Oral Formulation Roadmap from Early Drug Discovery to Development E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 463

Veröffentlichungsjahr: 2017

Beschreibung

Detailing formulation approaches by stage of discovery to early development, this book gives a "playbook" of practical and efficient strategies to formulate drug candidates with the least chance of failing in clinical development. * Comes from contributing authors with experience developing formulations on the frontlines of the pharmaceutical industry * Focuses on pre (or non-) clinical and early stage development, the phases where most compounds are used in drug research * Features case studies to illustrate practical challenges and solutions in formulation selection * Covers regulatory filing, drug metabolism and physical and chemical properties, toxicology formulation, biopharmaceutics classification system (BCS), screening approaches, early stage clinical formulation development, and outsourcing

Leseprobe

Table of Contents

Cover

Title Page

List of Contributors

Preface

1 Introduction

1.1 Overcoming Challenges in Big Pharma and Evolution of Start‐Up Companies

1.2 Overview of Activities Involved in Current Drug Discovery and Development

1.3 Value of the Right Formulation at the Right Time

References

2 Lead Identification/Optimization

2.1 Introduction

2.2 Early Characterization of Compounds

2.3 Formulation Approaches in Drug Discovery

2.4 Conclusion

References

3 Oral Drug Formulation Development in Pharmaceutical Lead Selection Stage

3.1 Introduction

3.2 Formulation Considerations in Lead Selection Stage

3.3 Formulation Supporting Toxicology Studies

3.4 Techniques of Oral Administration

3.5 Concluding Remarks

References

4 Bridging End of Discovery to Regulatory Filing

4.1 Introduction

4.2 Formulation Selection for GLP Nonclinical Safety Studies

4.3 Dose Selection and Test Article Requirements for Nonclinical Toxicology Studies

4.4 Phase‐Appropriate Nonclinical Formulation Strategy

4.5 Methods of Test Article Administration

4.6 Formulation Tolerability Across Species and Study Designs

4.7 The Relationship between Clinical and Nonclinical Formulations

4.8 Conclusions

References

5 Planning the First Clinical Trials with Clinical Manufacturing Organization (CMO)

5.1 Reasons for Outsourcing

5.2 Considerations for Outsourcing

5.3 Timing for CMO Selection

5.4 Pre‐CMO Selection Background Information/Preparation

5.5 Selection of CMO

5.6 Final Thoughts

Abbreviations

References

6 Formulation Strategies for High Dose Toxicology Studies

6.1 Introduction

6.2 General

6.3 Nanosuspension Formulations

6.4 Amorphous Solid Dispersion Formulations

6.5 Conclusion

References

7 Formulation, Analytical, and Regulatory Strategies for First‐in‐Human Clinical Trials

7.1 Introduction

7.2 Planning and Executing the FIH Trial

7.3 Formulation Development

7.4 Analytical Development

7.5 Information Needed in Preparation of Regulatory Submission

7.6 Conclusions

Abbreviations

Acknowledgments

References

Index

End User License Agreement

List of Tables

Chapter 01

Table 1.1 Activity definition from discovery to preclinical development.

Chapter 02

Table 2.1 Differences between PK and PD studies.

Table 2.2 PK of PF‐04191834 aqueous dispersion and nanosuspension after administration of 100 mg dose to pentagastrin‐treated dogs (

n

 = 5).

Chapter 03

Table 3.1 Potential routes of administration.

Table 3.2 Normal pH range for human physiologic fluids.

Table 3.3 Test subject characteristics that can influence GI tract absorption.

Table 3.4 Selected factors that may affect chemical distribution to various tissues.

Table 3.5 Chemical characteristics of a drug that may influence absorption.

Table 3.6 Non‐active formulation components in drug candidate oral delivery.

Table 3.7 Basic principles to be observed in developing and preparing test material formulations.

Table 3.8 General guidelines for maximum dose volumes by route.

Table 3.9 Limit doses for toxicological studies.

Table 3.10 US Code of Federal Register references to excipients.

Table 3.11 Standardized total compound requirements for rodent diet studies.

Chapter 04

Table 4.1 Formulation requirements for nonclinical safety studies.

Table 4.2 Typical safety studies to support clinical trials and registration of an oral small molecule NCE.

Table 4.3 Example test article requirements for GLP general toxicology studies.

Table 4.4 Considerations for oral gavage across standard nonclinical species.

Chapter 05

Table 5.1 Hygroscopicity classification.

Table 5.2 Evaluation of flow properties.

Table 5.3 Example of cost breakdown.

Table 5.4 Comparison of performance attributes of CMOs.

Chapter 06

Table 6.1 Physicochemical properties of compound A.

Table 6.2 Oral exposure of compound B in rat after 150 mg/kg dose.

Table 6.3 Physicochemical properties of compound C.

Table 6.4 Properties of spray dried amorphous solid dispersion of compound C.

Table 6.5 Oral exposure of compound C in rats after 100 mg/kg dose.

Table 6.6 Compositions of solubilized amorphous solid dispersion formulations of compound C.

Table 6.7 Oral exposure for the selected formulation of compound C in fed dogs: The formulation consisted of an amorphous solid dispersion consisting of 30% drug load of compound C in HPMCP in a dosing vehicle containing 10% polysorbate 80 in 0.5% methylcellulose at pH 4.

Chapter 07

Table 7.1 Parallel single ascending dose design with a linear dose escalation.

Table 7.2 Standard crossover design with a linear dose escalation.

Table 7.3 Interlocking cohort’s crossover design with a linear dose escalation.

Table 7.4 Parallel multiple dose design with a linear dose escalation.

Table 7.5 Comparison of the merits and demerits of fit‐for‐purpose and commercial approaches.

Table 7.6 The dosage strengths, dose ranges, and number of units used within 10 reported single dose (SD) FIH studies between 1995 and 2014 (Merck Sharp & Dohme Ltd, Unpublished research).

Table 7.7 Pros and cons of the various formulations available for use in FIH studies.

Table 7.8 Overview of analytical activities typically performed during development and clinical manufacture of FFP formulations.

Table 7.9 Examples of first‐in‐human/phase I analytical method validation tests and requirements.

Table 7.10 Summary of analytical testing performed on solid and liquid FIH formulations.

Table 7.11 Example documentation to be submitted to the MHRA for CTA authorization for an IMPD.

Table 7.12 Summary of IND content for submission to FDA (FDA, 1995).

Table 7.13 Format and content of the Common Technical Document Module 3: Drug Substance.

Table 7.14 Format and content of the Common Technical Document Module 3: Drug Product.

Table 7.15 Example of a drug substance stability protocol.

Table 7.16 Drug product composition.

List of Illustrations

Chapter 02

Figure 2.1 Precipitation of amorphous form resulting in over prediction of solubility.

Figure 2.2 Comparison of solubility values obtained from kinetic and pseudo‐kinetic solubility screens.

Figure 2.3 Schematic showing absorption routes for a compound.

Figure 2.4 Typical setup for permeability assay.

Figure 2.5 Flowchart to guide IV formulation for preclinical

in vivo

studies.

Figure 2.6 Flowchart to guide oral formulation for preclinical

in vivo

studies.

Figure 2.7 Process flow description for bench‐top nanosizing method.

Figure 2.8 Bench‐top equipment and impellers used to nanosize API for preclinical formulations.

Figure 2.9 Particle size reduction of PF‐04191834 after wet‐bead milling with bench‐top equipment.

Figure 2.10 Emulsion template structure.

Figure 2.11 PF‐04191834 nanoparticles produced by emulsion templating (IOTA Contrasol™ technology).

Chapter 03

Figure 3.1 The magic bullet concept.

Figure 3.2 Evolution of formulations through phase 1.

Figure 3.3 Path of drugs through the body after absorption by one of the three routes of administration.

Figure 3.4 Three different systemic absorption curves.

Figure 3.5 Dose–response curve spectrum (objective is to maximize the range of the anticipated (desired) effect zone).

Chapter 04

Figure 4.1 Phase‐appropriate formulation strategy. As a program progresses from lead optimization to clinical and eventually registration‐enabling studies, formulation for

in vivo

studies should evolve from grossly well‐tolerated formulations with some biological effects to fully qualified GLP formulations with no such effects. Early lead optimization or pilot toxicology studies can utilize formulations with minor biological effects because of the limited safety endpoints and short duration of dosing. However, as the program matures, the formulation options become more limited, generally resulting in simple suspension formulations being used for chronic or carcinogenicity studies.

Chapter 05

Figure 5.1 Selection criteria from 2014 Annual Outsourcing Survey.

Figure 5.2 CMO selection steps.

Chapter 06

Figure 6.1 Selection of a stabilizer for crystalline nanosuspensions of compound A.

Figure 6.2 Visual heat map of particle sizes following acoustic mixing of a sample of naproxen with varying polymer and surfactant excipients over time, where green indicates small nanoparticles, red indicates larger nanoparticles, and black indicates lack of stable nanoparticles.

Figure 6.3 (a) Particle size distribution for the nanometer‐size and micron‐size batches of compound A and (b) exposures achieved for the two batches in the particle size effect study when dosed

in vivo

in a mouse model.

Figure 6.4 AUC versus dose plot for compound A administered in GLP toxicology studies in a mouse model.

Figure 6.5 Solubility in FaSSIF of high‐throughput amorphous solid dispersion formulation screening of a variety of polymers and drug loadings.

Figure 6.6 (a) MiMBA prediction in rats at 10 mg/kg and (b) MiMBA prediction in dogs at 10 mg/kg. The particle size was set to be 20 µm initially, 5 µm post jet‐milling, and 200 nm post nanomilling for the simulation. The two scenarios of solubility improvement at 10‐ and 50‐fold were simulated.

Figure 6.7 Dissolution profile of compound C from three solubilizing‐enabled formulations.

Chapter 07

Figure 7.1 Major stages of the drug development process (FDA, 2015).

Figure 7.2 Route map showing the major processes from NCE selection to FIH trial.

Figure 7.3 The four main designs utilized for dose escalation in FIH clinical trials between 1995 and 2004.

Figure 7.4 A pyramid diagram to show the three types of blinding designs.

Figure 7.5 3 + 3 trial design. Each cohort contains three subjects and dose is escalated until two DLTs are observed.

RD

 recommended dose for later phase clinical trials.

ATD

accelerated titration design. Upward arrows represent intra‐patient dose escalation.

Figure 7.6 An example concentration–time graph showing

C

max

,

T

max

, and AUC.

Figure 7.7 Biopharmaceutics Classification System (BCS).

Figure 7.8 The Common Technical Document (CTD) triangle. The CTD is organized into five modules. Module 1 is region specific and modules 2–5 are intended to be common for all regions. A summary of the CMC information is contained within quality of overall summary Module 2, and more detailed information can be found within quality Module 3.

Figure 7.9 Flow diagram describing the manufacturing process for the drug product shown in Table 7.15.

Guide

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Oral Formulation Roadmap from Early Drug Discovery to Development

Edited by Elizabeth Kwong

This edition first published 2017© 2017 John Wiley & Sons, Inc

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The right of Elizabeth Kwong to be identified as the Editor of this work and has been asserted in accordance with law.

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Library of Congress Cataloging‐in‐Publication Data

Names: Kwong, Elizabeth, 1954– editor.Title: Oral formulation roadmap from early drug discovery to development / edited by Elizabeth Kwong.Description: Hoboken, NJ : John Wiley & Sons Inc., 2017. | Includes bibliographical references and index.Identifiers: LCCN 2016045904 | ISBN 9781118907337 (cloth) | ISBN 9781118907900 (Adobe PDF) | ISBN 9781118907870 (epub)Subjects: | MESH: Drug Discovery | Chemistry, Pharmaceutical–methods | Clinical Trials as Topic | Dosage Forms | Administratoin, OralClassification: LCC RS420 | NLM QV 745 | DDC 615.1/9–dc23LC record available at https://lccn.loc.gov/2016045904

Cover design by Wiley.Cover image: © annedde/Gettyimage and Steven Wright/Shutterstock.

List of Contributors

Steven Booth Merck Sharpe & Dohme, Hoddesdon, Hertfordshire, UK

Gerard Byrne Merck Sharpe & Dohme, Hoddesdon, Hertfordshire, UK

Lorenzo Capretto Merck Sharpe & Dohme, Hoddesdon, Hertfordshire, UK

Pierre Daublain Discovery Pharmaceutical Sciences, Merck Research Laboratories, Boston, MA, USA

Lee Dowden Merck Sharpe & Dohme, Hoddesdon, Hertfordshire, UK

Kung‐I Feng Discovery Pharmaceutical Sciences, Merck Research Laboratories, Kenilworth, NJ, USA

Shayne Cox Gad Gad Consulting Services, Cary, NC, USA

Mengwei Hu Discovery Pharmaceutical Sciences, Merck Research Laboratories, Kenilworth, NJ, USA

Elizabeth Kwong Kwong Eureka Solutions, Montreal, Quebec, Canada

Dennis H. Leung Small Molecule Pharmaceutical Sciences, Genentech, Inc., South San Francisco, CA, USA

Mark McAllister Drug Products Design, Pfizer Ltd., Sandwich, UK

Caroline McGregor Merck Research Laboratories, Kenilworth, NJ, USA

Evan A. Thackaberry Genentech, Inc., Safety Assessment, South San Francisco, CA, USA

Sarah Trenfield Merck Sharpe & Dohme, Hoddesdon, Hertfordshire, UK

Mei Wong Drug Products Design, Pfizer Ltd., Sandwich, UK

Preface

The discovery and development of new drugs is a very complex machine. Despite increasing investments in research and development, the number of new drug approvals has not increased, while the attrition rate of new drug candidates has increased. Many of these challenges are due to failure to properly identify formulations that are translatable from preclinical to the clinic due to lack of effective predictions of therapeutic and toxicological responses in the preclinical stages. Moreover, efforts spent to integrate the formulation scientists in the early discovery that leads to the lead candidate selection had been disappointing. Most of the time, the lack of understanding of the interplay of the physiological system to the formulation contributed to the failure to integrate the right expertise at the right time, which leads to poor clinical successes. The lack of collaboration and proper integration between the formulation and discovery scientists is the root cause of most of the failure in the clinic. Lastly, the understanding of regulatory requirements for formulations also can add to the burden of the timeline and cost of bringing a drug candidate forward.

This book describes and explains key factors that will help determine the types of formulation needed at the different stages of discovery. The considerations of limited amount of API in early stages to the use of the formulation to determine key efficacious or toxicological end point that will not interfere with readouts will be discussed. The formulation selection stage‐dependent approach will be detailed up to the planning for the regulatory filing. The interplay of drug metabolism, absorption, and physicochemical properties of the active will be laid out to help understand when a formulation can be improved and when a different lead candidate should be selected. Current formulation approaches based on the biopharmaceutics classification system (BCS) of the lead will be explained. The book will also focus on the relationships between various disciplines like physical chemistry, analytical chemistry, biology, DMPK, toxicology, and medicinal chemistry in determining the appropriate formulation to deliver the candidate in different forms. API sparing approaches including in vitro and fit‐for‐purpose formulation to support first‐in‐human study will also be covered in the book. Partnership considerations with contract manufacturing organization (CMO) will also be described and shared to increase the probability of meeting tight timelines and to ensure the proper selection of formulation to support an early stage development and how this can impact the late stage development of the drug candidate. Introduction of current formulation approaches including enabling formulations such as solid dispersions used in the industry will widen partnership with emerging innovators and sponsors, making it possible for the otherwise difficult drug candidate to be studied in the clinic.

This book will be the first in detailing the formulation approaches by stage of discovery to early development to help scientists of different disciplines. Practical challenges and solutions will be discussed. The content of the book will guide the proper use of resources to lead scientists to generate the proper database that can help in quick decision‐making. The target audience for the book will be drug discovery scientists including medicinal chemists, leaders in pharmaceutical industry (big pharma or start‐up companies), and academics who are interested in bringing a potential drug candidate to the clinic. The book will provide real case studies of challenging candidates that allows readers to understand the importance of formulation to their cases. My numerous years (>23 years) working in big pharmaceutical companies, especially the intimate involvement with discovery in the last 15 years of my career and my recent interaction with small‐ and medium‐sized pharmaceutical companies, allowed me to identify collaborators for this book to address the real problems and solutions in drug discovery related to all types of formulations.

The editor wishes to thank all the authors for their expertise in their respective sections and their patience during the revision procedures that were necessary to arrive at this juncture of delivering a well‐outlined roadmap.

July 2016                                                                                                                                                                               Elizabeth Kwong

1Introduction

Elizabeth Kwong

Kwong Eureka Solutions, Montreal, Quebec, Canada

1.1 Overcoming Challenges in Big Pharma and Evolution of Start‐Up Companies

1.2 Overview of Activities Involved in Current Drug Discovery and Development

1.3 Value of the Right Formulation at the Right Time

References

1.1 Overcoming Challenges in Big Pharma and Evolution of Start‐Up Companies

The discovery and development of new drugs is a very complex process. No matter how you implement Lean Six Sigma Black Belt or in‐depth data mining into the process, cost and success rate of commercializing drugs had not improved. It was estimated that it takes at least 10 years for a drug to make the journey from discovery to consumer at an average cost of $5 billion (Herper, 2013). Another study conducted by BIO and BioMedTracker (Hay et al., 2011), which collects data on drugs in development, had reviewed more than 4000 drugs from small and large companies that indicated that overall success rate for drugs moving from early stage phase I clinical trials to FDA approval is about 1 in 10, down from 1 in 6 seen in reports earlier. Despite increasing investments in research and development, the number of new drug approvals has not increased, while the attrition rate of new drug candidates has increased.

Recent publication in Fortune entitled “Big Pharma Innovation in Small Places” (Alsever, 2016) quoted several big pharma executives as to the current nature of big pharmaceutical companies where the focus of R&D is diminished to sorting out changes in the company and reprioritizing programs. Furthermore, with investor money flooding in and shift of drug pipelines from internal R&D to start‐ups licensing opportunities, big pharma is acquiring small companies at faster pace than before. Small start‐ups are now becoming the “new” innovative machines, which offer the high risk–high reward paradigm. According to surveys, last year, 64% of the approved phase I studies originated at a smaller start‐ups.

1.2 Overview of Activities Involved in Current Drug Discovery and Development

There had been many surveys that revealed the cause of attrition of molecule in clinical development through the years. The major factors for discontinuation of clinical candidates are lack of efficacy (~30%) and toxicity (~30%). Kola & Landis (2004) further revealed that a 10% drop in attrition in 2000 was partly due to advancement in formulation technologies. Furthermore with increase in molecular obesity in drug candidates in recent years, majority of new drug development is poorly water soluble (Hann, 2011). About 40% of drugs with market approval and nearly 70–90% of molecule in discovery are poorly water soluble, which can lead to low bioavailability with conventional formulations (Kalepu & Nekkanti, 2015). With the introduction of various drug delivery technologies, numerous drugs associated with poor solubility and low bioavailability have been formulated into successful drug products. In fact, recently an increase in NDA file under 505(b)(2) is gaining more importance. New dosage forms with improved solubility and enhanced bioavailability such as prodrugs/active metabolite of drug and reformulation of poorly absorbed drugs using new technologies are turning into lucrative business. According to the Q&A with Ken Phelps, president of Camargo Pharmaceutical Services, which provides services for drug development for 505(b)(2) applications, approximately 20% of new drug approved in 2006 is through 505(b)(2) process. By 2008 more than half of new drug approval was based on 505(b)(2) process (Phelps, 2013).

Poor solubility of development candidates can limit drug concentration at the biological target site, which can lead to loss of therapeutic effect. Increasing the dose can overcome this lack of therapeutic effect but can lead to high variability in absorption, which can be detrimental to the safety and efficacy profile. For these reasons, solubility‐enhancement technologies are being used increasingly in the pharmaceutical field. A formulation scientist’s approach to solubility enhancement of a poorly water‐soluble drug can vary. Often, physicochemical characterization, solid‐state modifications, nonconventional formulation technologies, and enabling formulations are often utilized. There are numerous literature resources available to provide guidance toward formulation development from discovery to development of development candidates; however, a single reference where formulation approaches are described in each stage is lacking. This book describes and explains key factors that will help determine the types of formulation needed at the different stages of discovery. The considerations of limited amount of API in early stages to the use of the formulation to determine key efficacious or toxicological end point that will not interfere with readouts will be discussed. The formulation selection stage‐dependent approach will be detailed up to the planning for the regulatory filing. The interplay of drug metabolism, absorption, and physicochemical properties of the active will be laid out to help understand when a formulation can be improved and when a different lead candidate should be selected. Current formulation approaches based on the biopharmaceutics classification system (BCS) of the lead will be explained. The book will also focus on the relationships between various disciplines like physical chemistry, analytical chemistry, biology, DMPK, toxicology, and medicinal chemistry in determining the appropriate formulation to deliver the candidate in different forms. API sparing approaches including fit for purpose formulation to get candidates into development will also be covered in the book. Each stage of formulation (see Table 1.1) development has its goals, degree of complexity, and increasing availability of information, which ultimately leads to candidate that will have properties that can be administered in humans.

Table 1.1 Activity definition from discovery to preclinical development.

Standardized solutions for

in vitro

HTS and

in vivo

PK screen

No vehicle screen

Usually contains DMSO or other standardized cosolvent vehicle (such as PEG/EtOH), low dose PK with IV/oral for %F

Dose range finding to identify exposure multiples

Resort to vehicle screen decision tree

a

,

b

,

c

,

d

Goal of formulation selection are:

Vehicles do not have any biological adverse effect

Achieve exposure at the highest toxicological dose

Can reach up to 2 g/kg

Key is to identify adverse effects

Vehicle identified and dose range identified for GLP tox

Repeat preparation of vehicle using optimized API

Characterize physical properties of API in vehicle

Meet GLP requirements

Pharmacology studies—needed a sustained plasma level use of Alzet Osmotic pumps

e

PK–PD studies—use solution at low dose and suspension at high dose to assess relationship

CTM development—based on physical properties, such as flow, stability, particle size, and BCS, bioavailability

a Higgins et al. (2012).

b Maas et al. (2007).

c Li & Zhao (2007).

d Palucki et al. (2010).

e Neervannan (2006).

1.3 Value of the Right Formulation at the Right Time

Many of the discovery challenges are due to failure to properly identify formulations that are translatable from preclinical to clinical due to lack of effective predictions of therapeutic and toxicological responses in the preclinical stages. Moreover, efforts spent to integrate the formulation scientists in the early discovery that leads to the lead candidate selection had been disappointing. Most of the time, the lack of understanding of the interplay of the physiological system and physicochemical properties of the molecule to the drug delivery system contributed to the failure to integrate the right expertise at the right time, which leads to poor clinical successes. The lack of collaboration and proper integration between the formulation and discovery scientists is the root cause of most of the failure in the clinic. Lastly, the understanding of regulatory requirements for formulations also can add to the burden of the timeline and cost of bringing a drug candidate forward.

Although discovery starts off with the structure‐based drug design, a better design of drug should be an understanding of how the biological effect is influenced by physicochemical properties, PK of the drug, and pharmaceutical delivery system. Optimization of the API via salt formation or co‐crystal and physical changes such as particle size reduction through milling or formation of amorphous dispersions are often employed to improve oral bioavailability of insoluble compounds. These approaches can be applied even at the lead identification if a candidate is deemed to show some potential. Various available formulations are discussed for early discovery in Chapter 2. This chapter will explain which formulation will be suitable at what stage and what features of the drug might suggest one technology over another. Chapters 3 and 4 deal with the different toxicology studies in relations to what formulation will be suitable. Following the development of suitable formulation to deliver required exposure in the early stage of discovery, this will then provide adequate safety assessment and risk of the candidate before proceeding to the more expensive clinical trials. Following this stage, Chapter 7 will cover the formulation technologies that will be scalable to support the first clinical trial study.

Selecting a suitable formulation for your drug candidate can be complicated. Publications on formulation options for poorly soluble drugs are widespread. Each publication would have its approaches with decision trees and had shown proof of success that suits the specific pharmaceutical support system. In other words, taking this approach to another company with a different support function may not work. In my years of experience, to properly select the “right” formulation for a specific compound will still need input from a formulation scientist. This will be someone who poses the breadth of knowledge that can span from understanding of the physiological environment, pharmacology, and physicochemical properties of the molecule that will be intended for development. First to note here is the dose that will be required to be formulated, since solubilization techniques will have their limitation if the doses needed will be high. For example, at the lead optimization stage where safety of the candidate will need to be assessed, high doses are usually expected, and no means of solubilization can be possible that uses excipients that are inert unless your candidate is truly water soluble, which is very rare. It is also worth noting that the term “solubilization” is for the candidate to be soluble in the vehicle or mixture, and this does not include the fact that once this formulation is dosed, solubilization in the physiological environment may pose another hurdle that still can limit the absorption of the drug. This then leads to the question of what is the solubility of this molecule in the physiological milieu? One has to consider the micro‐environment that may not be visible and static as we would envision during an in vitro test. For example, size reduction technology, which is also one of the solubilization techniques, is used to improve bioavailability. This technology is easy to achieve but may not be applicable to a large proportion of poorly soluble compounds. Evaluation of agglomeration potential of the molecule, understanding of the interplay of the excipients with the physical environment, and stability of the particle, molecule, and crystalline form are required. Another tool is the use of lipid technologies, which uses lipids as primary ingredient to deliver the water insoluble molecule. Lipid formulations are more complex and can produce micelles and microemulsions and will need a formulator to understand how each component of the mixture can ensure the target performance of the molecule from the in vitro to the in vivo environment. Most of the ingredient may be limited by the amount that can be administered in a preclinical study. At the same time, getting the number of additives together can result in a very viscous vehicle that may itself produce some challenge in a multiple day dosing during a toxicology study. Furthermore, use of such formulation for clinical supplies poses other challenges including use of soft gelatin capsule that can be in an appropriate size for dosing in patients and can be costly.

An important strategy to consider for your formulation selection is simplicity. Try to understand the criticality of solubilization to permeability/metabolism. In some cases where the molecule is poorly soluble, the oral absorption is still acceptable when given a suspension where the only solubilization was the use of a low concentration of surfactant as a wetting agent aid. This approach can provide a PK profile that will have less Cmax to Ctrough ratio and can mitigate some of the adverse effects related to high plasma levels. At the same time this may provide sustain release if solubilization of the molecule is slow and the absorption window is wide. To manage the reproducibility of the PK profile, it will be important to properly characterize the suspension including the form and particle size of the compound in suspension. Such formulation approach in preclinical can also translate into a simple blend in a capsule that can be used in clinical formulation. On the other hand, if the molecule is being metabolized or transported at specific dose or species, formulation may not provide the solution even with the help of permeability enhancers. This is part of the reason why optimal drug‐like properties are significant in drug discovery to minimize the complexity of downstream activities.

This book will be the first in detailing the formulation approaches by stage of discovery to early development to help scientists of different disciplines. Practical challenges and solutions will be discussed. The content of the book will guide the proper use of resources to lead scientists to generate the proper database that can help in quick decision making. The target audience for the book will be drug discovery scientists including medicinal chemists, leaders in pharmaceutical industry (big pharma or start‐up companies), and academics who are interested in bringing a potential drug candidate to the clinic.

Partnership considerations with contract manufacturing organization (CMO) will also be described and shared to increase the probability of meeting tight timelines and to ensure the proper selection of formulation to support an early stage development and how this can impact the late stage development of the drug candidate. Introduction of current formulation approaches including enabling formulations such as solid dispersions used in the industry will widen partnership with emerging innovators and sponsors, making it possible for the otherwise difficult drug candidate to be studied in the clinic.

References

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2Lead Identification/Optimization

Mei Wong and Mark McAllister

Drug Products Design, Pfizer Ltd., Sandwich, UK

2.1 Introduction

2.2 Early Characterization of Compounds

2.2.1 Preformulation

2.2.1.1 Solubility

2.2.1.2 p

K

a

2.2.1.3 Lipophilicity

2.2.1.4 Permeability

2.3 Formulation Approaches in Drug Discovery

2.3.1 PK/PD Studies of Lead Compounds: Formulating for Preclinical Development

2.4 Conclusion

References

2.1 Introduction

Over the last two decades, the introduction of high‐throughput screening (HTS) and combinatorial chemistry has changed the drug discovery process by enabling the rapid evaluation of large number of compounds against targets of interest (Bajorath, 2002; Hefti, 2008; Hughes et al., 2011). In the past, selection of compounds for progression (lead identification) focused mainly on affinity and selectivity. However, it has since been recognized that the physicochemical properties (such as solubility and lipophilicity) of a compound play a significant role in whether the compound progresses to be a successful drug candidate. To ensure that leads selected for progression have the right absorption, distribution, metabolism, and excretion (ADME) properties, rule‐based systems such as the “rule of five” have been used to predict the drug‐likeness of a compound and guide the selection of compounds for progression (Lipinski et al., 1997).The “rule of five” was developed based on a review of compounds that have successfully progressed into clinical studies and stipulates that for an orally active compound to be successful; it should not violate more than one of the following criteria:

No more than five hydrogen bond donors (the total number of nitrogen–hydrogen and oxygen–hydrogen bonds)

No more than 10 hydrogen bond acceptors (all nitrogen or oxygen atoms)

Molecular weight of less than 500

Octanol–water partition coefficient (log

P

) not greater than five

Despite the implementation of “rule of five” type filters to lead selection, a relatively high proportion of drugs entering clinical studies fail to reach the market (Hann, 2011). As a result, alternative methods such as “quantitative estimate of drug‐likeness” (QED) have been introduced (Bickerton et al., 2012). QED measured drug‐likeness based on the concept of desirability and enabled values for multiple molecular properties to be combined into a single measure of compound quality using a desirability function.

Once the leads are selected, the optimization process starts whereby the weaknesses of the compound are improved, while maintaining the favorable properties of the compound (Hughes et al., 2011) such that the compound entering clinical studies has a good balance of in vitro properties and ADME properties.

2.2 Early Characterization of Compounds

During this stage, preformulation data generated on the leads are used to identify developability risks and guide molecular structure modifications. The key challenge for the formulation scientist at this stage is the limited information available on the compound and limited bulk (if any) available of experimentation. Therefore, during the early stages of lead identification and lead optimization, computational modeling and HTS play a crucial role in assessing the physicochemical and pharmaceutical properties of the compound. As the compound progresses through to the later stages of lead optimization and larger quantities of material are available, focused experimentation can be used to answer specific questions about the compound as well as improve the quality of the data generated.

2.2.1 Preformulation

High oral bioavailability is often an important goal for drug development. Therefore, it is important to gain sufficient understanding of the properties that can limit oral bioavailability. In order to obtain an accurate assessment of the biopharmaceutical properties of a compound, the key physicochemical parameters determined during the preformulation stage are solubility, lipophilicity, pKa, and permeability.

2.2.1.1 Solubility

For orally absorbed drugs, the compound must be dissolved and in solution for absorption to occur. With the increasing number of compounds with poor solubility, solubility‐limited absorption has become one of the main reasons for poor bioavailability in the clinic (Di et al., 2012). Solubility‐limited absorption is even more of a problem during the preclinical stage for assessment of safety issues, especially where high doses are required. As a result, the importance of conducting solubility studies during the drug discovery stage is well recognized.

During the early stages of lead identification where solubility experimentation is not feasible due to the large numbers of compounds being screened and lack of material, computational models may be used for solubility prediction. These computational models range from simple models using semiempirical equations based on physicochemical properties such as logP and pKa to more complex models based on molecular properties such as molecular weight, polar surface area (PSA), and hydrogen‐bonding capacity. Although solubility predictions are useful, the accuracy of these models is variable and highly dependent on the training sets used.

Once material is available, experimentation can be conducted to more accurately determine the solubility of a compound. A range of different solubility assays can be conducted depending on the development stage of the compound, amount of material available for experimentation, and the purpose of the data generated. For example, high‐throughput (HT) kinetic solubility screens can be used to help compound selection, while equilibrium solubility experiments can be used to help biopharmaceutical predictions and guide formulation development.

2.2.1.1.1 Kinetic Solubility

Kinetic solubility assays are typically conducted during lead identification as the assays use stock solutions (e.g., DMSO stock solution), which are readily available at this stage. In addition, the assay uses minimal material, and the format of the assay readily lends itself to automation and integration into the HTS process (Lipinski et al., 2001).

A typical kinetic solubility study would involve the addition of small volumes of stock solution to media to form a supersaturated solution. The solution is then incubated for a short period of time to allow precipitation of the compound. The amount of compound remaining in solution is then analyzed by UV or nephelometry (Avdeef and Testa, 2002; Kerns et al., 2008).

While kinetic solubility is an indicator as to whether a compound may have solubility issues, studies have shown that kinetic solubility tends to overestimate the actual solubility of a compound (Saal and Petereit, 2012; Sugano et al., 2006). This difference could be a result of several factors including the short incubation time and precipitation of an amorphous or metastable solid form (Figure 2.1).

Figure 2.1 Precipitation of amorphous form resulting in over prediction of solubility.

2.2.1.1.2 Equilibrium/Thermodynamic Solubility

Equilibrium or thermodynamic solubility of a compound is defined as the maximum concentration of a compound, which, at a defined temperature and pressure in a given solvent, is thermodynamically valid as long the solid phase exists in equilibrium with the solution phase (Murdande et al., 2011). While equilibrium solubility is considered the “gold standard” for determining the solubility of a compound, it is less commonly used in early lead identification due to the higher bulk and resource requirements as well as longer turnaround times.

Equilibrium solubility measurements are conducted by adding excess solid material to the buffer and shaking the resulting suspension for a predetermined temperature for a defined time (typically between 24 and 48 h). The remaining solid at the end of the experiment is removed, and the amount in solution is analyzed to obtain the equilibrium solubility value of the compound. As the solid form (crystallinity and polymorphic form) of the material may change during the experiment, characterization of the remaining solid is important when reviewing solubility data.

In addition to aqueous buffers, equilibrium solubility studies are frequently conducted using simulated gastric and intestinal fluid (SGF, FaSSIF, and FeSSIF). Solubility results from these studies are used as inputs into in silico models such as GastroPlus™ and Simcyp® to help predict in vivo performance of the compound.

2.2.1.1.3 Pseudo‐Kinetic Solubility

To bridge the gap between the kinetic and equilibrium solubility assays, scientists at Pfizer developed the “pseudo‐kinetic solubility” screen. Like the kinetic screen, the pseudo‐kinetic screen starts with pre‐dissolved compound and can be easily automated. However, the pseudo‐kinetic screen has a longer incubation time (20 h), and the screen plate was modified to enable information on the solid form to be obtained using polarized light microscopy (PLM) (Sugano et al., 2006).

Figure 2.2 compares the correlation between the solubility values obtained from the kinetic screen and pseudo‐kinetic screen against values obtained via equilibrium solubility studies.

Figure 2.2 Comparison of solubility values obtained from kinetic and pseudo‐kinetic solubility screens.

2.2.1.2 pKa

The acid–base dissociation constant (pKa) of a compound is used to understand the ionization state of a compound in solution at a particular pH. The pKa is important as it can influence the solubility, lipophilicity, and permeability of a molecule, especially when ionized at physiologically relevant pH of 2–8 (Manallack, 2007). A molecule in its charged state will show higher solubility than in its uncharged state but, conversely, will have lower permeability. In other words, the permeability and/or solubility of a compound can be altered by the introduction or modification of ionizable groups.

In early lead identification, software packages such as ACD/Labs can be used to predict pKa values of a compound. pKa values can also be determined experimentally using either titration (potentiometric or UV spectral detection) or capillary electrophoresis (CE) (Wan et al., 2003).

2.2.1.3 Lipophilicity

The lipophilicity of a compound represents the affinity of the compound for oils, fats, and nonpolar solvents and is determined by either partition coefficient (logP) or distribution coefficient (logD) measurements using two nonmiscible solvents, typically n‐octanol and water. LogP values are the ratio of concentrations of unionized drug in the octanol–water system, while logD values are the ratio of concentrations of both unionized and ionized drug in the octanol–water system and are affected by the pH of the system. LogP/D measurements are usually conducted by adding dissolved compound into a flask containing both octanol and water and shaking the flask until equilibrium is achieved. The concentration of compound in each solvent is then quantified using an appropriate technique such as UV.

The marketed 96‐well format octanol–water shake flask method by Analiza, Inc (www.analiza.com) provides logD ranges of −3 to 4. Another common approach is the use of HPLC retention times in relation to a set of standards with known logD to predict an approximate logD for the compound of interest (Yamagami et al., 2002).

Furthermore, the lipophilicity of the compound influences the permeability of the compound and transport across the gastrointestinal tract (GIT) and blood–brain barrier (see Section 2.2.1.4). In addition, it can also be used during formulation development to help with selection of solubilizing formulations (e.g., use of self‐emulsifying drug delivery systems for compound with high logP/D).

2.2.1.4 Permeability

Following oral administration, compounds dissolved in gastrointestinal (GI) fluids have the potential to be absorbed via a variety of mechanisms that involves either passive diffusion or active transport (Figure 2.3). For the majority of drug compounds, the main route of absorption occurs via passive diffusion through the transcellular pathway. The transcellular diffusion rate is mainly determined by the rate of transport across the apical cell membrane and is controlled by the lipophilicity and ionization state of the compound.

Figure 2.3 Schematic showing absorption routes for a compound.

This interrelationship of pKa, logD/P, and pH of the absorption site in the GIT forms the basis of the pH‐partition theory (Shore et al., 1957). The theory states that transcellular diffusion of a drug molecule through the lipid bilayer of the intestinal membrane can only occur if the molecule is in its unionized state. Therefore, absorption of weakly basic drugs is favored in the small intestine where the pH is higher, and therefore, a larger proportion of unionized drug will be available for absorption. Conversely, absorption of weak acids will be favored in the stomach where pH is lower. However, in reality, the small intestine continues to be the main site of absorption for all drugs due to the larger surface area available for absorption compared with the stomach and colon (Hurst et al., 2007).

During early drug discovery, permeability estimations can be made using the PSA of a compound. Results from work by Palm et al. (1996, 1997) have shown that compounds with PSA < 60 Å2 show complete absorption, while compounds with PSA > 140 Å2 have unacceptably low absorption (Artursson and Bergström, 2004). More recently, studies looking at the use of surface activity profiling (relationship between surface activity and surface pressure of a drug solution) and surface tension on drug permeability were undertaken as part of the innovative tools for oral biopharmaceutics (OrBiTo) project (Bergström et al., 2014).

In vitro permeation studies can be conducted using cell monolayers (e.g., Caco‐2 or MDCK) or artificial membranes (e.g., parallel artificial membrane permeability assay (PAMPA)). Figure 2.4 shows the typical setup for the permeability assay. The dissolved compound is added to the apical chamber at the start of the experiment, and the apparent permeability (Papp) is determined using Equation 2.1:

(2.1)

where dQ/dt = permeability rate; A = surface area of membrane; and C0 = initial concentration in the apical chamber.

Figure 2.4 Typical setup for permeability assay.

Caco‐2 cell monolayers are most commonly used for permeability screening due to their morphological and functional similarity to the human intestine (Varma et al., 2004). The key disadvantage of Caco‐2 permeability is the intra‐ and interlab variability of Papp values due to variability in experimental conditions (e.g., pH and/or ionic conditions of the media, shaking rate) or cell culture conditions (Yamashita et al., 2000). Therefore, it is important that the Papp values must be used alongside reference values from internal standards.

Most Caco‐2 permeability experiments are conducted using either pH 6.5 or 7.4 in the apical chamber. As the degree of ionization can have a significant impact on permeability, it is important to consider the pKa of the compound alongside Papp values. For example, metoprolol has a Papp of 7.8 × 10−6 cm/s at pH 6.5, while at pH 7.4, the Papp increases to 39.7 × 10−6 cm/s.

2.3 Formulation Approaches in Drug Discovery

Formulation development during the early stages of drug discovery is often complicated by the limited availability of drug, which contributes to an incomplete physicochemical and biopharmaceutical profile. Solubility and permeability properties are often unfavorable and necessitate the use of approaches over and beyond simple solution or suspension formulations to achieve the required levels of exposure. Numerous literature reports (Chaubal, 2004; Li and Zhao, 2007; Maas et al., 2007; Niwa and Hashimoto, 2008; Saxena et al., 2009; Wilson, 2010) have described significant formulation efforts during the candidate‐profiling phase, but only a few publications describe comprehensive formulation strategies to support early discovery in vivo studies (Kwong et al., 2011). These studies can be classified into three main types: (i) pharmacokinetic (PK) study, (ii) pharmacodynamic (PD) study, and (iii) toxicokinetic/dose range finding studies to support toxicological studies (Shah and Agnihotri, 2011). These studies are carried out sequentially during the lead identification to lead optimization stages. PK studies are an essential first step to evaluate the fate of the drug after administration and to provide information on the ADME properties of a lead molecule or series. By contrast, PD studies evaluate the effect of drug on the body and are used to elucidate concentration drug activity relationships and to establish any correlation of PK to biological activity or efficacy. Toxicokinetic or dose range finding studies are performed to determine exposure/dose relationships and to develop an understanding of the maximal absorbable dose. These studies are followed by multiple dosing studies, which are used to establish the no observable effect level (NOEL) or the no observable adverse effect level (NOAEL) for a new chemical entity. The formulation strategies for toxicology studies will be discussed in a subsequent chapter of this book.

2.3.1 PK/PD Studies of Lead Compounds: Formulating for Preclinical Development

Throughout the early discovery phase, formulation expertise is required to enable PK and early biology studies in preclinical species to establish critical ADME parameters and proof of pharmacology for a lead series. As a molecule progresses through lead optimization into exploratory toxicology and then regulatory safety assessment studies, the need to develop effective formulations to deliver sufficient exposure is critical to the success of the program. The requirement to drive exposure in toxicology to levels that will provide adequate safety coverage for future clinical studies is often a considerable development hurdle to overcome. This spectrum of preclinical formulation activities is made even more difficult by the challenging physicochemical properties of typical lead candidate molecules. It is clear from experience across the industry that the exploration of novel biological target space and pharmacological mechanisms combined with the use of high‐throughput modern drug discovery approaches to yield highly potent and selective molecules has provided chemical substrate, which has become increasingly difficult to formulate due to poor molecular properties such as hydrophobicity and low aqueous solubility. The additional complexity associated with such substrate has forced the industry to apply formulation resource much earlier in the discovery process. Past practices such as “disperse and dose” (Maas et al., 2007) where discovery biologists, chemists, or drug metabolism scientists would formulate simple solutions and suspensions for screening PK or early PD studies have been largely superseded by the integration of candidate‐enabling formulation teams into the multidisciplinary discovery teams. This is evident from the number of publications from groups in major pharma companies with specific roles for discovery support, for example, Developability Assessment group at Novartis (Saxena et al., 2009), Research Formulation at Pfizer, Discovery Pharmaceutics at BMS (Chen et al., 2012), and Basic Pharmaceutical Sciences group at Merck (Palucki et al., 2010).

Some common challenges are encountered during preclinical formulation development for both PK and PD studies. Quantities of API are often limited (10–20 mg is not typical for formulation development), and quality of drug substance can be variable in terms of purity, particle size, and solid form attributes. Timelines are also compressed with discovery teams requiring formulations with a timeframe of days rather than weeks and certainly not months’ worth of notice. This of course can be tackled by efficient formulation development using miniaturized formulation technologies and standardized formulation protocols, but it does require the availability of physicochemical characterization data and a fit‐for‐purpose analytical method. There are also some key differences between PK and PD studies with regard to design and target parameters, which place different constraints on the formulation approach, which can be adopted. Generally, PD studies are more complex to deal with due to their longer duration, multiple dosing, and the need to avoid any biological activity associated with formulation excipients. Table 2.1 summarizes these and a number of additional differentiating aspects between PK and PD studies (Maas et al., 2007).

Table 2.1 Differences between PK and PD studies.

Source: Adapted from Maas et al. (2007).

PK studies

PD studies

Cassette dosing feasible

Cassette dosing not appropriate

Single administration

Often multiple or chronic administration required

PD effect of solvent can be acceptable

PD effects of solvents not acceptable

Normal, healthy animals used

Specialized or disease animal models used

Evaluation rapid

Evaluation complex and longer

No vehicle control

Vehicle control groups required

No requirement for PD evaluation

Parallel PK analysis often conducted

In vitro metabolism data (obtained from liver microsomes or hepatocytes from mouse, rat, dog, or human) (Asha and Vidyavathi, 2010; Naritomi et al., 2003; Obach et al., 1997; Parkinson et al., 2010) are a key component of the lead selection and optimization process. Compounds emerging from metabolic screens with limited predicted PK liability or those for which data