Drug development and discovery

1. HIT to LEAD
Drug discovery
Dr. Rajat Saini
Senior resident
Pharmacology
LHMC

2. Drug Discovery
• Drug Discovery is defined as the process by which pharmaceutical, academic or
government laboratories identify or screen compounds to find potentially active
pharmacological agent.
• Drug Screening consists of testing many compounds in an assay relevant to the disease
in question.
• A compound that passes the screen is called ‘hit’ compound.
• If the compound or its structural derivatives consistently show promise after further
biological and chemical characterization, it becomes a ‘lead’ compound.
• Ideally drug discovery should be cost-effective and produce hits that have greater
likelyhood of conversion to lead and eventually successful drug for marketing.

3. • Lengthy, high risk and complex process
• Every 5-10 thousand chemically synthesized molecules that are
screened for development, only one becomes an approved drug.
• Modify ‘hit’ to increase activity

5. • Introduction of new technologies
• bio/pharmacoinformatics, fluorescence, spectroscopy, cell culture
techniques, pharmacogenomics, recombinant DNA technology,
combinational chemistry etc.)
• Understanding of the pathophysiology of diseases and on molecular
biology technologies, new targets (receptors, enzymes, ion channels,
genes) are identified and assay systems are developed to test large
number of molecules from existing libraries using robotic system.

6. • High throughput screening (HTS) and ultra-high throughput screening (UHTS)
will identify hits, i.e. molecules with reasonable affinity (binding property)
to the target
• The medicinal chemist then optimizes the hit molecule, aiming at maximal
potency and selectivity, and when successful this will result in one or more
lead compounds for testing in in-vitro system.
• NMR, X-Ray crystallography, mass-spectroscopy computer-assisted
structure-activity relationship (CASAR) and computer-assisted molecular
design (CAMD) technologies are used in lead optimization.

8. • Drug discovery may be compound-centered or target-centered
• Compound-centered Drug Design:
• Identify compound
• Assess biological activity
• Modify compound to increase activity
• Target centered Drug Design:
• Identify target
• Determine structure/develop assay
• Use structure/assay to obtain ‘hit’
• Modify ‘hit’ to increase activity

9. COMPOUND-CENTERED DRUG DESIGN
• Compound is identified by one of several methods and its biological
profile is explored.
• If the compound displays desirable pharmacological activity, it is
refined and developed further.
• Natural, synthetic and natural analogs

10. Natural Compounds
• Traditionally drugs were discovered using a compound centered
approach
• Earliest drugs discovered were natural products isolated from plants,
molds, or other organisms
• Discoveries were made serendipitously, e.g. penicillin was discovered
when Alexander Fleming observed that spores of the contaminant
mold Penicillium notatum inhibited bacterial growth in a petridish.
• Other natural products :
• Pacilitaxel, a chemotherapeutic derived from the Pacific yew tree,
• Morphine, an opioid analgesic obtained from the opium poppy,
• Streptokinase, a thrombolytic agent obtained from streptococcal
bacteria etc.

11. Advantages to examining natural products
i) Natural products have a reasonable likelohood of biologic activity
ii) It may be easier to isolate a compound from its natural source than to
synthesize a compound de novo,
iii) especially if the structure of the compound is complex or requires difficult
synthetic manipulations
iv) It may be feasible to use the natural compound as a starting point for
synthetic fine-tuning, i.e. to for a semi-synthetic product.

12. Disadvantages of natural products
i) It often takes significant effort to isolate a natural product, without a
guarantee of success
ii) Although natural products are more likely than many synthetic
compounds to have biological activity, it may be difficult to predict
which assay system would be optimal for testing the function of
these molecules
iii) Even if it is found to be pharmacologically active, a natural product
can be expensive to isolate and modify

13. Synthetic Compounds
• This approach is now frequently used to search for new drugs
• Researchers can construct a library consisting of thousands of
compounds with differing structural characteristics tailored for a
particular type of need, e.g. a library could consist of numerous
compounds that have a lysine-proline instead of proline-lysine bond
or that are likely agonists or antagonists of a particular class of
receptors.

14. Analogs of Natural Ligands
• An alternative compound-centered approach uses the natural ligand or an agonist of a
receptor as the starting point for drug development, e.g. since dopamine deficiency in
nigro-striatal system in the brain is associated with Parkinson’s disease, one of the first
effective treatments, for this disease was administration of L-dopa, a metabolic
precursor of dopamine
• Insulin was developed in much the same way; once it was discovered the signs and
symptoms of diabetes mellitus were caused by low insulin levels, insulin was
administered exogenously
• The Natural agonist of a receptor can also serve as a skeleton on which chemical
modification can be made
• Such changes can alter the compound’s binding affinity or physiological effect, e.g.
agonist converting into an antagonist.This approach was used in the development of
cimetidine an H2-receptor antagonist from histamine/insulin analogs with different
pharmacokinetic properties.

15. TARGET-CENTERED DRUG DESIGN
• This strategy is more common mode, the putative drug target is identified
first
• The potential target could be:
• A receptor thought to be involved in a disease process,
• A critical enzyme, or another biologically, important molecule in the
disease pathway.
• Once the target is identified, researchers search for compounds that interact
with the target as agonists, antagonists, or modulators.
• The search may be
• Systematic, using information about the structure of the target as a starting point
• Shotgun approach, whereby all the compounds in a large library of compounds,
synthesized via combinatorial chemistry, are tested in a high-speed automated assay.

16. • In this strategy, researchers used a validated biochemical or molecular
target to search for hits.
• This strategy has several advantages
• High likelyhood of HIT interacting with target (associated disease)
• easier to devise assays capable of isolating effect of an agent on the
target. This is specially true for diseases too complex to observe in cell or
tissue preparations, e.g. a potential drug effect on the process of
anthersclerosis may be difficult to measure rapidly, it is relatively easy to
measure whether the drug inhibits an enzyme shown to be involved in the
pathogenesis of this disease such as HMG-CoA reductase.
• HIV protease inhibitors, such as ritonavir
• In an alternative approach, the development of macromolecules,
including antibodies, as novel pharmaceuticals to interrupt the
pathway(s) involved in different disease process.

17. High-Throughput Screening (HTS)
• An assay performed in a 96- or 384-well plate : screen many compounds
simultaneously.
• Once a library of compounds has been established, the same library can
be run through many different assays.
• Quality of assay results is dependent on the assay method(s) and the
compounds in the library, ( poorly designed assay or a limited library may
result in false hits or miss viable candidates )
• In practice, because HTS places a premium on rapid assays, false +ve and
false –ve are not uncommon; besides when a true hit is found it is most
likely be refined to increase its binding affinity or to change its
pharmacological properties (specificity, solubility, stability, kinetic, etc.).
• This process is called hit-to-lead development

18. Combinatorial Chemistry
• One important refinement in the process of HTS has been the
introduction of combinatorial chemistry
• This is a strategy analogous to that used by nature to construct a
wide variety of proteins from a relatively small number (approx.
20) of amino acids
• Here researchers use a relatively small number of precursor
molecules to generate a large number of compounds, e.g. a
researcher starting with 3 sets of 30 precursor building blocks can
create 27,000 (30x30x30) different compounds in two synthetic
steps.

19. • One could theoretically create each compound individually in its
own reaction well, but in practice it is easier to synthesize the
molecules on a solid support such as a polystyrene bead.
• In a parallel synthesis, the beads are split so that thousands are
reacted at once and then successively recombined and split to
undergo successive reactions.
• This strategy drastically reduces the number of reactions in the
synthesis (30 at a time instead of 27,000 at a time).

20. Structure-based design / Rational drug design
• In some target-centered strategies called Structure-based design
/ Rational drug design, a drug candidate is discovered using the
three-dimensional structure of the target obtained through NMR
or X-ray crystallography
• In theory, one could identify the active site within the structure of
the target, use modeling algorithms to study the shape of the
active site and design a candidate drug molecule to fit into the
active site.
• More commonly, though, the target is co-crystallized with a
substrate analogue or receptor ligand (agonist/antagonist) in
order to identify the structure of the active site.

21. • The structure of the analogue is then modified to increase the
molecule’s affinity (as was done in the case of ritonavir)
• Alternatively, one can refine the structure of a new compound
that binds to the target in a screening assay.
• By iteratively improving the fit of the prototypic molecule in the
active site of the target, the binding affinity is increased.
• There are several advantages to a structure-based drug design
approach e.g. the refined hit (also called lead) compounds are
often extremely potent, with binding affinities in the nanomolar
range.

22. • Moreover, only a limited number compounds need to be tested
because there is a high likelihood that one or more of the
designed compounds will bind the target.
• In addition, iterative modification of the compound is relatively
straightforward because it is known which parts of the molecule
are critical for binding to the active site of the target.
• Thus, in comparison to a structure-blind approach, fewer
analogues are prepared in a structure-based approach but each
analogue has a higher likelihood of activity.
• Structure-based methods have also been used to develop a new
class of antiviral drugs, the neuroaminidase inhibitors
(Oseltamivir; Zanamivir).

23. LEAD OPTIMIZATION
• The early drug discovery process will typically identify a promising
groups of lead molecules that appear to interact with the target in a
desirable way.
• For these promising molecules, however, many of the physical,
chemical, biological and pharmacological properties that are
important attributes of an effective drug remain unknown
• Lead optimization is the stage of drug discovery where these
properties are characterized and refined, with the ultimate goal of
selecting a single molecule to enter into clinical testing and formal
drug development, e.g. a number of precursors of ritonavir went
through several modifications before a final compound was chosen
to enter clinical trials.

24. Termination at the lead optimization stage.
• Failure to demonstrate efficacy in a rigorous animal model of
human disease
• Failure to attain adequate systemic exposures following oral
administration (low bioavailability)
• Extensive or complex metabolism within the body, resulting in the
generation of potentially dangerous reactive metabolites
• Extremely low solubility that prevents preparing a suitable
formulation for dosing
• Toxic effects in preliminary animal toxicology studies
• In vitro evidence that the molecule may damage DNA
(genotoxicity)
• Extremely difficult chemical synthesis that cannot be “scaled up”
in a cost-effective manner.

26. PHASES OF DRUG DEVELOPMENT
• The outcome of the lead optimization process is the selection of a molecule
suitable for testing in humans
• At this point, the molecule moves from drug discovery to drug development
• Early drug development consists of preclinical activities designed to support
clinical trials and clinical drug development
• The initial preclinical phase of drug development includes the following
activities:
• Manufacture, formulation, and packaging of high quality drug for both
the animal safety and clinical trial use
• Animal toxicology and pharmacokinetic studies to support the safety of
initial drug administration in humans
• Preparation of regulatory documents for submission to regulatory
authorities.

27. Drug Discovery
• Application of CAMD
• Using receptor-based properties (binding affinity and receptor
selectivity), CAMD calculates to propose a broad range of properties
that are likely to be useful in drug design from physical properties,
like molecular size solubility, indicators of metabolic fate and toxicity
etc.
• CAMD is also applied to find and validate the elements of Rule of five
or Lipinski’s rule. As per this rule, a drug like compound looks like a
molecule with a molecular weight <500, OH, NH groups less than 5,
the sum of N and O atoms less than 10 and log P value less than 5 for
a better absorption in the intestine.

28. LEAD IDENTIFICATION
 Compounds are identified which interact with the target proteins and modulate its activity
Random (Screening) Rational (Design)
Natural compounds Structural Biology
Derivatization Molecular modeling
Combinatorial Library design
Physico-chemical approaches

29. HIGH THROUGHPUT SCREENING
• Throughput speed of screening compounds
• 10,000/day-------HTS
• 100,000/day-----UHTS
• Adapted assays
• Mix and measure-avoid filtration, separation, wash
• µL to nanoL

30. HTS CHARACTERISTICS
 Automation
 Miniaturization
 Cellular assay system improvements
 Computational methods for assay simulation
 Data management improvements and innovations
 Increase in compound library diversity and size
 Integrated systems
 Exponential increase in targets from genomics/proteomics
 Outsourcing and customization
 More sensitive and efficient assay and detection systems
 Sensitive alternatives to radioactive assays
 Lead optimization tools

31. LIMITATIONS OF HTS
 Conducted in 500 labs worldwide
 Coordination of technology, processes and people
 Permanent need to supply
 Storage & retrieval at -20C, constant humidity
 Low volume liquid handling
 Positional accuracy of robotic arm
 Repair-cost, time lost
 “Human attention”
 Analyzing data

32. NATURAL PRODUCTS FOR LEAD
IDENTIFICATION
 Secondary metabolites of plants, microbes, animals
 Provide diversity
 Identify new targets
 New molecules acting on known targets
 Chromatographic separation (HPLC, HPTLC, LC-MS, IR,,
NMR)

33. VIRTUAL SCREENING
In vivo-------In vitro --------In silico
3-D structures of compounds from virtual/existing libraries are
docked on binding sites of target proteins
Steric and electrostatic complementarity
Attractive, cost effective before cumbersome synthesis
Time/Structure/Computer processor
Parallelization increases throughput

34. LIPINSKI’s RULE

35. LEAD OPTIMIZATION
• Chemical modification and pharmacological characterization of lead
• QSAR

36. HIT TO LEAD
• Hit to lead (H2L) also known as lead generation is a stage in early drug
discovery where small molecule hits from a high throughput screen (HTS) are
evaluated and undergo limited optimization to identify promising lead
compounds
• These lead compounds undergo more extensive optimization in a subsequent
step of drug discovery called lead optimization (LO).
• The drug discovery process generally follows the following path that includes
a
• hit to lead stage: target validation (TV) → assay development → high-throughput
screening → hit to lead (H2L) → lead optimization (LO) → preclinical drug
development → clinical drug development

37. • The hit to lead stage starts with confirmation and evaluation of the
initial screening hits and is followed by synthesis of analogs (hit
expansion).
• Initial screening hits display binding affinities for their biological target
in the micromolar (10−6 molar concentration) range.
• Through limited H2L optimization, the affinities of the hits are often
improved by several orders of magnitude to the
• nanomolar (10−9 M) range. limited optimization to
• improve metabolic half life
• improve selectivity against other biological targets binding

40. Target identification
• one of the most important steps in developing a new drug is target identification and validation.
• A target (range of biological entities) : proteins, genes and RNA.
• good target: efficacious, safe, meet clinical and commercial needs and, above all, be ‘druggable’.
• A ‘druggable’ target is accessible to the putative drug molecule, be that a small molecule or larger
biologicals and upon binding, elicit a biological response which may be measured both in vitro
and in vivo.
• G-protein-coupled receptors (GPCRs), whereas antibodies are good at blocking protein/protein
interactions.
• Good target identification and validation enables increased confidence in the relationship
between target and disease and allows us to explore whether target modulation will lead to
mechanism-based side effects.

41. • Data mining of available biomedical data has led to a significant increase in
target identification. In this context, data mining refers to the use of a
bioinformatics
• DATABASE: publications and patent information, gene expression data, proteomics
data, transgenic phenotyping and compound profiling data.
• Examining mRNA/protein levels to determine whether they are expressed in
disease and if they are correlated with disease exacerbation or progression. '
• Genetic associations, for example, is there a link between a genetic
polymorphism and the risk of disease or disease progression or is the
polymorphism functional. familial Alzheimer's Disease (AD) patients
commonly have mutations in the amyloid precursor protein or presenilin genes
which lead to the production and deposition in the brain of increased amounts
of the Abeta peptide, characteristic of AD

42. TARGET IDENTIFICATION
Systematic high throughput separation and characterization of
proteins within biological systems- PROTEOMICS
Protein level of disease manifestations identified
Diagnostics, Target discovery, Target validation, Lead compound
selection, Investigation of mode of action, Toxicology and Clinical
development

43. TARGET IDENTIFICATION IN GENE BASED THERAPY
• Up to 10 genes contribute to multi-
factorial diseases
• Disease genes are linked in circuit
• 5000-10,000 potential drug targets
• Current drug therapy based on <500
molecular targets GPCR Enzymes
Hormones Ion channel
Nuclear receptor

44. Target validation
• Validation techniques range from in vitro tools through the use of whole animal models, to modulation of a desired target in disease
patients
• confidence in the observed outcome is significantly increased by a multi-validation approach
• Gene knockout : loss of function
• Phenotypic screening to identify disease relevant targets.
• Antisense mRNA technology (reversible as compared to gene knockout models)
• Transgenic animals
• Gene knock-ins, where a non-enzymatically functioning protein replaces the endogenous protein.
• small interfering RNA (siRNA) : RNA-induced silencing complex (RISC)
• Monoclonal antibodies
• Interact with a larger region of the target molecule surface, allowing for better discrimination between even closely related targets and often providing
higher affinity
• Antibodies cannot cross cell membranes restricting the target class mainly to cell surface and secreted proteins
• Classic target validation tool is the small bioactive molecule that interacts with and functionally modulates effector proteins.

45. Chemical genomics
• Chemical genomics : genomic responses to chemical compounds.
• Rapid identification of novel drugs and drug targets embracing multiple early
phase drug discovery technologies ranging from target identification and
validation, over compound design and chemical synthesis to biological testing.
• Brings together diversity-oriented chemical libraries and high-information-
content cellular assays, along with the informatics and mining tools necessary
for storing and analysing the data generated
• The ultimate goal of this approach is to provide chemical tools against every
protein encoded by the genome.
• The aim is to use these tools to evaluate cellular function prior to full
investment in the target

47. Hit confirmation
• After hits are identified from a high throughput screen, the hits are
confirmed and evaluated using the following methods:
• Confirmatory testing: compounds that were found active against the selected
target are re-tested using the same assay conditions used during the HTS to
make sure that the activity is reproducible.
• Dose response curve: the compound is tested over a range of concentrations
to determine the concentration that results in half maximal binding or activity
(IC50 or EC50 value respectively).
• Orthogonal testing: confirmed hits are assayed using a different assay which is
usually closer to the target physiological condition or using a different
technology.
• Secondary screening: confirmed hits are tested in a functional cellular assay
to determine efficacy

48. • Synthetic tractability: medicinal chemists evaluate compounds according to
their synthesis feasibility and other parameters such as up-scaling or cost of
goods.
• Biophysical testing: nuclear magnetic resonance (NMR), isothermal titration
calorimetry (ITC), dynamic light scattering (DLS), surface plasmon resonance
(SPR), dual polarisation interferometry (DPI), microscale thermophoresis
(MST) are commonly used to assess whether the compound binds effectively
to the target, the kinetics,thermodynamics, and stoichiometry of binding, any
associated conformational change and to rule out promiscuous binding.
• Hit ranking and clustering: Confirmed hit compounds are then ranked
according to the various hit confirmation experiments.
• Freedom to operate evaluation: hit structures are checked in specialized
databases to determine if they are patentable

49. Hit expansion
• Following hit confirmation, several compound clusters will be chosen
according to their characteristics in the previously defined tests. An
Ideal compound cluster will contain members that possess:
• high affinity towards the target (less than 1 µM) selectivity versus other
targets significant efficacy in a cellular assay druglikeness (moderate
molecular weight and lipophilicity usually estimated as ClogP). Affinity,
molecular weight and lipophilicity can be linked in single parameter such
asligand efficiency and lipophilic efficiency. low to moderate binding to
human serum albumin low interference with P450 enzymes and P-
glycoproteins low cytotoxicity

50. • metabolic stability
• high cell membrane permeability
• high water solubility (above 10 µM) chemical stability synthetic
tractability patentability The project team will usually select between
three and six compound series to be further explored.
• The next step will allow the testing of analogous compounds to
determine aquantitative structure-activity relationship (QSAR). Analogs
can be quickly selected from an internal library or purchased from
commercially available sources ("SAR by catalog").
• Medicinal chemists will also start synthesizing related compounds using
different methods such as combinatorial chemistry, high-throughput
chemistry, or more classical organic chemistry synthesis.

51. The hit discovery process
• HIT: compound of desired activity in a compound screen and whose activity
is confirmed upon retesting
• High throughput screening (HTS) : screening of the entire compound library
directly against the drug target or in a more complex assay system,
• cell-based assay, whose activity is dependent upon the target but which would then
also require secondary assays to confirm the site of action of compounds
• Focused or knowledge-based screening : smaller subsets of molecules that
are likely to have activity at the target protein based on literature or patent
precedents for the chemical classes
• Physiological screening : tissue-based approach and looks for a response
more aligned with the final desired in vivo effect as opposed to targeting one
specific molecular component.

52. • improve the potency, selectivity and physiochemical properties of the
molecule,
• established compound libraries, screening infrastructure and the appropriate
expertise traditionally found within the industrial sector to screen target
proteins to identify so-called chemical probes for use in target validation and
disease biology studies and increasingly to identify chemical start points for
drug discovery programmes
• Screening hits form the basis of a lead optimization chemistry programme to
increase potency of the chemical series at the primary drug target protein.
• Phase molecules are also screened in cell-based assays predictive of the
disease state and in animal models of disease to characterize both the
efficacy of the compound and its likely safety profile

53. Assay development
• primary cell systems for compound screening
• cell-based assays have been applied to target classes such as membrane receptors, ion channels
and nuclear receptors and typically generate a functional read-out as a consequence of
compound activity
• biochemical assays, which have been applied to both receptor and enzyme targets, often simply
measure the affinity of the test compound for the target protein.
• Both assay : identify hit and candidate molecule.
• Multiple assay formats have been enabled to support compound screening
• dependent upon the biology of the drug target protein, the equipment infrastructure
in the host laboratory, the experience of the scientists in that laboratory, whether an
inhibitor or activator molecule is sought and the scale of the compound screen

54. • Pharmacological relevance of the assay. : studies should be performed using known ligands with activity at the target under study, to
determine if the assay pharmacology is predictive of the disease state and to show that the assay is capable of identifying compounds with
the desired potency and mechanism of action.
• Reproducibility of the assay : Within a compound screening environment it is a requirement that the assay is reproducible across assay
plates, across screen days and, within a programme that may run for several years, across the duration of the entire drug discovery
programme.
• Assay costs : assay reagents and assay volumes are selected to minimize the costs of the assay.
• Assay quality. Assay quality is typically determined according to the Z' factor . This is a statistical parameter that in addition to considering
the signal window in the assay also considers the variance around both the high and low signals in the assay. The Z factor has become the
industry standard means of measuring assay quality on a plate bases. The Z factor has a range of 0 to 1
• an assay with a Z factor of greater than 0.4 is considered appropriately robust for compound screening although many groups prefer to work with assays
with a Z factor of greater than 0.6.
• Effects of compounds in the assay. Chemical libraries are typically stored in organic solvents such as ethanol or dimethyl sulphoxide
(DMSO). Thus, assays need to be configured that are not sensitive to the concentrations of solvents used in the assay. Typically, cell-based
assays are intolerant to solvent concentrations of greater than 1% DMSO whereas biochemical assays can be performed in solvent
concentrations of up to 10% DMSO. Studies are also performed to establish the false negative and false positive hit rates in the assay.

55. Defining a hit series
• Drug likeness
• small molecular weight molecules that obey chemical parameters such as the Lipinski Rule of Five ,
molecular weights of less than 500 and clogP (a measure of lipophilicity which affects absorption into
the body) of less than 5.
• Initiate a drug discovery programme with a small simple molecule as lead optimization, to improve
potency and selectivity,
• computational chemistry algorithms have been developed to group hits based on structural similarity.
Analysis of the compound hit list using these algorithms allows the selection of hits for progression
based on chemical cluster, potency and factors such as ligand efficiency which gives an idea of how
well a compound binds for its size (log potency divided by number of ‘heavy atoms’ i.e. non-hydrogen
atoms, in a molecule).
• next phase in the initial refinement process is to generate dose–response curves in the primary assay
for each hit. Obtaining a dose–response curve allows the generation of a half maximal inhibitory
concentration which is used to compare of the potencies of candidate compounds
• Reliable dose–response curves generated in the primary assay for the target, the stage is set to
examine the surviving hits in a secondary assay (second messenger assay or in a tissue-or cell-based
bioassay)

56. Hit-to-lead phase
• refine each hit series to try to produce
more potent and selective compounds
which possess adequate PK properties to
examine their efficacy in any in vivo models
that are available.
• intensive SAR investigations : magnitude of
activity and selectivity of each compound
• detailed profiling of physicochemical and in
vitro ADME properties
• series of studies is carried out in parallel,
with key compounds being selected for
assessment.

57. Lead optimization phase
• Synthesize lead compounds, new analogs with improved
• potency,
• reduced off-target activities
• physiochemical/metabolic
• reasonable in vivo pharmacokinetics.
• Chemical modification of the hit structure, with modifications chosen by
employing knowledge of the structure-activity relationship (SAR)
• Experimental testing and confirmation of the compound based on animal
efficacy models and ADMET (in vitro and in situ) tools.
• QSAR, ADMET, Rational/ structure based drug design

58. QSAR
40 years ago, Hansch, Fujita et al
invented the field of QSAR
Whole molecule parameters like
(partitioning, molar refractivity,
shape, topology indices) for groups
of related compounds are
statistically correlated with
measures of biological activity
Predictive for NCEs that may/may
not exist

59. Termination at the lead optimization stage.
• Failure to demonstrate efficacy in a rigorous animal model of
human disease
• Failure to attain adequate systemic exposures following oral
administration (low bioavailability)
• Extensive or complex metabolism within the body, resulting in the
generation of potentially dangerous reactive metabolites
• Extremely low solubility that prevents preparing a suitable
formulation for dosing
• Toxic effects in preliminary animal toxicology studies
• In vitro evidence that the molecule may damage DNA
(genotoxicity)
• Extremely difficult chemical synthesis that cannot be “scaled up”
in a cost-effective manner.