Far.fiocruz.br

How were new medicines discovered?David C. Swinney*‡ and Jason Anthony* Abstract Preclinical strategies that are used to identify potential drug candidates include target-based screening, phenotypic screening, modification of natural substances and biologic-based approaches. To investigate whether some strategies have been more successful than others in the discovery of new drugs, we analysed the discovery strategies and the molecular mechanism of action (MMOA) for new molecular entities and new biologics that were approved by the US Food and Drug Administration between 1999 and 2008. Out of the 259 agents that were approved, 75 were first-in-class drugs with new MMOAs, and out of these, 50 (67%) were small molecules and 25 (33%) were biologics. The results also show that the contribution of phenotypic screening to the discovery of first-in-class small-molecule drugs exceeded that of target-based approaches — with 28 and 17 of these drugs coming from the two approaches, respectively — in an era in which the major focus was on target-based approaches. We postulate that a target-centric approach for first-in-class drugs, without consideration of an optimal MMOA, may contribute to the current high attrition rates and low productivity in pharmaceutical research and development.
Investment in drug research and development (R&D) which are typically proteins that appear to have a key has increased substantially in recent decades, but the role in disease pathogenesis3–5. Modification of target annual number of truly innovative new medicines activity provides a rational basis for the discovery of approved by the US Food and Drug Administration new medicines; a target-centric approach provides a (FDA) has not increased accordingly, and attrition rates specific biological hypothesis to be tested and a starting are very high1. Indeed, in a recent analysis2 it was noted point for the identification of molecules to do this with. that without a dramatic improvement in R&D produc- Tremendous advances have been made in the develop- tivity, the pharmaceutical industry cannot sustain suf- ment of new tools to identify targets (for example, RNA ficient innovation to replace the loss of revenues due to interference) and compounds that interact with these patent expirations for successful products.
targets (for example, high-throughput target-based The authors of this analysis2 also considered R&D pro- screening assays that are applicable to key protein fami- ductivity in two dimensions: efficiency and effectiveness. lies such as G protein-coupled receptors and kinases). R&D efficiency represents the ability to translate inputs Structure-based tools that can be used to aid lead (such as ideas, investment and effort) into defined out- identification and optimization for some targets have puts (such as milestones that represent resolved uncer- also been developed, including X-ray crystallography tainties), whereas R&D effectiveness can be considered as and computational modelling and screening (virtual *Roche Palo Alto, the ability to produce outputs with certain intended and screening). 3431 Hillview Avenue, desired qualities. A key efficiency variable for increased However, despite the power of these tools to identify Palo Alto, California 94304, productivity is the probability of technical success. If the potential drug candidates, R&D productivity remains a probability of technical success could be increased (by crucial chal enge for the pharmaceutical industry, which iRND3 (Institute for Rare and Neglected Diseases Drug reducing attrition) for any given drug candidate or, ide- raises questions about the possible limitations of a tar- Discovery), 951 Old County al y, for a portfolio of drug candidates, then productivity get-centric approach to drug discovery. Indeed, before Road, PMB 316, Belmont, would increase accordingly. The authors also suggested the introduction of target-based approaches, drug dis- California 94002‑2760, USA. that target selection may be one of the most important covery was driven primarily by phenotypic assays, often Correspondence to D.C.S.  determinants of attrition and overall R&D productivity2.
with limited knowledge of the molecular mechanisms Since the dawn of the genomics era in the 1990s, the of disease. Nevertheless, the pharmaceutical industry main focus of drug discovery has been on drug targets, was successful in the discovery and development of new NATURE REVIEWS DRUG DISCOVERY
VOLUME 10 JULY 2011 507
2011 Macmillan Publishers Limited. All rights reserved innovative medicines; it has therefore been suggested list of all the drugs and their classification is provided that the more limited use of phenotypic screening in in Supplementary information S1 (table) and a brief recent years has contributed to the current lack of suc- description of the discovery history of first-in-class drugs cess in drug R&D6,7. is provideox). We These two different approaches to drug discovery categorized the method of discovery of each new drug as — target-based screening and phenotypic screening — target-based, phenotypic-based, modification of a natural each have advantages and disadvantages. The strengths substance, biologic-based or other (see Supplementary of the target-based approach include the ability to apply information S1 (table)). Overall, 100 NMEs were dis- molecular and chemical knowledge to investigate spe- covered using target-based approaches, 58 NMEs were cific molecular hypotheses, and the ability to apply both discovered using phenotypic-based approaches, 18 smal -molecule screening strategies (which can often be NMEs were based on modifications of natural sub- achieved using high-throughput formats) and biologic- stances and 56 of the agents were biologics. All of the based approaches, such as identifying monoclonal anti- biologics can be considered to have been discovered bodies. A disadvantage of the target-based approach is using a target-based approach, and the main focus of that the solution to the specific molecular hypotheses our analysis is on the methods of discovery for small- may not be relevant to the disease pathogenesis or pro- molecule first-in-class NMEs and follower NMEs; that vide a sufficient therapeutic index. is, small molecules that are in the same class as a previ- A strength of the phenotypic approach is that the ously approved NME.
assays do not require prior understanding of the molecu- lar mechanism of action (MMOA), and activity in such MMOA. The MMOA of the NMEs was analysed because
assays might be translated into therapeutic impact in a the limitations of a target-based approach with respect given disease state more effectively than in target-based to the MMOA have been highlighted8–10, and because assays, which are often more artificial. A disadvantage the MMOA is a characteristic of drugs that has received of phenotypic screening approaches is the challenge less attention with regard to its connection to attrition. of optimizing the molecular properties of candidate For the purpose of this article, MMOA is defined as the drugs without the design parameters provided by prior biochemical mechanism through which the structural knowledge of the MMOA. An additional challenge is interactions between the drug and its target(s) result in to effectively incorporate new screening technologies a functional response10–12, which is important in both into phenotypic screening approaches, which is impor- drug efficacy and safety (BOX 1). The MMOA can affect tant for addressing the traditional limitation of some how efficiently a binding interaction is coupled to the of these assays: a considerably lower throughput than functional response, which can be assessed by consider- target-based assays. ing biochemical efficiency (BOX 2). In order to gain a better understanding of the factors For instance, resistance to the ATP-competitive that could contribute to the high attrition rates, and to kinase inhibitors gefitinib and erlotinib — which target provide insights that might help to reduce attrition and the epidermal growth factor receptor (EGFR) kinase increase R&D productivity, we decided to investigate the — has been shown to be due to mutations that alter approaches that were used in the discovery of recently the ATP binding site in such a way that they increase introduced medicines. To achieve this, we analysed the the affinity of the EGFR kinase domain for ATP. The characteristics of the new molecular entities (NMEs) and functional consequence of these resistance mutations new therapeutic biologics that were approved by the is therefore to enable ATP to compete more effec- FDA during the 10-year period between 1999 and 2008 tively with gefitinib and erlotinib12,13. This provides an by examining the discovery approach, the MMOA and explanation for the mechanism of resistance to these whether the drug was first in its class.
rapidly reversible ATP-competitive inhibitors, and also provides an explanation as to why irreversible covalent Data and analysis
binding inhibitors overcome this resistance13.
Numbers of NMEs. In the 10-year period between 1999
An example of how the therapeutic utility of drugs and 2008, the FDA approved 183 smal -molecule drugs, that function through interaction with a receptor is 20 imaging agents and 56 new therapeutic biologics (259 influenced by their MMOA is provided by the tissue- agents overall). Out of these, 75 drugs were identified as selective functional effects of the selective oestrogen first-in-class or with novel MMOAs based on the infor- receptor modulators (SERMs), which are mediated mation provided in the product labels on the FDA web- by SERM-induced structural changes in the oestrogen site (see thwebsite), and primary research receptor14. Binding to the receptor initiates a series of and review publications (TABLE 1;molecular events, which culminate in the activation able)). The specific sources for each drug are or repression of specific genes. The SERMs tamoxifen referenced in TABLE 1 anand raloxifene bind at the same site within the core of the ligand-binding domain, but with different bind- New molecular entities ing modes that are translated into distinct conforma- (NME). A medication Discovery approaches. We divided the list of 259 tions of the transactivation domain of the receptor.
containing an active ingredient agents into three general categories: first-in-class drugs Transcriptional regulation of the oestrogen receptor that has not been previously approved for marketing in any (75 drugs), follower drugs (164 drugs) and imaging is a complex process that involves the participa- form in the United States.
agents (20 agents; these were not further analysed). A tion of co-activators and co-repressors, and the 508 JULY 2011 VOLUME 10
2011 Macmillan Publishers Limited. All rights reserved Table 1 First-in-class small-molecule new molecular entities approved by the FDA: 1999–2008
Drug (trade name; company)
Target type
Molecular mechanism of action
Discovered through phenotypic screeningAripiprazole (Abilify; Bristol-Myers Azacitidine (Vidaza; Celgene/Pfizer) Irreversible inhibition Caspofungin (Cancidas; Merck) Infectious disease Cilostazol (Pletal; Otsuka) Cinacalcet (Sensipar; Amgen) Allosteric activator Daptomycin (Cubicin; Cubist) Infectious disease NA (disrupts bacterial Unknown Docosanol (Abreva; Avanir Infectious disease Pharmaceuticals) Ezetimibe (Zetia; Merck) Slow binding kinetics Fulvestrant (Faslodex; AstraZeneca) Antagonist-induced degradation Levetiracetam (Keppra; UCB Pharma) Linezolid (Zyvox; Pfizer) Infectious disease Lubiprostone (Amitiza; Sucampo Pharmaceuticals)Memantine (Namenda; Forest) Uncompetitive and fast Miglustat (Zavesca; Actelion) Reversible inhibition Fast binding kinetics (Fastic; Novartis/Astellas)Nelarabine (Arranon; Nucleotide chain termination Nitazoxanide (Alinia; Roche) Infectious disease Irreversible and redox Nitisinone (Orfadin; Syngenta) Pemirolast (Alamast; Senten) Immune modulation Ranolazine (Ranexa; Gilead) Retapamulin (Altabax; Infectious disease Allosteric inhibitor GlaxoSmithKline)Rufinamide (Inovelon; Novartis) Infectious disease (Veregen; Medigene)Sirolimus (Rapamune; Pfizer) Immune modulation Varenicline (Chantix; Pfizer) Vorinostat (Zolinza; Merck) Equilibrium kinetics Ziconotide (Prialt; Elan Equilibrium kinetics Pharmaceuticals)Zonisamide (Excegran; Dainippon Pharmaceuticals)Discovered through target-based screeningAliskiren (Tekturna; Novartis) Equilibrium binding Aprepitant (Emend; Merck) Slow binding kinetics Bortezomib (Velcade; Millenium Equilibrium binding Pharmaceuticals)Bosentan (Tracleer; Actelion) Equilibrium binding Equilibrium binding (Vaprisol; Astellas Pharma)Eltrombopag (Promacta; Noncompetitive agonist GlaxoSmithKline)Gefitinib (Iressa; AstraZeneca) Stabilize inactive conformation NATURE REVIEWS DRUG DISCOVERY
VOLUME 10 JULY 2011 509
2011 Macmillan Publishers Limited. All rights reserved Table 1 cont. First-in-class small-molecule new molecular entities approved by the FDA: 1999–2008
Drug (trade name; company)
Target type
Molecular mechanism of action
Imatinib (Gleevec; Novartis) Stabilizes inactive conformation Maraviroc (Celsentri; Pfizer) Infectious disease Conformational and/or allosteric Mifepristone (Mifeprex; Aventis Pharma)Orlistat (Xenical; Roche) Raltegravir (Isentress; Merck) Infectious disease Traps conformational state Ramelteon (Rozerem; Takeda Equilibrium binding Pharmaceuticals)Sitagliptin (Januvia; Merck) Equilibrium binding Sorafenib (Nexavar; Bayer) Conformation state-specific inhibition Sunitinib (Sutent; Pfizer) Conformation state-specific inhibition Infectious disease Equilibrium binding (Relenza; GlaxoSmithKline)Discovered based on natural substrate or natural substanceAcamprosate (Campral; Merck) Conformational channel modulator Aminolevulinic acid (Levulan; Berlex) NA (photosensitizer) Fondaparinux (Arixtra; Sanofi) Sapropterin (Kuvan; BioMarin) Verteporfin (Visudyne; QLT) NA (photoreaction) CNS, central nervous system; FDA, US Food and Drug Administration; NA, not applicable.
different conformations presumably change the affinity Discovery of first-in-class medicines
of the receptor for the interacting co-activators and co- NMEs that were discovered through phenotypic screen-
repressors. The change in co-repressor affinity alters ing. The 28 first-in-class small-molecule NMEs that
the composition of the distinct cellular co-regulatory were discovered in phenotypic screens either came from complexes that modulate the functional transcriptional intentional targeting of a specific phenotype (25 NMEs) or through serendipity (3 NMEs) (FIG. 1). The inten- The MMOA can also differentiate similar drugs with tional approaches were based on assays that measured respect to their therapeutic indications. At the structural a specific physiological phenomenon, with little under- level, aspirin is an irreversible inhibitor of cyclooxyge- standing of the MMOA. In many cases, the newly dis- nases, whereas ibuprofen and naproxen are reversible covered molecules were subsequently used to identify inhibitors. All three molecules bind to cyclooxygenase MMOAs for the physiological phenomena. For example, enzymes at the same substrate binding site. However, the oxazolidinone antibiotics (such as linezolid) were the irreversible MMOA of aspirin differentiates its initially discovered as inhibitors of Gram-positive bac- functional use as an antiplatelet drug from the revers- teria but were subsequently shown to be protein synthe- ible inhibitors, because this MMOA translates into a sis inhibitors that target an early step in the binding of long-lasting action of aspirin in platelets, as platelets do N-formylmethionyl-tRNA to the ribosome28. This is also not have the capacity to resynthesize new enzymes15,16.
il ustrated by the calcium receptor al osteric activator cin- There are many different biochemical features of acalcet29, the sterol transporter inhibitor ezetimibe30 and an MMOA through which molecular interactions can the N-type calcium channel blocker ziconotide31; these contribute to a specific functional response. These drugs were initial y discovered using phenotypic assays.
include residence time10,17–19, irreversible binding20, The majority of discoveries focused on using specific transient binding21,22, and uncompetitive22,23 and non- chemical classes in which prior knowledge contributed competitive10 inhibition mechanisms (BOX 1). It has to matching the chemical class with the phenotype — been proposed that drugs should be activated by the for example, screening nucleoside analogues as poten- pathological state that they are intended to inhibit22,23. tial anticancer and antiviral agents. Random library Allosteric inhibition and activation are important for screening was also successful for ezetimibe, linezolid, the pharmacological modulation of many receptors and pemirolast, retapamulin, rufinamide and sirolimus. An channels24,25. Voltage- or frequency-dependent channel additional approach was to use phenotypic screening blockade can also influence a selective pharmacological to identify new MMOAs for established targets, which response26,27. Given the importance of the MMOA to the led to the discovery of the partial agonists aripiprazole therapeutic effects of NMEs, we consider it further in and varenicline, and the ful antagonist fulvestrant (see the following sections.
Supplementary information S2 (box) for details). It is 510 JULY 2011 VOLUME 10
2011 Macmillan Publishers Limited. All rights reserved Box 1 Molecular mechanism of action
The molecular mechanism of action (MMOA) is defined here as the interaction between a drug and its target (or targets) that
creates a specific response. These specific molecular interactions link structure to function in such a manner as to provide a
therapeutically effective and safe response. In this context, the MMOA is differentiated from mechanism of action (MOA), which
describes the mechanism in the context of the physiological response — such as antihistamines, anti-inflammatory, and so on.
There are many facets of this interaction that ultimately result in the desired therapeutic outcome. For example, the site of interaction (allosteric or orthosteric), molecular descriptors of the binding interaction (such as affinity and binding kinetics), the functional impact (for example, receptor agonism, modulation or antagonism) and the specificity of the functional outcome (for example, activation of specific signalling pathways) all contribute to the MMOA and affect the ultimate pharmacological response.
Possible MMOAs at a target are listed below, together with selected examples of drugs that act through these MMOAs.
Kinetic mechanisms
For kinetic mechanisms, the pharmacological response to the drug is primarily driven by binding kinetics and residence
time at the target12,17–19.
Equilibrium binding. The response to the drug is represented by the equilibrium dissociation constant (K ) to the target. The binding has sufficiently fast on and off rates (k and k ) to allow equilibrium to be reached and is thereby sensitive to competition with physiological substrates and/or ligands (for example, bosentan, an endothelin receptor antagonist; and aliskiren, a renin inhibitor)37,38,68.
Slow kinetics. Non-equilibrium and irreversible mechanisms involve slow association and/or dissociation rates (k and k ) that do not allow equilibrium to be reached and are less sensitive to competition with physiological substrates and/or ligands
(for example, orlistat binds irreversibly to the active site serine of pancreatic lipase, azacitidine irreversibly binds to DNA
methyltransferases and candesartan has a slow dissociation rate from the angiotensin II receptor)17–20,35,63,69.
Conformational mechanisms
For conformational mechanisms, binding of the drug to the target involves a conformational change in the target that
couples drug binding to a response (for example, sirolimus binds to the peptidylprolyl isomerase FKBP12, which stabilizes
a conformation that subsequently inhibits the kinase activity of mammalian target of rapamycin; and fulvestrant induces a
conformation of the oestrogen receptor that is subsequently degraded)8–11,47,70.
Noncompetitive inhibition and/or antagonism. This is a form of MMOA in which the drug binds to a site on the target that is distinct from the physiological substrate- and/or ligand-binding site that results in an inhibition of the response (for example, caspofungin is a noncompetitive inhibitor of 1,3-β-d-glucan synthase owing to the observation that its IC (half-maximal inhibitory concentration) is not influenced by substrate concentrations)68,71. Uncompetitive inhibition and/or antagonism. An uncompetitive MMOA is contingent on prior activation of the target by the physiological effector (the substrate or the ligand). This means that the same amount of drug blocks higher concentrations of the physiological effector to a greater degree than lower concentrations. For example, memantine is an uncompetitive antagonist that binds only to the activated form of the NMDA receptor. The potency of the inhibition of the NMDA receptor by memantine increases at higher concentrations of glutamate (the physiological ligand) 22,23,68. Full agonism. Maximal efficacy is produced following drug binding to the receptor and subsequent receptor activation (for example, ramelteon mimics the activity of melatonin for the melatonin receptor through binding at the orthosteric site with efficient coupling to activate specific signalling pathways) 72,73. Partial agonism. This is a form of MMOA in which only partial efficacy is produced following drug binding to the orthosteric site on the receptor (for example, aripiprazole is a partial agonist of the dopamine D2 receptor and varenciline is a partial agonist of the nicotinic acetylcholine receptors )73,74–76. Allosteric modulator. This mechanism involves regulation of the biological activity of the target by binding of a drug at a
site other than the binding site for the endogenous substrate and/or ligand (allosteric site) (for example, cinacalcet is an
allosteric modulator of the calcium receptor by binding to the allosteric site) 29,73.
Redox mechanisms
Redox is short for reduction–oxidation reactions in which the pharmacological response to the drug is a consequence of
electron transfer between the drug and a physiological target. For example, generation of hydroxyl radicals by verteporfin
is thought to contribute to its ability to damage cells, and the antiprotozoal activity of nitazoxanide is believed to be due
in part to interference with the pyruvate–ferredoxin oxidoreductase enzyme-dependent electron transfer reaction, which
is essential to anaerobic energy metabolism77–79.
worth noting that several of these NMEs (for example, NMEs that were developed as synthetic and/or modi-
nelarabine, azacitidine and nitazoxanide) were initial y fied versions of natural substances, or discovered by
described decades before their approval and before the screening such substances. A small fraction of the
development of new molecular screening approaches. first-in-class NMEs (5 out of 75) were developed as Many of these NMEs were also derived from natural synthetic versions of natural substances (that were substances, including the nucleoside analogues nelara- sometimes slightly modified), including the modified bine and azacitidine, the PGE1 derivative lubiprostone heparin fondaparinux, the porphyrin verteporfin, the and the fatty acid docosanol. Ziconotide, sirolimus and biopterin cofactor sapropterin, the porphyrin precur- retapamulin were derived from natural products. sor aminolevulinic acid and the acetylated homotaurine NATURE REVIEWS DRUG DISCOVERY
VOLUME 10 JULY 2011 511
2011 Macmillan Publishers Limited. All rights reserved acamprosate (FIG. 1c). Additionally, in some cases, effect and pharmaceutical properties36. In a programme natural substances provided starting points for small- that was aimed at discovering non-peptide endothelin molecule phenotypic screening (10 NMEs (FIG. 1a)) and receptor antagonists, a class of substituted arylsulphon- target-based discovery (3 NMEs (FIG. 1b)). In total, 18 amidopyrimidines was identified in a chemical com- out of the 50 (36%) first-in-class small-molecule NMEs pound library, which led to the discovery of bosentan37. originated from natural substances. These numbers are However, knowledge of the targets did not necessarily consistent with those reported by Newman and Cragg32 lead to an easy path to discovery. For example, although for the percentage of all medicines derived from natu- renin had been a clear target for the treatment of hyper- ral products, and the supposition that libraries that are tension for decades, the development of orally active derived from natural substances provide good chemi- renin inhibitors, which culminated in the discovery of cal starting points for optimization. For example, two the NME aliskiren38, was a major chal enge. NMEs that were discovered using a target-specific The development of six of the NMEs that were dis- strategy — ramelteon, which targets melatonin recep- covered by target-based approaches involved subsequent tors, and mifepristone, which is a progesterone receptor identification of their effective MMOA at the target that modulator — were derived from the modification of was selected for the initial screening strategies. The natural ligands. kinase inhibitors gefitinib, imatinib, sorafenib and suni- tinib block kinase activation; the HIV integrase inhibi- Target-based approaches. Target-based approaches tor raltegravir traps an intermediate complex between
led to the discovery of 17 of the 50 first-in-class small- the enzyme and nucleic acid; and maraviroc is an al os- molecule NMEs. Various approaches contributed to teric antagonist of the the CC chemokine receptor type these discoveries, and they are illustrated by the fol- 5. These inhibitors represent successes of the target- lowing examples. Sitagliptin, an inhibitor of the pro- based strategy, but they also highlight that the optimal tease dipeptidyl peptidase 4 (DPP4), was discovered MMOA at the target may not be apparent at the time of in an iterative discovery approach that was aimed at initiating the discovery strategy. For example, the HIV1 optimizing metabolic properties while retaining effi- integrase inhibitor raltegravir was only discovered after cacy33. A computer-assisted drug design strategy that several MMOAs had been investigated using different was based on the crystal structure of the influenza viral assay formats39,40. The diketo acids that led to the dis- neuraminidase led to the identification of zanamivir34. covery of raltegravir were eventual y found to block the A target-directed screening of microbial broths from strand transfer reaction, and this MMOA provided good soil organisms resulted in the discovery of a very potent, in vivo efficacy. The importance of the assay format in selective and irreversible inhibitor of pancreatic lipases, the identification of compounds with effective MMOAs which was named lipstatin (orlistat)35. Eltrombopag was at a chosen target is also illustrated by the discovery of identified by screening small-molecule libraries for the gefitinib, which is thought to act by sequestering the ability to activate a reporter molecule in thrombopoietin EGFR and its ligand into inactive receptor–ligand com- (TPO)-dependent cell lines. Lead compounds were ini- plexes41. Screening for activity in A431 vulval squamous tial y identified and then optimized for their biological carcinoma cel s was the assay format that led to the iden- tification of gefitinib and its MMOA42. The neurokinin-1 receptor antagonist aprepitant and the proteasome inhibitor bortezomib were original y dis- Box 2 Biochemical efficiency
covered with a view to targeting different indications to The dose of a drug required to achieve the desired physiological response depends on those that they were first approved for (Supplementary its biochemical efficiency10,11. This is defined as ‘binding affinity/functional response', information S2 (box)). Repositioning was also involved which is equivalent to K /EC (effector concentration for half-maximal response). Good for three of the NMEs that were discovered through biochemical efficiency enables efficacy at lower drug concentrations and increases the phenotypic assays: miglustat, azacitidine and nitisinone therapeutic index. It is a property of many approved medicines10,11.
(Supplementary information S2 (box)).
There are many factors that can influence the shift in dose–response curves between binding and functional assays, including: Biologics. Biologics that were approved under biolog-
• Pharmacokinetics and ADME (absorption, distribution, metabolism and excretion) ics license applications and large peptide molecules that were approved as NMEs (for example, enfuvirtide • Assay relevance (is the functional assay appropriate for the target? Are the assays and pegvisomant) accounted for 25 (33%) out of the technically accurate?) 75 first-in-class medicines (FIG. 1d). The biologics were • The involvement of the target in the functional readout and biology further categorized according to their pharmacological • The molecular mechanism of action (MMOA) action as described by Leader, Baca and Golan43. The Although all of these factors can and do contribute to the relationship between pharmacological actions of these biologics included binding affinity and the functional response, the role of the MMOA is not always enzyme replacement (agalsidase-β, alglucosidase alfa, considered. The concept of biochemical efficiency was introduced to quantify this galsulfase, idursulfase and laronidase), augmenting possibility10,11. When biochemical efficiency is used as a measure of an optimal MMOA, existing pathways (drotrecogin-α, exenatide, palifermin, it is important that the other mitigating factors are eliminated. For example, when evaluating biochemical efficiency, the assays must be run in the absence of serum pramlintide and romiplostim), providing a novel func- (or plasma) to eliminate the shift in IC (half-maximal inhibitory concentration) owing tion (rasburicase), interfering with a molecular activity to serum protein binding. (alemtuzumab, abatacept, anakinra, alefacept, bevaci- zumab, cetuximab, eculizumab, efalizumab, enfuvirtide, 512 JULY 2011 VOLUME 10
2011 Macmillan Publishers Limited. All rights reserved eltrombopag and the ‘peptibody' TPO receptor agonist romiplostim). Three first-in-class medicines also act by inhibiting vascular endothelial growth factor (VEGF) signalling: the VEGF-specific monoclonal antibody bevacizumab, and the small-molecule VEGF receptor kinase inhibitors sunitinib, which also inhibits KIT, and sorafenib, which was original y discovered on the basis of its inhibition of RAF kinase44.
Strategies according to disease area. Evaluation of the
discovery strategy by disease area showed that a pheno- typic approach was the most successful for central nerv- ous system disorders and infectious diseases, whereas target-based approaches were most successful in can- cer, infectious diseases and metabolic diseases (TABLE 2). Biologics accounted for most of the new medicines that act by modulating the immune system and 50% of the new medicines for cancer.
Discovery of follower drugs
There were 164 follower drugs, out of which 83 (51%) were discovered via target-based approaches, 30 (18%) via phenotypic assays and 31 (19%) were biologics (FIG. 2) (Supplementary information S1 (table)). Seven (4%) of the follower drugs were prodrugs or combinations of previously approved medicines. Considering NMEs alone, target-based approaches accounted for 62% (83 out of 133) of the small-molecule NMEs. The ratio of NMEs from target-based approaches to those from phe- notypic screening increased during the final 4 years of the analysis (FIG. 3b).
Molecular mechanism of action
The majority of small-molecule first-in-class NMEs had MMOAs that involved inhibiting the activity of enzymes or modulating receptors (FIG. 4). This trend is consistent with the findings of Imming and col eagues4 in their analysis Figure 1 Discovery strategies used to identify first-in-class medicines. The
of the nature and number of all drug targets. The phar- strategies that were used were categorized as being based on phenotypic screening (a),
macological responses were often achieved by binding to target-based strategies (b), synthetic versions of natural substances or very close
the target protein to elicit a positive or negative response.
derivatives (c) and biologics (d). Phenotypic strategies were further subdivided into
For the first-in-class NMEs and biologics, many intentional screening with random compound libraries or compound-specific libraries, different biochemical mechanisms mediated the drug optimization for molecular mechanism of action (MMOA) and serendipitous discoveries. response at the target (BOX 1). These included revers- Drugs that were identified through target-based screening that involved optimization of ible, irreversible and slow binding kinetics; competi- a natural ligand or identification of the optimal MMOA are highlighted. *Drugs that are tive, uncompetitive and noncompetitive interactions derived from natural substances. ‡These medicines have been withdrawn from the market. § between physiological substrates/ligands and drugs; as Although enfuvirtide and pegvisomant were approved as new molecular entities, for the well as inhibition, activation, agonism, partial agonism, purpose of this analysis they have been treated as biologics, given that they are both much larger than typical small-molecule drugs (see Supplementary information S2 (box)).
allosteric activation and induced degradation. Illustrative examples in which stimulation of a bio- logical response was achieved included: exenatide, omalizumab, pegvisomant and natalizumab); and deliv- which mimics a natural peptide (glucagon-like peptide 1 ering other compounds or proteins (denileukin diftitox (GLP1)) but is resistant to degradation by the protease and gemtuzumab). Thus, the majority of these biologics DPP4 (REF. 45); sitagliptin, which prevents degradation function by interfering with a molecular activity and, as of endogenous GLP1 by inhibiting DPP4 (REF. 33); and mentioned above, all of these biologics can be considered cinacalcet, which is an al osteric activator of the calcium- to have been discovered using a target-based approach.
sensing receptor29. Both first-in-class small molecule NMEs and bio- Illustrative examples in which inhibition or antago- logics were approved for two targets: EGFR kinase (the nism of a biological response was achieved included: small-molecule EGFR kinase inhibitor gefitinib and aprepitant, which is a competitive antagonist of the the EGFR-specific monoclonal antibody cetuximab) neurokinin-1 receptor46; orlistat, which is an irreversible and TPO (the small-molecule TPO receptor agonist inhibitor of lipase enzymes35; fulvestrant, which induces NATURE REVIEWS DRUG DISCOVERY
VOLUME 10 JULY 2011 513
2011 Macmillan Publishers Limited. All rights reserved Table 2 Discovery of first-in-class NMEs by therapeutic area
interaction. The second component requires a coupled biochemical event to create a transition away from mass- Disease area
Phenotypic
action equilibrium". It is also consistent with the opinions expressed by Imming and colleagues4 in their analysis Infectious diseases of drug targets, in which they emphasized the need to consider the dynamics of the drug–target interactions, because "in situations in which the dynamic actions of the drug substance stimulate, or inhibit, a biological process, it Central nervous system is necessary to move away from the descriptions of single proteins, receptors and so on and to view the entire signal chain as the target".
The diversity of the MMOAs of the new drugs ana- lysed in this article is not surprising. Physiological and drug mechanisms provide numerous examples of how diversity and complexity in the MMOA can provide NME, new molecular entity.
robust, selective and timely functional responses. For example, nuclear receptor ligands can induce ligand- specific structural conformations that can be uniquely degradation of the oestrogen receptor47; bevacizumab, coupled to the physiological system to provide func- which binds to VEGF, thereby preventing its interaction tionally selective responses14. Such conformational with its cell surface receptors48; and imatinib, which changes might not be detectable by X-ray crystallogra- inhibits the BCR–ABL kinase by stabilizing its inac- phy studies; indeed, this was recently demonstrated for tive conformation49 (sethe β -adrenergic receptor — there was no discernable (box)) for further details on these and other MMOAs).
difference in the conformation of the receptor when it Importantly, simple equilibrium binding at the target was bound to an inverse agonist or an antagonist50. The was rarely sufficient for the translation of drug binding functions of many enzymes are also regulated by specific to the target into a therapeutical y useful response — a structural changes. For example, receptor tyrosine kinase subtle aspect of drug action that is underappreciated. activation requires conformational changes that are These results are consistent with the previous conclu- facilitated by ligand binding51, and many proteases have sion10 that "two components are important to the MMOA. inhibitory domains that must be proteolytical y cleaved The first component is the initial mass action-dependent for enzyme activation52. Both kinetics and conformation contribute to the specificity of high-fidelity nucleotide incorporation by DNA polymerases. Kinetic analysis has shown that the nucleotide substrate-induced structural change has a key role in discriminating between cor- rect and incorrect base pairs, by governing whether a nucleotide will be retained and incorporated or rapidly A principal observation from this analysis is that the majority of small-molecule first-in-class NMEs that were discovered between 1999 and 2008 were first discovered using phenotypic assays (FIG. 2): 28 of the first-in-class NMEs came from phenotypic screening approaches, compared with 17 from target-based approaches. This is despite the current focus of small-molecule drug discov- ery on target-based approaches. A possible contributing factor to this trend could have been a lag time between Figure 2 The distribution of new drugs discovered
the introduction of new technologies and strategies, and between 1999 and 2008, according to the discovery
their impact in terms of the number of approved first- strategy. The graph illustr 0CVWT
in-class NMEs derived from these approaches. However, entities (NMEs) in each category. Phenotypic screening was such a lag is not strongly apparent in a comparison of the the most successful approach for first-in-class drugs, cumulative number of NMEs from the two approaches whereas target-based screening was the most successful for during the period analysed (FIG. 3a). follower drugs during the period of this analysis. The total This observation, along with further analysis of the number of medicines that were discovered via phenotypic MMOA of the first-in-class NMEs, leads us to propose assays was similar for first-in-class and follower drugs — 28 and 30, respectively — whereas the total number of that a focus on target-based drug discovery, without medicines that were discovered via target-based screening accounting sufficiently for the MMOA of small-mole- was nearly five times higher for follower drugs versus cule first-in-class medicines, could be a technical reason first-in-class drugs (83 to 17, respectively). contributing to high attrition rates. Our reasoning for 514 JULY 2011 VOLUME 10
2011 Macmillan Publishers Limited. All rights reserved 0WODGTQH0/'U                      Figure 3 Cumulative distribution of new drugs by discovery strategy. a First-in-class drugs. A lag is not strongly
apparent in a comparison of the cumulative number of small-molecule new molecular entities (NMEs) that were
discovered from the different approaches during the period ana lysed. b Follower drugs. For follower drugs, the ratio
of small-molecule NMEs discovered through target-based screening to those discovered through phenotypic screening
appears to increase in the second half of the time period.
this proposal is that the MMOA is a key factor for the approaches should also be noted. First, it will often be success of all approaches, but is addressed in different necessary to characterize the MMOA of active molecules ways and at different points in the various approaches. that are identified in phenotypic screens to aid the opti- In the more common target-based approach, drug mization of a drug candidate, but substantial progress has discovery is generally hypothesis-driven, and there are been made in approaches to achieve this — for example, at least three hypotheses that must be correct to result approaches based on RNA interference54,55. Second, phe- in a new drug. The first hypothesis, which also applies notypic assays are often lower in throughput than stand- to other discovery approaches, is that activity in the ard target-based assays, although considerable progress preclinical screens that are used to select a drug candi- has also been made in recent years to automate such date will translate effectively into clinically meaningful assays and increase their throughput56–58.
activity in patients. The other two hypotheses are that Final y, as has often been noted in reviews of the role the target that is selected is important in human disease of natural products in drug discovery32,59, discovery and that the MMOA of drug candidates at the target in strategies that are based on natural substances have an question is one that is capable of achieving the desired inherent advantage: the biology, target and MMOA are biological response. Successful target-based discov- often likely to be have been optimized already through ery of first-in-class drugs with tolerable safety profiles evolution, and so modifying such substances can be a requires the time and resources to investigate all three fruitful approach. Similarly, some of the biologics that hypotheses. In particular, the importance of hypoth- have been approved are harnessing endogenous mecha- esis testing to identify an appropriate MMOA may be nisms in a rational way — for example, by providing a an underappreciated challenge that — if neglected — natural protein that is reduced in a given disease state, could contribute to increased attrition rates for such as is the case for enzyme replacement therapies for approaches. In other words, it is clearly difficult to lyosomal storage disorders. In other cases though, it is rationally identify the specific molecular interactions apparent that the precise MMOA of biologics might also from all of the potential dynamic molecular interac- be important in their biological effects, as illustrated by tions that will contribute to an optimal MMOA. Thus, the differences in the properties of two monoclonal the key biochemical nuances that are important for the antibodies that target CD20 on B cells60 — rituximab translation of the molecular interaction (between a drug and ofatumumab — although neither of these were and the target) to an optimal pharmacological response approved in the 10-year period we studied. Telling et could be missed with target-based approaches. al.60 conclude that the recognition of a novel epitope By contrast, in the case of phenotypic-based screening cooperates with a slow off-rate in determining the activ- approaches, assuming that a screening assay that trans- ity of CD20 monoclonal antibodies in the activation of lates effectively to human disease is available or can be complement and the induction of tumour cell lysis.
identified, a potential key advantage of this approach over The importance of the MMOA is further supported target-based approaches is that there is no preconceived by the evolution of the MMOA within drug classes, from idea of the MMOA and target hypothesis. This could the first-in-class molecule to the best-in-class molecule, considerably aid the identification of molecules with which is not widely appreciated. For example, in some appropriate targets (and possibly multiple targets) and cases in which there is no mechanism-based toxicity, the MMOAs, which might be less likely to emerge rapidly, if evolution of drugs in a given class towards the best-in- at al , from pursuing a focused target-based hypothesis. class has been associated with slower dissociation rates However, two limitations of phenotypic-based screening at the target. This has been observed with antihistamines NATURE REVIEWS DRUG DISCOVERY
VOLUME 10 JULY 2011 515
2011 Macmillan Publishers Limited. All rights reserved C #ȭGEVGP [OGCEVKXKV[
GP [OGKPJKDKVQTU Figure 4 Activities of first-in-class small-molecule new molecular entities. Nearly half (22 out of 50) of the
first-in-class small-molecule drugs that were approved between 1999 and 2008 affected enzyme activity (a). The
molecular mechanisms of action (MMOAs) of these drugs included reversible, irreversible, competitive and
noncompetitive inhibition, blocking activation and stabilizing the substrate. The next largest group of targets (10 drugs)
were receptors (b), most of which were G protein-coupled receptors. Their MMOAs included agonism, partial agonism,
antagonism and allosteric modulation. Two drugs — fulvestrant and mifepristone — targeted nuclear receptors. Four of
the drugs targeted ion channel activity (c); their MMOAs included uncompetitive antagonism and partial agonism. One
drug, ezetimibe, targeted the activity of a transporter (d). The remaining drugs had other activities (e), or unclear targets
or MMOAs (f). Of the NMEs with other activities, two had a unique MMOA: verteporfin, a porphyrin that catalyses the
generation of reactive oxygen species and is used for photodynamic therapy; and daptomycin, which has an MMOA that
involves disruption of bacterial membranes. For details of the discovery and activities of each drug, see Supplementary
information S2 (box). *Sirolimus binds to the protein FKBP12 and the sirolimus–FKBP12 complex inhibits the kinase
activity of mammalian target of rapamycin, whereas the other four kinase inhibitors target receptor tyrosine kinases.
‡Bortezomib inhibits the 26S proteasome — a multiprotein complex — by inhibiting the chymotryptic-like activity of the
proteasome. §Fulvestrant acts by promoting receptor degradation.
(desloratadine)61, antimuscarinics (tiotropium)62 drugs was initiated before first-in-class approval. The and angiotensin receptor blockers (candesartan)63,64. authors66 concluded that "drug development can often Conversely, in drug classes with mechanism-based tox- be characterized as a race in which several firms pursue icity, MMOAs that increase the therapeutic index have investigational drugs with similar chemical structures been identified, as illustrated by SERMs such as ralox- or with the same mecha 0CVWT
m of a XKGYU
ctio  
efore an XGT[
ifene14,65. A decrease in the number of iterations required in the class obtains regulatory marketing approval". to identify an optimal MMOA for first-in-class drugs That is, it appears that once a mechanism of action or could accelerate lead discovery and reduce late-stage a chemical class with the potential to be developed into attrition, thereby increasing R&D productivity.
a drug is discovered, multiple organizations within the With regard to the discovery of follower drugs, the pharmaceutical industry may pursue it vigorously. In opposite trend was seen compared to first-in-class drug discovery, this race may contribute to the escalat- drugs, with target-based approaches accounting for 83 ing costs, as there is only room for a few drugs in a class. (51%) of these NMEs and phenotypic-based approaches Additionally, the analysis by DiMasi and Faden66 only accounting for 30 (18%) NMEs. The reversal of the captures the drug classes that have been approved; if trend is presumably the result of drug developers tak- the costs for organizations involved in a race around a ing advantage of knowledge of a previously identified hypothesis that was later proven to be incorrect are also MMOA to effectively use target-based tools. The tim- considered, the total costs could be substantial y higher. ing of the use of these tools may also be important. A The increased reliance on hypothesis-driven target- recent report by DiMasi and Faden66 on fol ower drugs based approaches in drug discovery has coincided with shows that research on a large percentage of follower the sequencing of the human genome and an apparent 516 JULY 2011 VOLUME 10
2011 Macmillan Publishers Limited. All rights reserved belief by some that every target can provide the basis the success of drugs, which has also been postulated to for a drug. As such, research across the pharmaceutical be an underlying factor for current attrition rates67.
industry as well as academic institutions has increas- Reducing the impact of technical uncertainty on the ingly focused on targets, arguably at the expense of the later, more costly stages of drug development through a development of preclinical assays that translate more ‘quick win/fast fail' strategy has been proposed as a solu- effectively into clinical effects in patients with a specific tion to the current problems with R&D productivity2. disease. In our analysis, we found that there are numerous However, this strategy does not address the key issues diverse MMOAs for approved new first-in-class drugs, that contribute to the greater technical uncertainty but drug discovery at present appears to be dominated by and associated risk of failure. Our analysis leads us to a ‘one size fits al ' approach, in which drugs are optimized conclude that the identification of an optimal MMOA for binding affinity with less consideration for binding has been a key factor contributing to the success of kinetics and conformation. For optimal application of phenotypic screening in the discovery of the first-in- target-based approaches, it is important to consider how class NMEs in the 10-year period we studied. Thus, we efficiently binding is coupled to the response (BOX 2). consider that technical risk and, consequently, overall However, the molecular descriptors for the coupling fac- attrition in drug development could be decreased for tors may not be accurately captured by only consider- first-in-class drugs through the development and greater ing binding affinity. Furthermore, an excessive focus on use of translational phenotypic assays, and by considering affinity at a given target could lead to compromises being diverse MMOAs when using a target-based, hypothesis- made in pharmacokinetic properties that are critical for driven strategy.
Munos, B. Lessons for 60 years of pharmaceutical 15. Roth, G. J. & Majerus, P. W. The mechanism of the 31. Valentino, D. et al. A selective N-type calcium channel innovation. Nature Rev. Drug Discov. 8, 959–968
effect of aspirin on human platelets. I. Acetylation of a antagonist protects against neuronal loss after global particulate fraction protein. J. Clin. Invest. 56,
cerebral ischemia. Proc. Natl Acad. Sci. USA 90,
Paul, S. M. et al. How to improve R.&D productivity: 624–632 (1975).
7894–7897 (1993).
the pharmaceutical industry's grand challenge. Nature 16. Majerus, P. W., Broze, G. J. Jr, Miletich, J. P. & Tollefsen, 32. Newman, D. J. & Cragg, G. M. Natural products as Rev. Drug Discov. 9, 203–214 (2010).
D. M. in Goodman & Gilman's The pharmacological sources of new drugs over the last 25 years. J. Nat. Lindsay, M. A. Target discovery. Nature Rev. Drug basis of therapeutics. (eds Hardman, J. G. & Limbird, L. Prod. 70, 461–477 (2007).
Discov. 2, 831–838 (2003).
E.)1353 (McGraw-Hill, New York, 1996).
Describes the successes of natural products as a
Imming, P., Sinning, C. & Meyer A. Drugs, their targets 17. Copeland, R. A., Pompliano, D. L. & Meek, T. D. source for new drugs.
and the nature and number of drug targets. Nature Drug-target residence time and its implications for 33. Deacon, C. F. Therapeutic strategies based on Rev. Drug Discov. 5, 821–834 (2006).
lead optimization. Nature Rev. Drug Discov. 5,
glucagon-like peptide-1. Diabetes 53, 2181–2189
Overington, J. P., Al-Lazikani, B. & Hopkins, A. L. How 730–739 (2006).
many drug targets are there? Nature Rev. Drug 18. Timmino, P. J. & Copeland, R. A. Residence time of 34. Von Itzstein, M. et al. Rational design of potent receptor–ligand complexes and its effect on biological sialidase-based inhibitors of influenza virus Williams, M. Systems and integrative biology as function. Biochemistry 47, 5481–5492 (2008).
replication. Nature 363, 418–423 (1993).
alternative guises for pharmacology: prime time for an 19. Lu, H. & Tonge, P. J. Drug-target residence time: 35. Weibel, E. K., Hadvary, P., Hochuli, E., Kupfer, E. & iPharm concept? Biochem. Pharmacol. 70,
critical information for lead optimization. Curr. Opin. Lengsfeld, H. Lipstatin, an inhibitor of pancreatic Chem. Biol. 14, 1–8 (2010).
lipase produced by Streptomyces toxytricini. Flordellis, C. S., Manolis, A. S., Paris, H. & Karabinis, A. 20. Johnson, D. S., Weerapana, E. & Cravatt, B. F. 1. Producing organism, fermentation, isolation and Rethinking target discovery in polygenic diseases. Strategies for discovering and derisking covalent, biological activity. J. Antibiot. 40, 1081–1086
Curr. Top. Med. Chem. 6, 1791–1798 (2006).
irreversible enzyme inhibitors. Future Med. Chem. 2,
Urban, J. D. et al. Functional selectivity and classical 949–964 (2010).
36. Kluter, D. J. New thrombopoietic growth factors. concepts of quantitative pharmacology J. Pharmacol. 21. Ohlson, S. Designing transient binding drugs: a new Blood 109, 4607–4616 (2007).
Exp. Ther. 320, 1–13 (2007).
concept for drug discovery. Drug Discov. Today 13,
37. Remuzzi, G. et al. New therapeutics that antagonize Formalizes the concept of functional selectivity,
433–439 (2008).
endothelin: promises and frustrations. Nature Rev. whereby multiple unique ligands can bind to one
22. Lipton, S. A. Paradigm shift in neuroprotection by Drug Discov. 1, 986–1001 (2002).
receptor to initiate different responses.
NMDA receptor blockade: Memantine and beyond. 38. Wood, J. M. et al. Structure-based design of aliskiren, Kenakin, T. & Miller, L. J. Seven transmembrane Nature Rev. Drug Discov. 5, 160–170 (2006).
a novel orally effective renin inhibitor. Biochem. receptors as shapeshifting proteins: the impact of 23. Lipton, S. A. Pathology activated therapeutics for Biophys. Res. Commun. 308, 698–705 (2003).
allosteric modulation and functional selectivity on neuroprotection. Nature Rev. Neurosci. 8, 803–808
39. Pommier, Y. et al. Integrase inhibitors to treat HIV/ drug discovery. Pharmacol. Rev. 62, 265–304
AIDS. Nature Rev. Drug Discov. 4, 236–248 (2005).
Describes the principle that drugs should be
40. Espeseth, A. S. et al. HIV-1 integrase inhibitors that 10. Swinney, D. C. Biochemical mechanisms of drug activated by the pathological state that they are
compete with the target DNA substrate define a action: what does it take for success? Nature Rev. intended to inhibit.
unique strand transfer conformation for integrase. Drug Discov. 3, 801–808 (2004).
24. Changeux, J. P. Allosteric receptors: from electric Proc. Natl Acad. Sci. USA 97, 11244–11249
Describes how the MMOA influences the
organ to cognition. Annu. Rev. Pharmacol. Toxicol. 50,
therapeutic index and utility of a medicine and
1–38 (2010).
41. Lichtner, R. B. et al. Signaling-inactive epidermal introduces biochemical efficiency as a metric to
25. Conn, J. P., Christopoulos, A. & Lindsley, C. W. growth factor receptor/ligand complexes in intact quantify this influence.
Allosteric modulators of GPCRs: a novel approach for carcinoma cells by quinazoline kinase inhibitors. 11. Swinney, D. C. Biochemical mechanisms of new the treatment of CNS disorders. Nature Rev. Drug Cancer Res. 61, 5790–5795 (2001).
molecular entities (NMEs) approved by United States Discov. 8, 41–54 (2009).
42. Barker, A. J. et al. Studies leading to the identification FDA during 2001–2004: mechanisms leading to 26. Hanck, D. A. et al. Using lidocaine and benzocaine to of ZD1830 (IressaTM): an orally active, selective optimal efficacy and safety. Curr. Top. Med. Chem. 6,
link sodium channel molecular conformations to state- epidermal growth factor receptor tyrosine kinase 461–478 (2006).
dependent antiarrhythic drug affinity. Circ. Res. 105,
inhibitor targeted to the treatment of cancer. Bioorg. 12. Swinney, D. C. Applications of binding kinetics to drug 492–499 (2009).
Med. Chem. Lett. 11, 1911–1914 (2001).
discovery: translation of binding mechanism to 27. Butterworth, J. F. & Strichartz, G. R. Molecular 43. Leader, B., Baca, Q. J. & Golan, D. E. Protein clinically differentiated therapeutic responses. Pharm. mechanisms of local anesthesia: a review. therapeutics: a summary and pharmacological Med. 22, 23–34 (2008).
Anesthesiology 72, 711–734 (1990).
classification. Nature Rev. Drug Discov. 7, 21–39
13. Yun, C.H. et al. The T790M mutation in EGFR kinase 28. Wilson, D. N. et al. The oxazolidinone antibiotics causes drug resistance by increasing the affinity for ATP. perturb the ribosomal peptidyl-transferase center and 44. Wilhelm, S. et al. Discovery and development of Proc. Natl Acad. Sci. USA 105, 2070–2075 (2008).
effect tRNA positioning. Proc. Natl Acad. Sci. USA sorafenib: a multikinase inhibitor for treating cancer. Provides an illustration of how drug resistance
105, 13339–13344 (2008).
Nature Rev. Drug Discov 5, 835–844 (2006).
could be overcome through an understanding of
29. Nemeth, E. F. Misconceptions about calcimimetics. 45. Goke, R. et al. Exendin-4 is a high potency agonist and the MMOA.
Ann. NY Acad. Sci. 1068, 471–476 (2006).
truncated exendin-(9–39)-amide an antagonist at the 14. Brzozowski, A. M. et al. Molecular basis of agonism Discusses lessons learned in the discovery of
glucagon-like peptide 1-(7–36)-amide receptor of and antagonism in the oestrogen receptor. Nature cinacalcet, with emphasis on the importance of
insulin-secreting β-cells. J. Biol. Chem. 268,
389, 753–758 (1997).
using an understanding of physiology.
Shows structurally how agonists and antagonists
30. Salisbury, B. G. et al. Hypocholesterolemic activity of a 46. Alvaro, G. & Di Fabio, R. Neurokinin 1 receptor bind at the same site but with different binding
novel inhibitor of cholesterol absorption, SCH 48461. antagonists — current prospects. modes that result in different responses.
Athlerosclerosis 115, 45–63 (1995).
Curr. Opin. Drug Discov. Dev. 10, 613–621 (2007).
NATURE REVIEWS DRUG DISCOVERY
VOLUME 10 JULY 2011 517
2011 Macmillan Publishers Limited. All rights reserved 47. Wijayaratne, A. L. & McDonnell, D. P. The human 73. Kenakin, T. Pharmacologic Analysis of Drug‑Receptor 94. Stenoien, D. L. et al. FRAP reveals that mobility of estrogen receptor-α is a ubiquitinated protein whose Interaction 242–395 (Lippincott-Raven Publishers, oestrogen receptor-α is ligand- and proteasome- stability is affected differentially by agonists, antagonists, Philadelphia, 1997). dependent. Nature Cell Biol. 3, 15–23 (2001).
and selective estrogen receptor modulators. J. Biol. 74. Burris K. D. et al. Aripiprazole, a novel antipsychotic, 95. Glower, A. J., Noyer, M., Verloes, R., Gobert, J. & Chem. 276, 35684–35692 (2001).
is a high-affinity partial agonist at human dopamine Wulfert, E. UCB L059, a novel anti-convulsant drug: 48. Ferrara, N. et al. Discovery and development of D2 receptors. J. Pharmacol. Exp. Ther. 302,
pharmacological profile in animals. Eur. J. Pharmacol. bevacizumab, an anti-VEGF antibody for treating 381–389 (2002).
222, 193–203 (1992).
cancer. Nature Rev. Drug Discov. 3, 391–400
75. Pulvirenti, L. & Koob, G. F. Dopamine receptor 96. Shinabarger, D. Mechanism of action of the agonists, partial agonists and psychostimulant oxazolidinone antibacterial agents. Expert Opin. 49. Capdeville, R., Buchdunger, E., Zimmermann, J. & addiction. Trends Pharmacol. Sci. 15, 374–379
Investig. Drugs 8, 1195–1202 (1999).
Matter A. Glivec (ST571, imatinib), a rationally 97. Brickner, S. J. Oxazolidinone antibacterial agents. developed, targeted anticancer drug. Nature Rev. 76. Coe, J. E. et al. Varenicline: an α4β2 nicotinic receptor Curr. Pharm. Des. 2, 175–194 (1996).
Drug. Discov. 1, 493–502 (2002).
partial agonist for smoking cessation. J. Med. Chem. 98. Cuppoletti J. et al. Recombinant and native intestinal 50. Wacker, D. et al. Conserved binding mode of human 48, 3474–3477 (2005).
cell ClC-2 Cl– channels are activated by RU-0211. β2 adrenergic receptor inverse agonists and Describes the thinking that led to a
Gastroenterology 122, A538 (2002).
antagonist revealed by X-ray crystallography. J. Am. mechanism-based search for a partial agonist of
99. Cuppoletti, J. et al. SPI-0211 activates T84 cell Chem. Soc. 132, 11443–11445 (2010).
chloride transport and recombinant human ClC-2 51. Lemmon, M. A. & Schlessinger, J. Cell signaling by 77. Rickter, A. M. et al. Preliminary studies on a more chloride currents. Am. J. Physiol. 287, C1173–C1183
receptor tyrosine kinases. Cell 141, 1117–1134
effective phototoxic agent than hematoporphyrin. J. Natl Cancer Inst. 79, 1327–1332 (1987).
100. Peña-Münzenmayer, G. et al. Basolateral localization 52. Li, P. et al. Cytochrome c and dATP-dependent 78. Hemphill, A., Mueller, J. & Esposito, M. Nitazoxanide, of native ClC-2 chloride channels in absorptive formation of Apaf-1/caspase-9 complex initiates an a broad-spectrum thiazolide anti-infective agent for intestinal epithelial cells and basolateral sorting apoptotic protease cascade. Cell 91, 479–489.
the treatment of gastrointestinal infections. Expert encoded by a CBS-2 domain di-leucine motif. J. Cell 53. Johnson, K. A. Role of induced fit in enzyme Opin. Pharmacother. 7, 953–964 (2006).
Sci. 118, 4243–4252 (2005).
specificity: a molecular forward/reverse switch. J. Biol. 79. Rossignol, J. F. & Maisonneuve, H. Nitazoxanide in the 101. Parsons, C. G., Danysz, W. & Quack, G. Memantine is a Chem. 283, 26297–26301 (2008).
treatment of Teania saginata and Hymenolepis nana clinically well-tolerated N-methyl-d-aspartate (NMDA) 54. Sigoillot, F. D. & King, R. W. Vigilance and validation: infections. Am. J. Trop. Med. Hyg. 33, 511–512
receptor antagonist — a review of the preclinical data. keys to success in RNAi screening. ACS Chem. Biol. 6,
Neuropharmacology 38, 735–767 (1999).
47–60 (2011).
80. Lewis, D. A. & Lieberman, J. A. Catching up on 102. Gerzon, K. et al. The adamantyl group in medicinal 55. Hergenrother, P. J. & Palchaudhuri, R. Transcript schizophrenia: natural history and neurobiology. agents. I. Hypoglycemic N-arylsulfonyl-N′- profiling and RNA interference as tools to identify Neuron 28, 325–334 (2000).
adamantylureas. J. Med. Chem. 6, 760–763 (1963).
small molecule mechanisms and therapeutic potential. 81. Yasuda, Y. et al. 7-[3-[4-(2,3 dimethylphenyl) 103. Bormann, J. Memantine is a potent blocker of ACS Chem. Biol. 6, 21–33 (2011).
piperazinyl] propoxy]-2(1H)-quinolinone (OPC-4392), N-methyl-d-aspartate (NMDA) receptor channels. Eur. 56. Macarron, R. et al. Impact of high-throughput a presynaptic dopamine receptor agonist and J. Pharmacol. 166, 591–592 (1989).
screening in biomedical research. Nature Rev. Drug. postsynaptic D2 receptor antagonist. Life Sci. 42,
104. Platt, F. M., Neises, G. R., Dwek, R. A. & Butters, T. D. Discov. 10, 188–195 (2011).
1941–1954 (1988).
N-butyldeoxynojirimycin is a novel inhibitor of 57. Pruss, R. M. Phenotypic screening strategies for 82. Kikuchi, T. et al. 7-(4-[4-(2,3-dichlorophenyl) glycolipid biosynthesis. J. Biol. Chem. 269,
neurodegenerative diseases: a pathway to discover 8362–8365 (1994).
novel drug candidates and potential disease targets or quinolinone (OPC-14597), a new putative 105. Pastores, G. M. & Barnett, N. L. Substrate reduction mechanisms. CNS Neurol. Disord. Drug Targets 9,
antipsychotic drug with both presynaptic dopamine therapy: miglustat as a remedy for symptomatic 693–700 (2010).
autoreceptor agonistic activity and postsynaptic D2 patients with Gaucher disease type 1. Expert Opin. 58. Bickle, M. The beautiful cell: high-content screening in receptor antagonistic activity. J. Pharmacol. Exp. Ther. Investig. Drugs. 12, 273–281 (2003).
drug discovery. Anal. Bioanal. Chem. 398, 219–226
274, 329–336 (1995).
106. Hu, S. et al. Pancreatic β-cell KATP channel activity 83. Oshiro, Y. et al. Novel antipsychotic agents with and membrane-binding studies with nateglinide: a 59. Mayer, A. M. et al. The odyssey of marine dopamine autoreceptor agonist properties: synthesis comarison with sulfonylureas and repaglinide. pharmaceuticals: a current pipeline perspective. and pharmacology of 7-[4-(4-phenyl-1-piperazinyl) J. Pharmacol. Ther. 293, 444–452 (2000).
Trends Pharmacol. Sci. 31, 255–265 (2010).
107. Shinkai, H. et al. N-acylphenylanalines and related 60. Telling, J. L. et al. The biological activity of human J. Med. Chem. 41, 658–667 (1998).
compounds. A new class of oral hypoglycemic agents. CD20 monoclonal antibodies is linked to unique 84. Inoue, T., Domae, M., Yamada, K. & Furukawa, T. J. Med. Chem. 31, 2092–2097 (1988).
epitopes on CD20. J. Immunol. 177, 362–371
Effects of the novel antipsychotic agent 108. Shinkai, H. et al. N-acylphenylanalines and related compounds. A new class of oral hypoglycemic agents. 61. Anthes, J. C. et al. Biochemical characterization of J. Med. Chem. 32, 1436–1441 (1989).
desloratadine, a potent antagonist of the human on prolactin release from the rat anterior pituitary 109. Parker, W. B. et al. Purine nucleoside analogues in histamine H receptor. Eur. J. Pharmacol. 449,
gland. J. Pharmacol. Exp. Ther. 277, 137–143
development for the treatment of cancer. Curr. Opin. 229–237 (2002).
Investig. Drugs 5, 592–596 (2004).
62. Disse, B. et al. Tiotropium (Spiriva): mechanistic 85. Egger, G., Liang, G., Aparicio, A. & Jones, P. A. 110. Rodriguez, C. O. et al. Mechanisms for T-cell selective considerations and clinical profile in obstructive lung Epigenetics in human disease and prospects for cytotoxicity of arabinosylguanine. Blood 102,
disease. Life Sci. 64, 457–464 (1999).
epigenetic therapy. Nature 429, 457–463
1842–1848 (2003).
63. Vauquelin, G., Fierens, F. & Van Liefde, I. Long-lasting 111. Krenitsky, T. A. et al. An enzymatic synthesis of AT1 receptor binding and protection by candesartan: 86. Satistowska-Schroder, E. T., Kerridge, D. & Perry, H. purine-d-arabinonucleosides. Carbohydr. Res. 97,
comparison to other biphenyl-tetrazole sartans. Echinocandin inhibition of 1,3-β-D-glucan synthase 139–146 (1981).
J. Hypertens. 24, S23–S30 (2006).
from Candida albicans. FEBS Lett. 173, 134–138
112. Lambe, C. U. et al. 2-amino-6-methoxypurine 64. Fuchs, B. et al. Comparative pharmacodynamics and arabinoside: an agent for T-cell malignancies. Cancer pharmacokinetics of candesartan and losartan in man. 87. Nishi, T. et al. Studies on 2-oxoquinoline derivatives as Res. 55, 3352–3356 (1995).
J. Pharm. Pharmacol. 52, 1075–1083 (2000).
blood platelet aggregation inhibitors. I. Alkyl 113. Gandhi, V., Keating, M. J., Bate, G. & Kirkpatrick, P. 65. Gustafsson, J. A. Raloxifene: magic bullet for heart Nelarabine. Nature Rev. Drug Discov. 5, 17–18 (2006).
and bone? Nature Med. 4, 152–153 (1998).
and related compounds. Chem. Pharm. Bull. 31,
114. Lock, E. A. et al. From toxicological problem to 66. DiMasi, J. A. & Fadon, L. B. Competitiveness in follow- 798–810 (1983).
therapeutic use: the discovery of the mode of action on drug R&D: a race or imitation? Nature Rev. Drug 88. Tally, F. P. & DeBruin M. F. Development of daptomycin of 2-(2-nitro-4-trifluoromethylbenzoyl)-1, Discov. 10, 1–5 (2011).
for Gram-positive infections. J. Antimicrob. Chemother. 3-cyclohexanedione (NTBC), its toxicology and 67. Gleeson, M. P., Hersey, A., Montanari, D. & 46, 523–526 (2000).
development as a drug. J. Inherit. Metab. Dis. 21,
Overington, J. Probing the links between in vitro 89. Stock, C, C. & Francis, T. J. The inactivation of the 498–506 (1998).
potency, ADMET and physiocochemical parameters. virus of epidemic influenza by soaps. J. Exp. Med. 71,
115. Kavana, M. & Moran, G. R. Interaction of Nature Rev. Drug Discov. 10, 197–208 (2011).
661–681 (1940).
(4-hydroxyphenyl)pyruvate dioxygenase with the 68. Fersht, A. Enzyme Structure and Mechanism 88–109 90. Snipes, W., Person, S., Keller, G., Taylor, W. & Keith, A. specific inhibitor 2-[2-Nitro-4-(trifluoromethyl) (W. H Freeman and Company, New York,1985).
Inactivation of lipid-containing viruses by long-chain benzoly]-1,3-cyclohexanedione. Biochemistry 42,
69. Issa, J. P. J., Kantarjian, H. M. & Kirkpatrick, P. alcohols. Antimicrob. Agents Chemother. 11, 98–104
Azacitidine. Nature Rev. Drug Discov. 4, 275–276
116. Brownlee, J. M., Johnson-Winters, K., Harrison, D. H. T. 91. Sands, J., Auperin, D. & Snipes, W. Extreme sensitivity & Moran, G. R. Structure of the ferrous form of 70. Martel, R. R., Klicius, J. & Galet, S. Inhibition of of enveloped viruses including herpes-simplex, to 4-(hydroxyphenyl)pyruvate dehydrogenase from immune response by rapamycin, a new antifungal long-chain unsaturated monglycerides and alcohols. Streptomyces avermitilis in complex with the antibiotic. Can. J. Physiol. Pharmacol. 55, 48–51
Antimicrob. Agents Chemother. 15, 67–73
therapeutic herbicide, NTBC. Biochemistry 43,
6370–6377 (2004).
71. Bartizal, K. et al. In vitro antifungal activities and 92. Katz, D. H., Marcelletti, J. F., Khalil, M. H., Pope, L. E. 117. Yanagihara, Y., Kasai, H., Kawashima, T. & Shida, T. in vivo efficacies of 1,3-β-glucan synthesis inhibitors & Katz, L. E. Antiviral activity of 1-docosanol, an Immunopharmacological studies on TBX, a new L671,329, L646,991, tetrahydroechinocandin B, and inhibitor of lipid-enveloped viruses including herpes antiallergic drug (1). Inhibitory effects on passive L687,781, a papulacandin. Antimicrob. Agents simplex. Proc. Natl Acad. Sci. USA 88, 10825–10829
cutaneous anaphylaxis in rats and guinea pigs. Chemother. 36, 1648–1657 (1992).
Jpn. J. Pharmacol. 48, 91–101 (1988).
72. Uchikawa, O. et al. Synthesis of a novel series of 93. Wakeling, A. E., Dukes, M. & Bowler, J. A potent 118. Gaffney, S. M. Ranolazine, a novel agent for chronic tricyclic indan derivatives as melatonin receptor specific pure antiestrogen with clinical potential. stable angina. Pharmacotherapy 26, 135–142
agonists. J. Med. Chem. 45, 4222–4239 (2002).
Cancer Res. 51, 3867–3873 (1991).
518 JULY 2011 VOLUME 10
2011 Macmillan Publishers Limited. All rights reserved 119. Chaitman, B. R. et al. Anti-ischemic effects and 136. Dorr, P. et al. Maraviroc (UK-427,857), a potent, 154. Sima, A. A. F., Kennedy, J. C., Blakeslee, D. & long-term survival during ranolazine monotherapy orally bioavailable, and selective small-molecule Robertson, D. M. Experimental porphyric neuropathy: in patients with chronic severe angina. J. Am. Coll. inhibitor of chemokine receptor CCR5 with broad- a preliminary report. Can. J. Neurol. Sci. 8 105–114
Cardiol. 43, 1375–1382 (2004).
spectrum anti-human immunodeficiency virus type 1 120. Chaitman, B. R. et al. Effects of ranolazine with activity. Antimicrob. Agents Chemother. 49,
155. Choay, J. et al. Structure–activity relationship in atenolol, amlodipine, or diltiazem on exercise 4721–4732 (2005).
heparin: a synthetic pentasaccharide with high affinity tolerance and angina frequency in patients with severe 137. Watson, C., Jenkinson, S., Kazmierski, W. & Kenakin, T. for antithrombin III and eliciting high anti-factor Xa chronic angina: a randomized controlled trial. JAMA The CCR5 receptor-based mechanism of action of activity. Biochem. Biophys. Res. Commun. 116,
291, 309–316 (2004).
873140, a potent allosteric noncompetitive HIV entry 492–499 (1983).
121. Antzelevitch, C. et al. Electrophysiological effects of inhibitor. Mol. Pharmacol. 67, 1268–1282 (2005).
156. Hirsh, J. et al. Heparin and low-molecular-weight ranolazine, a novel antianginal agent with antiarrhythmic 138. Pincus, G. (ed.) The Control of Fertility. 128–138 heparin: mechanisms of action, pharmacokinetics, properties. Circulation 110, 904–910 (2004).
(Academic Press, New York, 1965).
dosing, monitoring, efficacy, and safety. Chest 119,
122. Hunt, E. Pleuromutilin antibiotics. Drugs Future 25,
139. Belanger, A., Philibert, D. & Teutsch, G. Regio and 64S–94S (2001).
1163–1168 (2000).
stereospecific synthesis of 11β-substituted 157. Walenga, J. M. et al. Development of a synthetic 123. Jain, K. K. An assessment of rufinamide as an anti- 19-norsteroids. Steroids 37, 361–382 (1981).
heparin pentasaccharide: fondaparinux. Turk. epileptic in comparison with other drugs in clinical 140. Mahajan, D. K. & London, S. N. Mifepristone J. Haematol. 19, 137–150 (2002).
development. Expert Opin. Investig. Drugs 9,
(RU486): a review. Fertil. Steril. 68, 967–976 (1997).
158. Blau, N. & Erlandsen, H. The metabolic and molecular 829–840 (2000).
141. Raaijmakers, H. C., Versteegh, J. E. & Uitdehaag, J. C. bases of tetrahydrobiopterin-responsive phenylalanine 124. Rogawski, M. A. Diverse mechanisms of antiepileptic The X-ray structure of RU486 bound to the progesterone hydroxylase deficiency. Mol. Genet. Metab. 82,
drugs in the development pipeline. Epilepsy Res. 69,
receptor in a destabilized agonistic conformation. J. Biol. 101–111 (2004).
273–294 (2006).
Chem. 284, 19572–19579 (2009).
159. Niederwieser, A. & Curtius, H. C. in Inherited Diseases 125. Meltzer, S. M., Monk, B. J. & Tewari, K. S. Green tea 142. Hadvary, P., Lengsfeld, H. & Wolfer, H. Inhibition of of Amino Acid Metabolism (eds Bickel, H. & Wachtel, catechins for treatment of external genital warts. Am. pancreatic lipase in vitro by the covalent inhibitor U.) 104–121 (Georg Thieme, Stuttgart, 1985).
J. Obstet. Gynecol. 200, 233.e1–233.e7 (2009).
tetrahydrolipstatin. Biochem. J. 256, 357–361 (1988).
160. Kure, S. et al. Tetrahydrobiopterin-responsive 126. Vezina, C., Kudelski, A. & Shegal, S. N. Rapamycin. 143. Hazuda, D. J. et al. Inhibitors of strand transfer that phenylalanine hydroxylase deficiency. J. Pediatr. 135,
(AY-22,989), a new antifungal antibiotic. I. Taxomony prevent integration and inhibit HIV-1 replication in 375–378 (1999).
of the producing streptomycete and isolation of the cells. Science 287, 646–650 (2000).
161. Muntau, A. C. et al. Tetrahydrobiopterin as an active principle. J. Antibiot. 10, 721–726 (1975).
144. Summa, V. et al. Discovery of raltegravir. A potent, alternative treatment for mild phenylketonuria. 127. Richon, V. M. et al. Second generation hybrid polar selective orally bioavailable HIV-integrase inhibitor for N. Engl. J. Med. 347, 2122–2132 (2002).
compounds are potent inducers of transformed cell the treatment of HIV-AIDS infection. J. Med. Chem. 162. Mellish, K. J. & Brown, S. B. Verteporfin: a milestone differentiation. Proc. Natl Acad. Sci. USA 93,
51, 5843–5855 (2008).
in ophthalmology and photodynamic therapy. 5705–5708 (1996).
145. Buysse, D., Bate, G. & Kirkpatrick, P. Ramelteon. Expert Opin. Pharmacother. 2, 351–361
128. Marks, P. A. & Breslow, R. Dimethyl sulfoxide to Nature Rev. Drug Discov. 4, 881–882 (2005).
vorinostat: development of this histone deacetylase 146. Drucker, D. J. The biology of incretin hormones. Cell. inhibitor as an anticancer drug. Nature Biotech.25,
Metab. 3, 153–165 (2006).
84–90 (2007).
147. Cohen, H. T. & McGovern, F. J. Renal-cell carcinoma. We wish to acknowledge the employees of Roche (Palo Alto) 129. Masuda Y. et al. 3-Sulfamoylmethyl-1,2-benzisoxazole, N. Engl. J. Med. 353, 2477–2490 (2005).
who created a great environment to do drug discovery a new type of anticonvulsant drug: pharmacological 148. Atkins, M. B. et al. Innovations and challenges in renal research. We specifically thank the members of the profile. Arzneimittelforschung 30, 477–483 (1980).
cancer: consensus statement from the first international Biochemical Pharmacology Core led by A. Ford and the 130. Maibaum, J. et al. Structural modification of the P2' conference. Clin. Cancer Res. 9, 6277S–6281S (2004).
Virology Disease Biology Area led by N. Cammack for their position of 2,7-dialkyl-substituted 149. Bergers, G. et al. Benefits of targeting both pericytes support and encouragement. D.C.S. also wishes to thank the and endothelial cells in the tumor vasculature with many scientists whose feedback, constructive criticism and the discovery of aliskiren, a potent non-peptide human kinase inhibitors. J. Clin. Invest. 111, 1287–1295
desire to discover new medicines helped to provide the moti- renin inhibitor active after once daily dosing in vation for this work. marmosets. J. Med. Chem. 50, 4832–4844 (2007).
150. Mendel, D. B. et al. In vivo anti-tumor activity of 131. Goldberg, A. in Cancer Drug Discovery and SU11248, a novel tyrosine kinase inhibitor targeting Competing interests statement:
Development: Proteasome Inhibitors in Cancer Therapy VEGF and PDGF receptors: determination of a The authors declar: see Web (ed. Adams, J.) 17–38 (Humana, Totowa, 2004).
pharmacokinetic/pharmacodynamic relationship. version for details. 132. Stein, R. L., Ma, Y. T. & Brand, S. Inhibitors of the 26s Clin. Cancer Res. 9, 327–337 (2003).
proteolytic complex and the 20s proteasome 151. De Clercq, E. Strategies in the design of antiviral contained therein. US Patent 5,693,617 (1995).
drugs. Nature Rev. Drug Discov. 1, 13–25 (2002).
133. Decaux, G., Soupart, A. & Vassart, G. Non-peptide 152. Boismare, F. et al. A homotaurine derivative reduces arginine-vasopressin antagonists: the vaptans. Lancet the voluntary intake of ethanol by rats: are cerebral 371, 1624–1632 (2008).
GABA receptors involved? Pharmacol. Biochem. 134. Flexner, C. HIV drug development: the next 25 years. Behav. 21, 787–789 (1984).
Nature Rev. Drug Discov. 6, 959–966 (2007).
153. Kennedy, J. C., Pottier, R. H. & Pross, D. C. 135. Tsibris, A. M. & Kuritzkes, D. R. Chemokine Photodynamic therapy with endogenous protoporphyrin See online article:(table) (box) antagonists as therapeutics: focus on HIV-1. Annu. IX: basic principles and present clinical experience. ALL LINKS ARE ACTIVE IN THE ONLINE PDF
Rev. Med. 58, 445–459 (2007).
J. Photochem. Photobiol. B 6, 143–148 (1990).
NATURE REVIEWS DRUG DISCOVERY
VOLUME 10 JULY 2011 519
2011 Macmillan Publishers Limited. All rights reserved

Source: http://www.far.fiocruz.br/farmanguinhos/images/stories/mestrado/2012/ANALYSIS.pdf