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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5329_Библиотеки_им_академика_М_И_Перельмана
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Figure 10.3 Timeline for generic IND enabling studies to support dosing in humans for 1 month.
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Figure 10.4 Timeline for IND enabling studies required for PPAR agonists to be dosed for >6 months in humans.
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GMP drug substance and product is not required to conduct animal pharmacology
and toxicology studies. However, prior to conducting GLP toxicology studies to
support an IND, a well-defined batch of drug substance synthesized by the final
process chemistry method is recommended. To accelerate the development of a
clinical candidate, a research batch of drug substance may be prepared under nonGMP conditions. This non-GMP batch can be used for preliminary stability as well as
initial toxicology studies. Concurrently, a GMP batch may be prepared for final
animal toxicology and human trials providing a faster development time to clinical
trials. The risk associated with this strategy is as follows:
1. GMP batch cannot contain any new impurities compared to the non-GMP batch.
2. GMP batch cannot contain greater levels of impurities than the non-GMP batch
tested in preclinical studies.
TABLE 10.2 Complete Set of Experiments for an IND Enabling Package (Rat and Dog
Assumed as Species for Toxicological Assessments)
1. Bioanalytical assay development and
validation
v. Reproductive toxicology (rat and
rabbit)
a. Rat d. Safety pharmacology
b. Dog i. Cardiovascular telemetry—dog
c. Human ii. Respiratory—rat
2. ADME iii. CNS effects—rat
a. Protein binding (rat, dog, human) 4. CMC
b. In vitro CYP inhibition (rat, dog,
human)
a. Process chemistry/final synthetic
route
c. In vitro CYP metabolism (rat, dog,
human)
b. Develop and validate drug substance
and product characterization
d. Plasma stability (rat, dog, human) c. Raw material accelerated stability
e. PK
i. Dose proportionality
d. GMP batch synthesis for drug
substance and product
ii. Multiple dose
iii. Radiolabeled PK/mass
balance (rat)
e. Drug substance and drug product ICH
stability
f. Develop clinical formulation
3. GLP safety and toxicology g. Synthesis of radiolabeled drug
a. Method validation of dosing solutions 5. Regulatory
b. In vitro toxicology a. Establish clinical development plan
i. HGPRT forward mutation b. Produce pre-IND meeting material
ii. Gene aberration c. Pre-IND meeting with FDA
iii. Ames d. Phase 1a clinical protocol
c. GLP in vivo toxicology including
toxicokinetics
e. Clinical Investigators Brochure
i. Escalating single dose in rat
ii. Escalating single dose in dog
iii. 4 week rat study including recovery
iv. 4 week toxicity and toxicokinetic
study in dog
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If the impurity profile of the GMP batch differs from the non-GMP preclinical
batch, then another GMP batch of drug substance will need to be prepared or a
bridging toxicology study is required which will delay the clinical trial.
In the single-dose escalating toxicological studies, the dose of the drug
candidate is increased via the intended therapeutic route of administration until
any adverse events are observed or until a predetermined maximum dose is
obtained. The goal for selecting dose levels is to demonst rate no observable
adverse effect level (NOAEL) at as high dose as possible, since this will set the
limit for what can be tested in humans. As an example, if the doses are increased from
1 mg/kg to 10 mg/kg and then finally 100 mg/kg, and adverse events are evident at
100 mg/kg, the NOAEL is 10 mg/kg. Perhaps doses at 10, 30, and 100 mg/kg would
again only show adverse events at 100 mg/kg, in which case the NOAEL now is 30 mg/
kg. To ensure a good safety margin, the NOAEL should be at a dose 50- to 100-fold
greater than the efficacious dose.
Repeated dosing for 4 weeks at doses expected to produce efficacy and below the
maximum tolerated dose in the escalating single-dose study will detect any adverse
effects upon repeat systemic exposure. A recovery period will provide information
regarding reversal of any side effects noticed. In both single-dose escalating and
repeat-dose toxicol ogy studies, toxicokinetic (TK) data should be collected for
systemic exposure.
The reproductive toxicology studies administered in rat and rabbit are designed to
detect any adverse effects on the ability to reproduce as well as effects on the
developing embryo. Safety pharmacology studies are designed to detect effects on the
cardiovascular, respiratory, and central nervous system. As previously discussed,
safety pharmacology studies of respiratory and central nervous systems for Sibutramine were favorable, but the drug is severely limited in dose due to heart rate and
blood pressure effects [10].
10.6.5 Regulatory
It is important to meet with the FDA as early as possible to discuss whether the
proposed preclinical plan provides sufficient safety information for the proposed
clinical studies, and to discuss the design of the clinical study. Proper timing of this
meeting is based upon two factors: (1) a company’s strategy for interacting and
communicating with the FDA; (2) the Division of the FDA (cardiovascular and renal,
neurology, metabolism and endocrinology, etc.) for submission of the application.
Different companies will provide the FDA a different preclinical data package for
their review and guidance. Differences in the data package may include varying
toxicology studies, GLP versus non-GLP,use of GMP drug product, etc. The advice of
an experienced consultant is very valuable to decide which data to present including
a Phase 1 protocol draft.
Typically in the pre-IND request meeting letter, the Sponsor will submit questions
that will allow FDA to guide a Sponsor in the studies that will be required to design
and initiate a Phase 1 trial. Data to provide a sense of the maximum tolerated dose,
414 PRECLINICAL CANDIDATE NOMINATION AND DEVELOPMENT
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generated in the early pilot toxicological studies, is usually included in the briefing
document.
A Phase 1 protocol is prepared while the nonclinical pharmacology and toxicology
studies are being conducted. Once the Phase 1 protocol, CMC data, and nonclinical
pharmacology and toxicology studies are completed, the clinical Investigator’s
Brochure (IB) may be prepared. The IB summarizes the CMC, nonclinical pharmacology and toxicology, and clinical data of the drug candidate for the clinical
investigators selected to conduct the clinical studies.
10.7 CONCLUSIONS
As discussed, there are a multitude of factors influencing the selection of a preclinical
candidate as well as a variety of development paths once a candidate has been
selected. The disease area will greatly influence the studies that need to be performed,
and also to a large extent determine the side effects that are acceptable for a drug
candidate. Given the significant cost associated with generating a preclinical data
package, a candidate should be selected with great care and the development plan
should be discussed with the FDA at an early stage to insure that the data will support
an IND filing.
REFERENCES
1. Guidance for Industry: Content and Format of Investigational New Drug Applications
(INDs) for Phase 1 Studies of Drugs, Including Well-Characterized, Therapeutic, Biotechnology-Derived Products. Available at http://www.fda.gov/cder/guidance/phase1.pdf.
2. Clinical Trial. Available at http://en.wikipedia.org/wiki/Clinical_trials.
3. Wang, J. and Urban, L. The impact of early ADME profiling on drug discovery and
development strategy. Drug Discov. World 2004, 5(Fall),73–86.
4. Guidance for Industry. Developing Products for Weight Management. Available at http://
www.fda.gov/cder/guidance/7544dft.pdf.
5. Kola, I. and Landis, J. Can the pharmaceutical industry reduce attrition rates? Nat. Rev.
Drug Discov. 2004, 3(8), 711–715.
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htm.
7. Neuvonen, P. J., Backman, J. T., and Niemi, M. Pharmacokinetic comparison of the
potential over-the-counter statins simvastatin, lovastatin, fluvastatin and pravastatin.
Clin. Pharmacokinet. 2008, 47,463–474.
8. Neuvonen, P. J., Niemi, M., and Backman, J. T. Drug interactions with lipid-lowering
drugs: mechanisms and clinical relevance. Clin. Pharmacol. Ther. 2006, 80(6), 565–581.
9. Babbs, A. J., Smyth, D. J., and Thomas, G. H. PSN602: A Novel Monoamine Reuptake
Inhibitor and 5-HT1A Agonist that, in Rats, Exhibits Equivalent Weight Loss to Sibutramine with a Superior Cardiovascular Profile. Proceedings of the American Diabetes
Association 68th Scientific Sessions, 2008, 1744 p.
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10. Product Monograph, Meridia. Available at http://www.abbott.ca/static/content/document/
Meridia-PM-15JAN09.pdf.
11. Pipeline MBX-2982. Available at http://www.metabolex.com/MBX-2982.html.
12. Overton, H. A., Babbs, A. J., Doel, S. M., Fyfe, M. C., Gardner, L. S., Griffin, G., Jackson,
H. C., Procter, M. J., Rasamison, C. M., Tang-Christensen. M., Widdowson, P.S., Williams,
G. M., and Reynet, C. Deorphanization of a G protein-coupled receptor for oleoylethanolamide and its use in the discovery of small-molecule hypophagic agents. Cell Metab.
2006, 3(3), 167–175.
13. Summary Basis of Decision (SBD): Pr Sutent. Available at http://www.hc-sc.gc.ca/dhpmps/prodpharma/sbd-smd/phase1-decision/d rug-me d/sbd_ smd_20 07_su tent_1 01319eng.php.
14. Turpeinen, M., Korhonen, L. E., Tolonen, A., Uusitalo, J., Juvonen, R., Raunio, H., and
Pelkonen. O. Cytochrome P450 (CYP) inhibition screening: comparison of three tests.
Eur J Pharm Sci. 2006; 29(2), 130–138.
15. Madsen, K., Bjerre Knudsen, L., Agersø, H., Nielsen, P.F., Thøgersen, H., Wilken, M., and
Johansen, N. L. Structure activity and protraction relationship of long acting glucagon like
peptide 1 derivatives: importance of fatty acid length, polarity and bulkiness. J. Med. Chem.
2007, 50, 6126–6132.
16. Guidance for Industry. Diabetes Mellitus—Evaluating Cardiovascular Risk in New
Antidiabetic Therapies to Treat Type 2 Diabetes. Available at http://www.fda.gov/cder/
guidance/8576fnl.pdf.
17. Davies, N.M., Teng, X.W., and Skjodt, N.M. Pharmacokinetics of rofecoxib: a specific
cyclo-oxygenase-2 inhibitor. Clin. Pharmacokinet. 2003, 42, 545–556.
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21. Guidance for Industry. Diabetes Mellitus: Developing Drugs and Therapeutic Biologics for
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11
FRAGMENT-BASED DRUG DESIGN:
CONSIDERATIONS FOR GOOD ADME
PROPERTIES
HAITAO JI
11.1 INTRODUCTION
The development of a new therapeutic drug creates many challenges as a drug has to
possess many attributes for it to be an effective medicine, which includes potency,
target selectivity, bioavailability, appropriate duration of action, and lack of toxicity.
Historically, most drugs have been discovered either based on an already existing
therapeutic agent or by random screening of compound collections [1]. Modern
technologies for the synthesis and screening of large numb ers of compounds have
provided unique opportunities and challenges in drug discovery. The onset of
combinatorial chemistry and the development of screen miniaturization and
automation have resulted in much larger compound collections and vastly enhanced
high-throughput screening (HTS) capabilities. These developments have taken the
discovery of hits to a new level over the last several decades, enabling the screening
of collections of hundreds of thousands of compounds in a matter of days, and
allowing high-throughput screening of corporate compound collections the predominant approach for hit discovery in large pharmaceutical companies.
Nevertheless, despite several success stories [2], HTS has not, so far, been able to
completely fulfill the original expectations of being able to bring medicines to the
marketplace more rapidly [3], because HTS has some inherent fundamental issues
that limit its scope. First, even in an ideal world where reliable assays can be
developed against all targets, HTS will only be capable of identifying compounds
ADMET for Medicinal Chemists: A Practical Guide, Edited by Katya Tsaioun and Steven A. Kates
Copyright 2011 John Wiley & Sons, Inc.
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that already exist in corporate or commercial collections. This not only puts a strain on
novelty and downstream intellectual property of the hits themselves but also limits
medicinal chemistry to existing themes and knowledge; exploration of compound
chemical space in truly new directions does not, by definition, automatically ensue.
Second, different estimates exist in the literature as to the number of possible chemical
structures with lead-like sizes, all of them being larger than the number of atoms on
earth. Typically, in a HTS campaign, targets are interrogated with approximately 10
6
discrete compounds in parallel, which falls far short of potential chemical diversity
space, estimated to be upward of 10
60
molecules containing up to 30 nonhydrogen
atoms [4]. Third, corporate libraries are continuously being filled with compounds
that have been synthesized in late-phase discovery projects, and hence have drug-like
rather than lead-like properties. The good hits identified from historical compound
collections usually have moderate biological activity (K
i
or Kd: 1–10 mM), but with
relatively high-molecular weights (the average molecular weight is 400 Da) and
excessive lipophilicity [5], which are frequently not amenable for lead optimization
to generate compounds with drug-like properties. Finally, for many targets, suitable
lead molecules will simply be absent from the compound collections or the HTS hit
rate is very low, which results in few good chemical starting points for inhibitor
optimization [2e].
The adoption of concepts such as leadlikeness [6] and druglikeness [7], as well as
an increased awareness of the importance of more general physicochemical properties
of compound collections, will undoubtedly lead to improved success rates in HTSbased lead generation [8]; however, it is generally accepted that there is a need for
alternative, complementary approaches for lead generation. The analysis of HTS hits
by Hann and coworkers shows that bad ligand–receptor interactions increase exponentially with the size and complexity of the molecule. As a consequence, the
probability that small and simple molecules will bind to the protein, albeit with low
affinity, is much higher than HTS-size compounds [9]. Indeed, ligand-efficiency (LE)
calculations [10] of HTS hit compounds show that the average contribution to binding
per atom can be rather modest. This supports the use of molecular fragments to anchor
the drug design process rather than complex and large molecules.
11.2 FRAGMENT-BASED SCREENING
Stimulated by the introduction of Lipinski’s “rule of five” [11], many research
programs filter compound collections and retain those with lower average molecular
weights, which have a smaller chance for mismatches with receptor-binding sites.
This trend led to the generation of fragment-based screening [12], which was first
described in 1997 with the advent of SAR by NMR [13], but has only become p ractical
in recent years because of significant advances in technology.
Fragment-based screening relies on the identification of low-molecular weight
and simple (low complexity) compounds that (weakly) bind to a chosen target and
attempts to construct drugs from these small-molecular pieces to achieve the desired
biological activity and molecular properties. This important approach is largely
418 FRAGMENT-BASED DRUG DESIGN: CONSIDERATIONS FOR GOOD ADME PROPERTIES
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complementary to HTS as a technique that aids the hit-to-lead processes [14]. The
technologies that have played a major role in driving the development of fragment
discovery are nuclear magnetic resonance (NMR) spectroscopy [15], X-ray crystallography [16], mass spectrometry [17], and surface plasmon resonance [18]. These
methods are also sometimes used in a synergistic way [19].
Fragment-based screening offers a number of attractive features compared with
HTS. First, compounds from HTS libraries are more restricted in their rotational
degrees of freedom, and thus less able to be adapted to a given target site. Conversely,
a high proportion of atoms of a fragment hit are directly involved in the desired
receptor–ligand interactions, which allows for optimal positioning within the
receptor pocket. Therefore, a fragment is generally a more efficient binder (high
binding energies per unit molecular mass) [20]. Second, a fragment-based strategy
provides a combinatorial advantage. The number of fragments screened is in the
range of only hundreds to a few thousands, but a larger chemical space than
a preassembled large compound library may be explored. On the contrary, developing and maintaining a small set of fragments with simpler structures is easier than
maintaining a massive HTS library. Third, when the binding of a fragment is
identified, the subsequent structural optimization can benefit from extensive design
and may result in a higher success rate and greater flexibility for generating novel
chemical entities. Finally, starting with a low-molecular mass fragment is likely to
produce leads with rather small and simple structures, which allows for molecular
mass increases during the lead optimization process. Fragment-based screening
provides chemical starting points that have no or few unnecessary structural
elements, and therefore allows the addition of groups that can reduce the risk of
toxicity or metabolic instability.
11.2.1 Fragment Library Design
The molecules in the library for fragment-based screening should be of a lower
complexity than those typicall y screened by HTS. Since the throughput of fragmentbased screening is generally low, typically only about 500–1000 molecules per target
are screened. Therefore, a carefully designed library is essential.
The basic principles for the design of fragment libraries have been discussed [21].
One selection strategy to build a generic fragment library is to analyze current drugs,
since they have already passed toxicity and ADME studies [22]. Databases such as the
MDL comprehensive medicinal chemistry (CMC) [23], the Maccs drug data report
(MDDR) [24], and the world drug index (WDI) [25] containing drugs or molecules in
development are analyzed to identify interesting structural elements that can be used
for library design. When applying this strategy, one must be aware that this is
a retrospective analysis and this appro ach is then biased toward what is known.
To limit the complexity of the fragments, the “rule of three” was introduced for
fragments on the basis of Lipinski’s “rule of five” [26], stating that the molecular
weight of screening fragments should be <300, Clog P 3, the number of H-bond
donors 3, the number of H-bond acceptors 3, the number of rotatable bonds 3,
and polar surface area (PSA) 60 A
˚
2
. The retrospective analysis of 18 different drug
FRAGMENT-BASED SCREENING 419
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leads confirmed that fragments should not be larger than 20 heavy atoms or about
300 Da (for some targets, the upper limit to the molecular weight of fragment was set
to 250 Da). However, a lower limit to the molecular weight should also be taken into
account in a fragment library [27]. A lower limit of approximately 150 Da minimizes
the chance that a fragment reorients on the target on elaboration [28], because smaller,
less complex fragments that only contain single rings with small substituents have
a greater likelihood of binding in multiple orientations [29].
Effective molecular recognition elements need to be packed into fragments
with low-molecular complexity. Hydrophob ic and electrostatic interactions are two
important forces that describe the molecular recognition between ligand and protein.
Most structures in a generic fragment library should include a hydrophobi c
group [30] and a strong hydrogen bonding or charged group [21c]. Restrictions
to the numbers of substituents are important so as not to miss attractive binders for
a particular target [31]. The active chemical functionalitie s of the fragments have to
be masked to avoid potential false positives or negatives due to unwanted reactions
with the target enzyme and working buffers. Each fragment should preferably
possess at least one masked linker group that can be used for further structural
elaboration.
In fragment-based screening, water solubility of fragments is of paramount
importance since they are screened at high concentration (0.2–1.0 mM) in aqueous
buffer. A 500 mM concentration of compounds in 95% phosphate-buffered saline
and 5% DMSO is the typical standard solution to determine whether a fragment is
appropriate for fragment-based screening.
Substructural analysis and filtering can be used to evenly select fragments that are
dispersed to the different subregions of chemical space. The measure of molecular
similarity (2D and 3D fingerprints, physicochemical properties, electrostatic fields,
and molecular shape) can be accommodated within this design paradigm [32].
11.2.2 Detection and Characterization of Weakly Binding Ligands
Fragments typically are unable to derive substantial free energies from interactions
with protein-binding sites because of their small size and limited functionality, and as
a result display equilibrium dissociation constants in the range of 10
4
–10
2
M.
Therefore, fragment-based screening must be able to detect binding that is 2–3 orders
of magnitude weaker than that for typical HTS campaigns. Because most detection
technologies require a level of binding site occupancy of >20% for reliable
identification of a binding event, fragments must be screened at high concentration, and this places severe demands on the assay. Functional biochemical assays,
particularly those that have been miniaturized for compatibility with HTS formats,
cannot always give reliab le results under such conditions. However, biophysicsbased detection methods, which give a direct readout of ligand binding to a target
protein, are often preferred for fragment-based screening. Biophysical methods tend
to have significant robustness and resistance to artifacts, and additionally, some
afford a high level of information content that can assist the downstream exploitation
of fragment hits.
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