the failure. For example, having a wrong polymorph would be severe, highly probable (obviously dependent on the compound and the underlying crystallization process, let us take this as an example), but also easily detectable. This would lead to a high risk priority number and consequently to a high priority on the “to do list” of items to be analyzed in more depth, e.g. by development of a robust crystallization process, which again would require good knowledge of the polymorph landscape and associated properties of the polymorphs. The unit operation of granulation in a high shear granulator can serve as another example. A critical process parameter could be the rate of the impeller; the respective failure mode would be a too high rate and a too long mixing time. As a consequence, larger granules could be obtained that, in turn, could lead to an undesired dissolution profile for the final tablet, which was defined earlier in the QTPP, and that was identified as a CQA (as an example). Again a high risk priority number would call for a deeper investigation of this issue.
Table 1.1 Risk analysis as a part of risk assessment.
DS material attribute
DP CQA
Salt co‐crystal
Polymorph
Crystallinity
Morphology
Purity
Solvent content
Particle size
Hygroscopicity
Appearance
Low
Low
Low
Low
Low
Low
Low
Low
Identity
High
Low
Low
Low
Low
Low
Low
Low
Assay
Low
Low
Low
Low
High
Low
Low
High
Impurity
Low
High
High
Low
High
High
Low
Low
Content uniformity
Low
Low
Low
High
Low
Low
High
High
Dissolution
High
High
High
High
Low
Low
High
Low
Material attributes and their possible impact on quality attributes of the drug product are exemplified (case‐by‐case matrix).
As many of the CMAs and critical process parameters are influenced by multiple variables, a meaningful and common way of investigation of the identified high risk priority numbers consists of using statistical experimentation and analysis of results. Design of experiments (DoE) is a very useful tool for that. Use of screening designs helps to identify the statistically significant contributors to a process. This is, in general, followed by an optimization DoE (response surface designs) to obtain good mathematical models of the investigated experimental space. The art in all this exercise consists of finding and describing the right parameters and attributes that are to be studied. For instance, in the development of a scale‐up crystallization process, it is not the stirring rate that is to be varied but rather a characteristic and relevant mixing time [38]. Results of such studies generally lead to understanding of the process and help to identify how close to a possible edge of failure a “standard parameter” process is and to define a design space, i.e. an ensemble of parameters which, if varied within a certain range, still lead to the desired process outcome as defined by its specifications. The whole process can then be continued by introducing control. Use of process analytical technologies (PAT) and the introduction of a control space within the design space coupled to a control strategy will help to keep processes within the desired boundaries. QbD also leaves some room for continuous improvement. As with any process that is repeated many times, experience will lead to identification of small improvements, which might lead to increased efficiency without impact on any CQA. The possibility to introduce continuous improvement to pharmaceutical processes without a huge regulatory burden is currently in preparation by the ICH.
The beauty of QbD is that the concept can be applied at various levels: from a top line holistic view level down to very specific single activities. The philosophy and its associated tools allow, for example, the development of an analytical method under such principles [39, 40].
As mentioned earlier, QbD is a systematic procedure that leads to understanding of the product, understanding of the process leading to that product, and finally providing the knowledge to control that process. Many things that are described above are logical and common sense from a scientific point of view. Because the justifications needed for the QTPP, for the CQA, and the risk assessment are based on a scientific rationale, a deep understanding of the matter is needed. And the matter that is discussed in this book in depth is molecular crystals and their bulk appearance in powders. Calling for a deep understanding, in turn, opens the door to science, and this encompasses any aspect related to this topic, from thermodynamic questions to kinetic considerations, from analytical questions to crystallization process scale‐up problems, and from surface and mechanical properties to intellectual property‐related questions (to name only a few aspects).
From the perspective of the pharmaceutical solid‐state development, this means that answers and rationales for many questions and decisions need to be elaborated. This always with the goal in mind to understand, possibly predict, and quantify the outcome of any subprocess to ultimately ensure safety, efficacy, and quality of the medicine brought to patients.
1.4 The Solid State in the Context of Pharmaceutical Development
1.4.1 Typical Drug Discovery and Development
Typically, it takes 8–12 years [41, 42], or sometimes even longer, for a molecule with biological activity to progress from its first synthesis to market introduction as an efficacious, formulated drug. This process is normally divided into two main phases: (i) research or discovery and (ii) development. In the research phase, the appropriate target for a particular disease model is identified and validated, and candidate molecules are synthesized or chosen from libraries. They are primarily tested with respect to binding affinity to the target or, if possible, directly for their potential to alter a target's activity. Sometimes, other parameters, such as selectivity, are considered at this stage as well. Promising candidates are usually termed “hits.” As a rule at this stage, limited attention is paid to the possibility to formulate a drug for a certain administration route. Often, from a drug delivery aspect, simple vehicles like DMSO solutions are used. As a result, the activity of especially poorly water‐soluble drugs may not be identified at all because they precipitate under the used in vitro conditions [43]. In a medicinal chemistry program, the “hits” are then modified to improve physicochemical parameters such as solubility and partition coefficient. This is the first time that solid‐state properties come into play. When solubility is evaluated, it is critical to know whether the solubility of an amorphous or crystalline substance was measured. Permeation measurements are performed using, e.g. Caco‐2 [44], PAMPA [45], or MDCK [46] assays, and dose–response studies are conducted in in vitro models. Selectivity is assessed in counter screens. At the same time, preliminary safety studies are carried out, and IP opportunities are assessed. Structure–activity relationship (SAR) considerations play a large role at this stage. Molecules that show promise in all important aspects are called “leads.” Often several series of leads are identified and are then further optimized and scrutinized in more sophisticated models, including early metabolic and in vivo studies. Both pharmacokinetics (PK, quantitative relationship between the administered dose and the observed concentration of the drug and its metabolites in the body, i.e. plasma and/or tissue) and pharmacodynamics (PD, quantitative relationship between the drug concentration in plasma and/or tissue and the magnitude of the observed pharmacological effect) are studied in animal models in order to predict bioavailability and dose in humans. Simultaneously with the characterization of the DS, a proper dosage form needs to be designed, enabling the DS to exert its maximum effect. For freely water‐soluble drugs, this is less critical than for poorly water‐soluble drugs, which cannot be properly investigated in the research stage without the aid of an adequate dosage form. In the discovery phase, high‐throughput methods play an increasingly important role in many aspects, such as target identification, synthesis of potential candidate molecules, and screening of candidate molecules. Considering that only about 1 out of 10 000 synthesized molecules will reach the market, high‐throughput approaches are definitely a necessity. The molecule that is found to be optimal after these assessments is then promoted to the next stage, i.e. development.
The development process of a pharmaceutical product is schematically depicted in Figure 1.2. It consists of a preclinical and a clinical phase. Although drug companies' approaches to the preclinical phase can differ somewhat, the clinical phase is treated very similarly everywhere because of regulatory requirements.
Figure 1.2 Typical development process of a pharmaceutical product and related solid state.
In the preclinical phase, enough data is gathered to compile an Investigational New Drug Application (IND) in the United States or a Clinical Trial Application (CTA) in the European Union, which is the prerequisite for the first use of the substance in humans. For obvious reasons, particular emphasis is placed on toxicology studies during this phase, including assessment of toxicity by single‐dose and repeated‐dose administration. An absolute necessity at this stage is that the drug is bioavailable, resulting in sufficient exposure of the animals to the drug to obtain an adequate assessment of its toxicity profile. The duration of the preclinical development phase is between one and two years [47], and the attrition rate is approximately 30% [41]. In the clinical phases, the product is first tested on healthy volunteers and then on small and large patient populations. For certain disease indications, such as oncology, clinical phase I studies are performed directly on patients. Approximate population sizes are given in Figure 1.2. One has to bear in mind, however, that these numbers depend significantly on the indication the drug is intended to treat. Overall attrition rates during the clinical phases and submission to launch are between 80% and 90% [41, 48].
In order to perform clinical development, obviously some clinical trial material (CTM) needs to be available in the required amount at the required quality and appropriate time. As a consequence, chemistry, manufacturing, and controls (CMC) activities are to be conducted at risk, much ahead of any clinical results.
Considering the high investment costs it takes to develop new innovative medicines [49], it is of major interest to manage the pharmaceutical development risks. To lower the risk that an active molecule falls into the attrition funnel, developability criteria are to be considered upon selection. For that purpose, a close interaction of discovery and development teams helps to create mutual understandings. Developability assessment should comprise the identification and selection of the optimal DS (including the optimal solid form for the intended application route and use) and should consider the feasibility of required formulation principles that allow delivering the required dose. Potential hurdles should be identified early on [50–52]. A good understanding of the dose‐dependent PK profile and related parameters such as solubility, stability, permeability, first‐pass effect, clearance, etc., will help to evaluate risks for DP development as a function of extrapolated needed doses (based on potency, receptor occupancy, exposure profile, etc.). Luckily, modern software tools are used more and more to provide development guidance and to support decision making. In silico modeling and simulation help to visualize and understand the interplay of a multitude of parameters and variables of underlying principles. Such tools include physiologically based PK modeling and also population balance‐based equation solving for generation of absorption profiles throughout the gastrointestinal tract of different solid forms or formulation principles.
As a consequence of introducing rational developability criteria for selection (which is very much in the spirit of QbD), the classical flow of development sequences might need to be rearranged. Frontloading of certain key CMC activities will allow getting a better overall understanding of limitations and help avoiding long‐term manufacturing issues.
1.4.2 The Solid State at the Interface of Drug Substance and Drug Product
The majority of DPs (formulated drug substances) are administered as oral dosage forms, and by far, the most popular oral dosage forms are tablets and other solid forms such as capsules. Drugs for parenteral application are also often stored as solids (mainly as lyophilized products) and dissolved just before use since, in general, the chemical stability of a molecule in the solid form is much higher than in solution. Drugs administered by inhalation have become more and more popular, and dry powder inhalers are now commonly in use. It is, therefore, evident that the solid form of the DS and the selected excipients have a strong impact on the properties of the formulated drug. Even if the envisaged market form of the drug is a solution, information about the solid‐state properties of the DS is still necessary [53]. If different forms have a significantly different solubility, it may be possible to unintentionally create a supersaturated solution with respect to the least soluble form by creating a concentrated solution of a metastable form.
When discussing solid‐state development and polymorphism in the context of pharmaceutical development, it has to be pointed out that solid form selection and polymorphism should not be a tick box exercise performed in an isolated way. Although the active molecule is the primary focus and interest of chemists, it is the solid material obtained that will define many of the parameters influencing the absorption of the active molecule from a DP. Careful examination of available options will possibly allow tuning solid‐state properties by, e.g. salt [30] or co‐crystal [31] formation. At the end of the development chain is the marketed medicine. Because a solid oral dosage form is desired in most cases, the DS physicochemical properties will influence many of the subsequent manufacturing processes. The M3 mnemonic (Molecules–Materials–Medicines) [54] nicely brings it straight to the point; pharmaceutical development needs a holistic approach: chemical development – solid‐state development – DP development. These three disciplines are tightly interconnected and have the same goal of making products of the highest standard with respect to quality, safety, and efficacy.
For a defined active molecule, the F3 mnemonic (Form–Formation–Formulation) also nicely describes the interconnectivity of development disciplines (Figure 1.3). The molecular arrangement in a crystal lattice, governed by thermodynamics, will define the polymorphic form (i.e. the Form), that will exhibit a natural habit. The formation of the material, which is governed by kinetics (i.e. the processes of crystallization, isolation, and drying), will define the habit and size of singular particles. Singular particles will express surfaces, and these surfaces, which are the boundary of the molecules to a different environment, will define many of the physicochemical properties and behaviors [55–57]. Many particles together will yield a powder, and properties of powders can be invariant or variant. Properties that are invariant are thermodynamic values such as melting point or solubility. These are defined by the polymorph. Variant properties of a powder are, e.g. particle size distribution, flow properties, cohesion, and dissolution rate [58, 59]. It is a DS powder that will be finally used for making a DP. Pharmaceutical unit operations such as powder blending, dry or wet granulation, and ultimately tableting will, therefore, depend on the properties of the powder [57, 60, 61]. Properties such as melting point and mechanical properties such as brittleness or ductility, particle size, surface energy, etc., will influence the tabletability, compactability, and compressibility of the powders. It is clear that the appropriate selection of excipients as a function of dose/drug load will help to mitigate the influences of the DS powder properties. The selection of appropriate formulation processes as a function of DS powder properties was recently described in the “manufacturing classification system” (MCS) [62]. The MCS is intended as a tool for pharmaceutical scientists to rank the feasibility of different processing routes for the manufacturer of oral solid dosage forms, based on the selected properties of the drug substance and the needs of the formulation.
Figure 1.3 The interplay of form and formation resulting in powders that are further processed to the DP.
1.4.3 Biopharmaceutics and Bioavailability of Solids
An issue that has to be addressed for every orally taken DP, and which is closely related to its solid‐state properties, is whether solubility and dissolution rate are sufficiently high. This leads to the question what the minimal acceptable solubility and dissolution rates are.
An absorption profile of a drug from the gastrointestinal tract essentially depends on three factors: solubility, permeability, and dose [63]
